ASURE SOFTWARE INC — Call Transcript 2026

Good afternoon, and welcome to Asure's Fireside Chat on Current Perspective on AI. This webcast will include a presentation followed by a question and answer session. I would now like to hand it over to Patrick McKillop, VP of Investor Relations. Thank you, operator, and welcome everyone to Asure's AI webcast. Today's call will contain forward-looking statements that refer to future events and as such involve some risks. We use words such as expects, leaves, and may to indicate forward-looking statements. We encourage you to review our filings with the SEC for additional information on factors that could cause actual results to differ materially from our current expectations. Specifically, our event today will include a discussion of AI, and our use of AI in connection with Asure's business. For more information about certain risks to our business as a result of the emergence of AI and our use of artificial intelligence, please see our risk factors in Item 1A on our Form 10-K filed with the SEC on February 26, 2026. Now, what I'd like to do is walk you through today's agenda. These are our forward-looking statements I just referenced. For the agenda today, we have four different sections. We have Pat Goepel, Asure Chairman and CEO, as well as Yasmine Rodriguez, who is our Chief Technology Officer. In the first section, we plan to talk about how AI is reshaping enterprise software economics. In the second section, we wanna talk about Asure's platform execution infrastructure. In the third section, we're gonna talk about structural advantages of Asure's execution platform. Finally, in section four, we're gonna talk about how AI expands Asure's operating leverage. With that, I'd like to move on to the first section and hand it over to Pat Goepel, Chairman and CEO. Yeah. Thank you, Patrick. Hey, I'm really excited to be here today. Wow, we set up this as an adjunct investor meeting, and I got calls from employees and clients and friends that I haven't seen in a couple of years. It feels like everybody's talking about AI and wants to hear more about the topic. With me, Patrick introduced our CTO, Yasmine Rodriguez. I gotta tell you, I've been working closely with her for six years, and she is a game changer, and there's nobody I'd rather be on this panel with than Yasmine. You'll hear plenty from her. Really excited about her presenting what she's helped us do and really drove within Asure. We're gonna get right into it, but can't wait for the conversation. First of all, section one, AI is reshaping enterprise software economics. If I go to the next slide. Hey, there's always changes in technology, and, I'm old enough to think about whether it's mainframes and DOS to Windows to client server to the Internet to mobile to AI. Let's talk about that. With this model, if you think about it, remember when mainframe went to the PCs, COBOL for a long time was the fastest cruncher of data. Still today, there's COBOL systems in. It's not an either/or, but where we think it really is AI and software together that's ultimately gonna be the answer. Before we even talk about the answer, if you think about how AI is reshaping enterprise software economics, similar to those days with COBOL, which was very narrow on a calculation engine, AI is different in that it gets data from all over the place very, very quickly and can come back with a probabilistic answer or a directionally correct answer very, very quickly. If you think of businesses that might be at a disruption risk, consulting and labor services around consulting, where they're looking for a large amount of probable outcomes and large amount of data, they're gonna be more apt to be disruptive. Next on the continuum for SaaS, where capabilities are increasingly getting automated, and AI can help not only in the software component of that, but also with agents as well as workflow items, etc. System of records has some defensible and structural advantages, and that's operational data or the data that's proprietary that really is almost system of record data, but data where action could begin, where you need that data as a premise, as part of moving forward. There's to the right where you have execution infrastructure around it, where it's a regulated transaction, maybe money movement or API agencies or a risk legal kinda documentation compliance offering where you really have highly regulated data, and you have to be 100% right. Very, very different on the continuum. The next slide. If we know that coming into it and we look at it, and we're gonna introduce some concepts here, but on the left, you have what I talked about on the bottom left, if you have, hey, I wanna be directionally correct, and I wanna have various levels of outcome, consulting and labor services, you can get there pretty quickly with AI. With just being directionally, perhaps, more advantageous than when it started. Now, if you wanna get pretty deterministic or with a very secure outcome, system of record will help in the top left. In the third quadrant there with feature SaaS, where your computation is probabilistic, your execution infrastructure is high, now that you have a lot of software tools for knowledge work, AI agents can replicate the features, you're gonna have some risk, but where you have execution infrastructure. If you think about it, the money movement, and we move roughly $20 billion today. We have 100,000 clients where we have platform of very, very secure data with Social Security numbers and wage, et cetera. Where its clients cannot easily replicate, that's a execution infrastructure that will actually accelerate where software meets an AI, especially if you embed AI with the software right from the ground up. We're gonna talk a little bit about that, but we think we're in the right quadrant here, and that's why we are so excited about hitting this topic head on. Next question or next slide, I should say. Why the execution platforms behave differently. First of all, the revenue model will tell you where there might be disruption. You see in the news or you see on CNBC where seat subscriptions or SaaS companies that have a revenue model that's all around people as opposed to agents, they gotta kinda pivot to outcomes. The good news with execution infrastructure that Asure has, we already have that outcome where we get paid when people get paid. We get paid on the amount of transactions. The good news here is our model is in place, and our model doesn't change with AI. AI will enhance some of the execution, pricing on the model, which gives us in really a competitive advantage here. The AI on traditional SaaS, where it replicates features, the AI automates delivery. When I think of kind of our market, you have software tools, you have software enablement, you have software workflow, and you have ultimately people that execute that. Software with AI opens up a huge opportunity here where we might have played in one of those areas, but now we can potentially play in all four. When you think about operating leverage expense, let's just take the category of people. If you have, like we do, 100,000 customers where we have a payroll person potentially or an HR person, we have people within our service delivery infrastructure. If you look at the end-to-end process, and remember, end-to-end process starts at the customer wall all the way to our walls and back. Well, now you have four areas, whether it's people, whether it's workflow, whether it's enablement, or you also have the baseline kind of transaction, where now you have the ability to open up a bigger market. Some analysts, such as Sapphire and some of the work Gartner and others that have done it, opens up this possibility close to 50 times. Over time, we believe we're at a structural advantage that will ultimately compound and accelerate over time with software using AI. The next slide. What is it about our platform and execution infrastructure? This is the longest 11 minutes that Yasmine has let me talk unfettered. I'm gonna bring in Yasmine Rodriguez, our CTO, to talk about the execution infrastructure that we really have the foundation for, what we just talked about. Thank you, Pat. It was a good time. I was good. I'm gonna start really by reframing a question. I wake up every morning, the first thing I look at, what is the latest post out there about AI? The question that the market keeps asking, is AI a threat to your business? I think in my humble opinion it's the wrong question, or maybe it's an incomplete one. The right question should be, does AI affect your specific business model positively or negatively? AI is absolutely reshaping the enterprise software economics. Absolutely. That's not even a dispute today. Software features are gonna continuously be automated. Cost structures are gonna shift across every category. The impact is gonna vary enormously by business model. For Asure, the answer is gonna be a positive impact, and we're gonna go through that today. It's structurally positive. Three things if I was to have you walk away with today after our presentation with Pat. One AI affects business models totally differently. Second, the revenue structure is what determines the AI impact. Third, and you heard Pat talk about it, the execution platform is where Asure sits across the board. You saw it on the spectrum, you saw it on the execution. Asure sits there. What we do is gain operating leverage as AI scales, not the other way around. Let's get started on how that works. Let's go to the next slide, please. Okay. We all know that AI can reason. Most of us has used it. It can analyze, it could summarize, it could recommend, it could generate. I mean, it's impressive. What it cannot do is execute in a regulated world of work without infrastructure. Traditional SaaS has features and a system of records. Asure has all of that, but in addition to that, it has three additional layers that are key. Statutory system. We are, at Asure, a registered IRS bulk filer. We are the legal agent with the authority to file on behalf of thousands of employers. We've been doing it for years. We are fully accountable to the outcome of our filing. That relationship is really earned through demonstrated operational history and regularity approval. It cannot be something you just download, and you get it. The tax laws that are out there are updated continuously. Sometimes agencies release detail right before a due date. One may argue AI is absolutely capable of reading an IRS update online in real-time. Yeah, it can. But reading a rule and being authorized to act upon it are completely different. Asure doesn't just know the rule changed, we file under it. We hold the power of attorney with tax agencies on behalf of our client. That is a legal trust relationship with the regulator. This is not just a software integration and APIs. Let's go to the compliance systems. Every payroll calculation has to be traceable, reproducible, defensible on demand under an audit. Federal law requires those payroll records to be retained for the minimum of three years, in some cases, seven. Regulators are not gonna accept it's because the AI said so as the documentation. A payroll tax filing error is not just a bug report on an integration. It results in IRS penalties, state interest charges, direct employer liability. That is that accountability that lands on Asure, not on the model that helped us actually calculate it. Last is your financial risks. Asure participates in ACH networks. We operate under NACHA risk controls. We maintain knowing your customers, the banking laws, anti-money laundering, the BSA Act. We hold money transmitter licenses across the state that require them. Each of these require separate application, and for those that ever went through this, it required a surety bond, audited financials, regulatory approvals. Some take up to 12-18 months just to review your application. In summary, AI can reason about the money movement, about all of it, but Asure is actually the one authorized to move it. If you keep in mind, knowledge is not what gives you authorization. Being aware of something does not hold you accountable. An AI system can know every tax code in every jurisdiction, and it still cannot file a single return on your behalf or bear a single dollar of liability. Asure can, and we do that every single day. Now move to the next slide, please. I want you to look at the flow left to right, and because this is the architectural reality that works in our favor today. On the left is AI reasoning, agents, copilots, models. Excellent at that probabilistic reasoning. They analyze, they recommend, they decide. This is where the AI ecosystem lives today, your OpenAI, your Microsoft Copilot, all these models. The minute any of these need to act or take an action, they have to make a system request. They have to do it through event triggers. Notice what sits at the center of that request. It's Asure Luna. You guys are gonna hear me talk a lot about Asure Luna, our AI agent. Beginning of 2025 is when we actually released our AI agent, Luna. It's not just a chatbot AI Luna is capable of actually performing actions on behalf of the employees and the customer. We've done that in beginning 2025. We launched Luna really, and we kept on growing Luna with more actions taking. Luna is not connecting to our payroll system from the outside, she runs within it. Within our architecture, our infrastructure, we were at the right time of a modernization journey that we embedded her into the architecture. Luna, as you see there, is the bridge between that entire external AI and action-taking AI engine inside a live regulated payroll platform. Luna does not connect to the payroll again from the outside, she's within it. When a system request comes in and hits the system of record, whether it's payroll, tax, employee data, it is verified, it is audited, it is legally defensible. It's not just a general database, it's a license compliance approved execution platform. On the right, that deterministic execution, the real-world outcome, money movement, as we said, tax filing, IRS, this is where AI recommendation becomes a legal transaction. Real accountability behind it. An AI agent all the way on the left cannot just skip and go right to the right side. It needs that orchestration layer. It needs our Luna. It needs our AI. The system of record, the regulated execution infrastructure that we built, and all of that does exist today in Asure. We're not competing with anything on the left, any of the AI models. We are that infrastructure that AI model will need to reach to the right. As AI adoption grows, that dependency only deepens. It does not shrink on our side. Next slide, please. In a world where every company has AI copilot, let's say the future coming, what happens to the platform underneath it? The answer is right on the slide. They don't get bypassed. They become even more valuable. External AI system, whether Microsoft Copilot, any other agent platform, connecting through the Luna orchestrator to execute payroll, perform tax actions, compliance actions securely. The AI is the interface, Asure is the engine behind it. I'm gonna give you an example. It's a favorite for our CFO, by the way. A CFO is budgeting in Excel. He's living in Excel, picks up Microsoft Copilot, which is embedded in Excel. The CFO would type, "Model a 3% raise effective January first all the way to July first. And by the way, show me the payroll cost, the tax impact, the cash flow effect." Copilot invokes Luna, the orchestrator, via secure API. Luna pulls live headcount. Why? 'Cause Luna is in the payroll system. It pulls tax directly from Asure Central, applies compliance awareness logic across every jurisdiction. You're gonna see some of that in our demo later. It returns a real P&L and cash impact instantly. There's no separate login. You don't have to log out of Excel, go into Asure Central to pull the data. There is no export. There's no manual modeling. Excel stays the interface, Asure remains the system of record, Luna remains the orchestrator. Let's take another one for HR. An HR manager gets a Slack message: "We're hiring three engineers in Texas and two in Pennsylvania starting next month. What's the fully loaded cost?" HR ask the Copilot Studio agent the same question. Again, what does the agent do? It invokes Luna orchestrator. Luna pulls current salary benchmark, calculates employer-side payroll taxes by state. It includes local Pennsylvania data, applies the benefit load, and returns a fully loaded cost per head within seconds. No spreadsheet, no call to finance, no waiting, no separate login. The pattern is the same in both of those cases. AI handles the interface, Luna handles the orchestration, Asure handles the execution. The more AI copilot across our client organizations as they intake it, the more requests will come through Asure. That's not a threat. It's really a distribution advantage for us. Can I go to the next slide, please? In there, what I would like to do is I'm gonna ask the operator to run our payroll demo. What you're about to see is a payroll manager running a complete payroll cycle within Luna. You're gonna see proactive notification. You're gonna see live data retrieval, downloading. You're gonna see anomaly detection, which is key. That is actually gonna bring up any exception prior to processing the payroll. Then you're gonna get confirmation that the payroll has processed. Operator, would you please run the payroll? Yeah. Yasmine, just before we roll it, we're gonna show you this example within our Asure Central application that we've rolled out in October. If you really think about this demonstration, the demonstration will take about three minutes or so. This is about it can be a full day of work, it can be a half day of work because what happens is there's a lot of coordination over time, getting information from the time clock. Maybe somebody didn't get paid. Were they on vacation? Were they not? Maybe the person has to ask a bunch of questions. Really pay attention to the workflow and how easy it is in when AI meets software as opposed to maybe where you have to pay people, 30 days ago. With that, operator, turn on the demonstration. We've logged into Asure Central, and we're looking at the Henderson Technology payroll area. The first thing we wanna do is confirm whether any payroll has already been processed. As you can see on the screen, there are no payroll runs listed, which confirms that no payroll has been processed for this company yet. This lets us safely move forward with the next steps. After confirming that no payroll has been run, let us follow Sarah, the user responsible for processing payroll. When Sarah logs into Asure Central, which is the entry point and landing page for users to access all of their Asure applications. When Sarah logs in, Luna displays an alert for an item needing Sarah's attention. This is displayed as a notification count above the Luna icon in the bottom right of the screen. Sarah sees the notification icon and would like more information. She clicks the Luna icon, which opens Luna. Luna greets Sarah, displays suggested actions, and shows the notification count above the bell icon. Sarah clicks the notification icon. Sarah has the permissions to run payroll for her company. Timesheets have been submitted for the pay period, and it is detected that a payroll is ready to be run. An alert is sent to Sarah that payroll is ready to be processed. Sarah closes the notifications and returns to the main section of Luna. Luna again greets Sarah and reminds Sarah that there is a payroll pending her approval. Luna asks Sarah if she would like for Luna to run the payroll or if Sarah has any questions about the payroll. Sarah has questions about the payroll and asks Luna how many employees are on the payroll. Luna retrieves the information about the payroll and answers Sarah's question that there are 11 employees on the payroll for the given pay period. Luna also notes that one employee has no hours recorded for the given pay period. Luna then asks Sarah if she would like additional information or would like to run the payroll. Luna also provides suggested follow-up questions that Sarah can select if she'd like to, including one for, "Can you run the payroll for me?" Sarah still has questions and asks Luna for a summary of the payroll. Luna provides a summary of the payroll, including the pay period, pay date, employee count, a breakdown of hours per employee, and notes that Dudley Drew has no hours recorded for the pay period and that two employees have overtime. Sarah asks Luna if she can have the summary as a PDF. Luna provides a PDF for Sarah to download. All of Sarah's questions have been answered, and she has verified the data for the payroll. Sarah now asks Luna to run the payroll. Luna responds that she would be happy to run the payroll, but requests confirmation from Sarah, as well as noting that the payroll may take up to five minutes to run. Sarah confirms, and Luna runs the payroll. Luna informs Sarah that the payroll has been submitted and that it may take up to five minutes to complete. After a few minutes, the payroll has been successfully run, and a notification is sent to Sarah. The notification count increases from one to two. Sarah clicks the notification icon. The notification informs Sarah that the payroll for Henderson Technology for the 2/08/2026-2/21/2026 pay period has been completed and provides a URL to view. Sarah follows the URL and sees that her payroll has been processed. Pat. Yes. Okay. I think now that we concluded the payroll, right, demonstration, we do have one more around tax. One of the most important thing in the compliance engine when it comes to tax is really knowing the rules. I want us to see that video first, but would you like to say a couple of things, Pat, before we get started? Yeah, about a two-minute demonstration. If you think about the conversation, you're gonna see Luna kinda look at is it a tax ID or is it a tax jurisdiction? If you see when Yasmine talked about kinda setting up Pennsylvania and different states, you'll see some evidence of this. Some of you have been asking questions around scale and kinda does it impact the model. I think by this demonstration you can see it sure impacts our model and our quality as well as our cost to serve. With that, operator, can you turn on the tax demonstration? Logs into Asure Central, and a notification badge is visible above the Luna icon. Sarah opens the Luna widget and clicks the notification icon. Luna has detected that there are errors with Sarah's tax agency setup. "Action required. I found two missing agency IDs that must be resolved before your tax report can be forwarded to PTM." Sarah closes the notifications and Luna offers to help. Sarah asks what is wrong with her tax agency setup, and Luna shows the missing agency IDs. Luna retrieves Sarah's tax agency setup and highlights that she is missing agency IDs for Virginia SUI and Florida SUI. Luna gives a summary of the expected ID format for both agencies and then gives context on why these IDs are important to file and pay taxes. Sarah wants to update the missing information, but is not very familiar with tax. She mistakenly asks Luna to update her Virginia SUI rate instead of her Virginia SUI ID. Luna detects that the given value is not a SUI rate, and that Sarah may have actually meant to update the agency ID. Luna asks Sarah if she would like to update the agency ID value instead, and also points out that if this is meant to be an agency ID, that there has to be two leading zeros for Virginia SUI. Sarah asks Luna to update with the two leading zeros. Luna recognizes that Sarah means to update the agency ID, but asks Sarah for confirmation. After confirmation, Luna makes the update, shows Sarah the status of her tax agency setup, and asks if she would like to update the missing agency ID. Sarah asks for Luna to update the Florida SUI ID, and after confirmation of the change, Luna makes the update. Sarah reviews the changes to the agency IDs and asks Luna to submit the changes for her tax agency setup. With Sarah's permission, Luna begins to make these updates for Sarah and provides a summary of the changes. When the tax agency IDs have been updated, Luna notifies Sarah that the task was successfully completed. Sarah goes to view the changes for herself and confirms that they were successfully updated. Okay. Pat, it has completed. Great. If we go to the next slide. Okay. The structural advantages of Asure's execution platform. We talked a little bit about it, but really if we go to the next slide, the big advantage here. Next slide. I'm sorry. There you go. Yeah. And Yasmine, you hit it and I'll let you talk to it, but really if you think about our execution infrastructure, really whether it's regulatory, money transmitter licensing, whether it's the banking, Nacha payments, et cetera, security, compliance, IRS, state agencies, local agencies. Then on the bottom here, we really talk about all the kinda things that were happening. I know Yasmine and I both had as we go through the money transmitter licenses, we had to get fingerprinted, et cetera. I don't know if Claude has a fingerprint yet, but we'll answer that question here at some point. But Yasmine, I think this is the real advantage here. Absolutely, Pat. You said it as well. These are the infrastructure layers that we talk about. Each one of them is defensible, and all of them reinforce each other. They come together as an infrastructure. The regulatory infrastructure where the money transmitter licensing, those state regulatory oversight, custodial fund handling requirement, these are legal relationship, keep in mind, we said it before, with regulators. They actually acquire years of history. The security and the compliance, what you need to go through the audit with SOC controls and certification, data protection controls, audit, compliance framework, annual audits really against defined standards. There are standards you have to follow. Operational maturity over time. This is not an overnight thing that you do. Banking and payment, we talked about the ACH network participation. There are some Nacha risk controls. There are the KYC. All of these have to be in place when you are actually in an HCM system where you're dealing with people's PII. Tax filing infrastructure, the IRS bulk filer status, you said it, you gotta get fingerprinted. There is a huge process in there. There are power of attorneys that actually where you hold them with the customers that you are representing. There are agency notices that come through and that needs to be reconciled. Years of operational history with actual tax authorities. Each of these reinforce each other. AI first without this infrastructure. Sorry, Pat, go ahead. No, no. Yeah, I'm sorry, Yas, go ahead. I was just gonna say, the AI without this infrastructure in play really does not work. It becomes a liability. The hard part is not the AI piece, it's exactly what's on this slide, those four pillars. Go ahead, Pat. If you think about why this infrastructure's in place. It's really all the data gravity. What it is, if you look at the blue on this one, whether you have dental plans or health insurance or 401(k)s, local taxes, wages, Social Security numbers, that's why it's really legislated like it is. That data gravity is ultimately a compounding effect when you can use software with security, with AI to really drive transactions. Really, this infrastructure combined with the execution infrastructure and the data, this is a competitive advantage in what we can do for our customers. What we can do is really a game changer, and AI helps enable this to be really a multiplier customers. Absolutely. If I go to the next slide. I'm sorry. On the operating leverage, I'm gonna let Yasmine talk about this, because really the effect of this with the data, the legislation, et cetera, now let's show and let's talk about ways that AI embedded in our software can really help us. Yeah, absolutely, Pat. Thank you. I think if you think Luna becomes the cost reduction engine, it is one. It's that payroll query deflection. We saw it also, guys, in the demo. Fewer support tickets per cycle, guided compliance question and answers reduces the processor time. Where today a customer support representative have to answer those questions. The entry of a payroll, keying it in, that's taking it from minutes and probably 20-30 minutes effort into a two-minute and less. The automated amendment suggestion, they cut manual review. Onboarding acceleration, whether you're onboarding customers via conversational workflow that we have in our client onboarding module with Luna. Every payroll query that Luna resolve is a support ticket that doesn't need a human agent to handle it. Same revenue, lower delivery cost. In the near term, Luna becomes that revenue retention tool. It's that proactive compliance alert that increases the stickiness. You saw it with the EIN and the rate, where a user may actually enter incorrect data, and Luna will add that prevention. It alerts the user of a possibility of an error. That creates stickiness. That AI-powered anomaly detection before a payroll run reduces errors that, in most cases, most of the time churn happens because of errors. Luna itself becomes that switching cost. A client who switches platform is no longer just losing the software, they lose the AI that already learned their business and their payroll. In the long term, Luna is that competitive differentiator, AI that only works because of Asure's data depth. We compete on AI intelligence, not just the features. The platform data moat compounds with every single payroll run. AI capabilities justify that premier tier pricing. Luna, not a feature, it's the mechanism by which our margin profile improve over time without proportionally cost grows. Pat? Yeah. If you think about it, the market expansion, given that it's not only tools, it's not only enablement, it's not only workflow, it's people, our market expands, the more people we can bring awareness to or bring AI to awareness to our company and our AI-generated marketing, et cetera, can help us. It's voice activated in addition to software, so that multimedia approach is gonna bring more adoption and more asks into our environment. From a revenue retention and sentiment analysis, we get so much learning that Yasmine says compounds, and what we're finding is we can get ahead of issues before they become issues. Ultimately, that's a competitive separator for us, and it's really, really is a game changer for the model. Next slide. AI embedded across software. I talked about tools, enablement, automation, and cost out, it. at the client level. Remember, end-to-end process is not only at the four walls of Asure, but it's at the customer wall all the way and back. When you think about the people and you think about tools, you might need less L&D, you might need less HR. You can really provide and use Asure Central and our software, or you could say, "You know what? I'd rather have you use AI Asure. You get our back office, and we can grow our business." That's a much different message. It's a bigger message ultimately by embedding both. Then I know, Yas, you had a couple of examples here on product and revenue and operational efficiency. Absolutely, Pat. On the, for me, more on the R&D and the product itself, right? Today, approximately 70% of any new code is generated with AI tool as a co-assistant, as a copilot. Our UX prototyping, where you used to have to spend probably days coming up with a prototype just to share the idea of the vision of a solution, now it's done in minutes. Where we are not only able to show the prototype, we're allowing them to walk through the functionality before we write the line of code, get in alignment. Legacy code translated and modernized by AI. We're only shipping faster with the same team. We are running faster through our roadmap because of the use of AI. I think on the revenue itself, productivity, right, Pat? If you wanna take on what our team is doing today as well. Yeah. Just in the interest of time, I'll let you read or let the investors read, but really some nice changes that we've highlighted on the earnings call. On the next slide. When you look at kinda some of those operating leverage and AI adoption, what it really does for us and Yasmine, I think you talked about the three items initially that you wanted to bring home. Maybe, Yas, if you could do that, and then I'll wrap it up for questions. Yeah. Sure, Pat. I think the most important thing that we wanted to, those three items, AI affects your business model differently. It does. Not all software are equally exposed, absolutely, is your second, whether it's a labor hour or it's an execution platform. The market has been really pricing AI risk broadly across multiple software. So what matters, the execution layer is what is important, and Asure is in there. We are not hoping. When we look at Sorry. Go ahead, Pat. I'm sorry, Yas. There's a little bit of a delay, so I apologize. No. Go ahead. No, I was just gonna talk a little bit more about the execution platform, but in the essence of time, I'll let you do it. I'll let you run it this time. Okay. With that, all across Asure, we create structural operating leverage, and we talked about that. What that means for you as an investor over time is if you look to the next slide, what you have is. The next slide, Patrick, is over time here, what we've done a nice job is building a business, and then where we build the business, we're at $200 million, roughly 30% margin. We see opportunities to accelerate growth. We see opportunities to have fixed cost absorption. We also see opportunities we can grow revenue faster than cost with really using AI embedded with software in the sense of where we can look at tools, we can look at enablement, we look at workflow. Ultimately, we look at people and where we can grow faster the revenue. By looking at the end-to-end process, not only in our four walls, but also within the customer, that opens up huge scale advantages, not only in payroll, but if you think about our business, whether it's insurance, 401(k), money movement, tax filing, all the agencies, now you have an infrastructure that can be accelerated with AI as opposed to at risk. If we go to the next slide. We talked about execution infrastructure. Yasmine talked about it, why it's a strategic advantage. We feel it strongly that it is. We see where we're positioned. We wanna make sure as a discerning investor, you look at the opportunity of Asure software, and you look at our business in a different way or in a way that really is an acceleration here. We're excited to offer that point of view today. With that, Patrick, if we have questions, Yasmine and I would be happy to answer them. Okay. Great, Pat. Just getting some questions here on the web, and we'll check for any people that are submitting questions online. First up, just one question is: What would it actually take for an AI company to become an IRS bulk filer and start executing payroll tax filings directly? Are the barriers primarily regulatory, operational or technical? All three. I was gonna say. Yasmine, I don't know if you wanna add any color there. No, it's absolutely, it's what you said. It's all of the above. It requires all of it, right? It's you gotta become a reporting agent, that is, the forms that you have to fill in, and that is, of course, the fingerprinting. There is a lot that needs to be in place. Plus, what comes with it is really the knowledge and the authority that you have gained throughout years of experience with the IRS. It's not something that any company can just turn on and become an IRS bulk filer. Patrick, I always go to the example, I go to the mailbox every day, and I have 100,000 companies that we process payroll and taxes for, and I'm always disappointed because I never get a letter from the IRS saying, "Hey, Pat, great job on those taxes." If there's a problem, I certainly get a letter, and we work through with our clients to make sure those get resolved. It's a negative satisfier business where perfection is expected, but if you have risk and you have a problem, it takes a little bit of know-how to work through in getting those problems solved, and that's really the key. We think we can use AI to our advantage, and we don't think it'll replace it anytime soon. Next question. Let's see here. Where are you already seeing tangible reductions in cost to serve from AI? Support operations, compliance, workflows, onboarding or somewhere else? Yeah. Honestly, all of the above. I think I thought Yasmine and Luna did a great job, and Sarah on the demo to point out the payroll, the tax filing. If you think about the workflow within your own company, how quickly we went through that demonstration and how streamlined those questions got answered and the process got run. If you think about where we are as a growing business, I think you're gonna see us grow more revenue faster than we're adding people, and that's by layering in those opportunities, and then we're expanding our marketplace because we're taking on more. Really excited about that opportunity, but those are the items that you've seen. Okay. Operator, can we just check to see if we have any questions from folks that may have dialed in on the phone here? Yes. I don't see any questions. Okay. We'll just continue with ones that are coming in over the web here. Next question is, "The Luna value proposition is very clear, but can you please talk about how are you going about monetizing the product and driving adoption? Yas, do you wanna talk about that or you want me to? You could go ahead, and I'll add to it, Pat. Yeah. No, I think what first of all, monetizing adoption, we could do a lot more. If you think about all the data that we have, what's interesting is we bring Asure Essential together. We're talking about attach rates. We're talking about revenue per unit. Because now when we sit on this kind of data and we have the tools, the workflow, ultimately now, when somebody has 50 employees and they need work site reporting, we can automatically enroll that client. All they have to do is check yes in work site reporting. That comes with a fee. It also is regulatory. 20 employees, COBRA starts. It comes with a fee, it's regulatory, and we can ask them proactively if they want us to handle it or themselves. If you think about the bigger kind of question as well, we can go to a small business and say, "Listen, we have all the products and services that you can use with software, but if you want Asure to help you and do it all for you or with you, we can do that." That opens up a big marketplace. Then, I don't know, lately, if you've seen all the work we've done with tax filing, money movement, treasury management. We have an ability to continue to grow to help customers. AsurePay is a prime example where we now have earned wage access in addition to a default, kind of opportunity to get people paid right away and get a little bit interest on their bank account. Number of different ways, we're gonna continue to talk through all those items on the quarterly call. Okay, Pat. Looks like we're just about out of time. I don't see any other questions popping in at this second, so I don't know if you wanna take a minute and kind of wrap things up. Yeah, absolutely. First of all, I wanna thank Yasmine Rodriguez. I tell you, she's a Chief Technology Officer second to none. She's done a great job here building the foundation with AI and Asure. She and I talked about this with our management team probably a little over two years ago and really excited about it. What you're seeing sometimes, the best laid plans happen either overnight or a couple years in the making, and in this case, it was a couple years making. We believe we're at a really good inflection point within the business. We hope you came away and you learned something today or you understand a little bit more about Asure. And we have quarterly calls. We also are available through investor relations. Patrick always makes himself available. As if you have questions or comments, please reach out to us. We're excited about the opportunity and really wanna thank you for taking and investing some time today. Yes, thank you all. Thank you all. Operator, I think we can log off now. Thank you. Thank you.

Speaker 1: Good afternoon, and welcome to Asure's Fireside Chat on Current Perspective on AI. This webcast will include a presentation followed by a question and answer session. I would now like to hand it over to Patrick McKillop, VP of Investor Relations. Good afternoon, and welcome to Asure's Fireside Chat on Current Perspective on AI. good afternoon and welcome to asure's fireside chat on current perspective on ai This webcast will include a presentation followed by a question and answer session. this webcast will include a presentation followed by a question and answer session I would now like to hand it over to Patrick McKillop, VP of Investor Relations. i would now like to hand it over to patrick mckillop vp of investor relations

Speaker 3: Thank you, operator, and welcome everyone to Asure's AI webcast. Today's call will contain forward-looking statements that refer to future events and as such involve some risks. We use words such as expects, leaves, and may to indicate forward-looking statements. We encourage you to review our filings with the SEC for additional information on factors that could cause actual results to differ materially from our current expectations. Specifically, our event today will include a discussion of AI, and our use of AI in connection with Asure's business. For more information about certain risks to our business as a result of the emergence of AI and our use of artificial intelligence, please see our risk factors in Item 1A on our Form 10-K filed with the SEC on February 26, 2026. Now, what I'd like to do is walk you through today's agenda. Thank you, operator, and welcome everyone to Asure's AI webcast. thank you operator and welcome everyone to asure's ai webcast Today's call will contain forward-looking statements that refer to future events and as such involve some risks. today's call will contain forward-looking statements that refer to future events and as such involve some risks We use words such as expects, leaves, and may to indicate forward-looking statements. we use words such as expects leaves and may to indicate forward-looking statements We encourage you to review our filings with the SEC for additional information on factors that could cause actual results to differ materially from our current expectations. we encourage you to review our filings with the sec for additional information on factors that could cause actual results to differ materially from our current expectations Specifically, our event today will include a discussion of AI, and our use of AI in connection with Asure's business. specifically our event today will include a discussion of ai and our use of ai in connection with asure's business For more information about certain risks to our business as a result of the emergence of AI and our use of artificial intelligence, please see our risk factors in Item 1A on our Form 10-K filed with the SEC on February 26, 2026. for more information about certain risks to our business as a result of the emergence of ai and our use of artificial intelligence please see our risk factors in item 1a on our form 10-k filed with the sec on february 26 2026 Now, what I'd like to do is walk you through today's agenda. now what i'd like to do is walk you through today's agenda These are our forward-looking statements I just referenced. For the agenda today, we have four different sections. We have Pat Goepel, Asure Chairman and CEO, as well as Yasmine Rodriguez, who is our Chief Technology Officer. In the first section, we plan to talk about how AI is reshaping enterprise software economics. In the second section, we wanna talk about Asure's platform execution infrastructure. In the third section, we're gonna talk about structural advantages of Asure's execution platform. Finally, in section four, we're gonna talk about how AI expands Asure's operating leverage. With that, I'd like to move on to the first section and hand it over to Pat Goepel, Chairman and CEO. These are our forward-looking statements I just referenced. these are our forward-looking statements i just referenced For the agenda today, we have four different sections. for the agenda today we have four different sections We have Pat Goepel, Asure Chairman and CEO, as well as Yasmine Rodriguez, who is our Chief Technology Officer. we have pat goepel asure chairman and ceo as well as yasmine rodriguez who is our chief technology officer In the first section, we plan to talk about how AI is reshaping enterprise software economics. in the first section we plan to talk about how ai is reshaping enterprise software economics In the second section, we wanna talk about Asure's platform execution infrastructure. in the second section we wanna talk about asure's platform execution infrastructure In the third section, we're gonna talk about structural advantages of Asure's execution platform. in the third section we're gonna talk about structural advantages of asure's execution platform Finally, in section four, we're gonna talk about how AI expands Asure's operating leverage. finally in section four we're gonna talk about how ai expands asure's operating leverage With that, I'd like to move on to the first section and hand it over to Pat Goepel, Chairman and CEO. with that i'd like to move on to the first section and hand it over to pat goepel chairman and ceo

Speaker 2: Yeah. Thank you, Patrick. Hey, I'm really excited to be here today. Wow, we set up this as an adjunct investor meeting, and I got calls from employees and clients and friends that I haven't seen in a couple of years. It feels like everybody's talking about AI and wants to hear more about the topic. With me, Patrick introduced our CTO, Yasmine Rodriguez. I gotta tell you, I've been working closely with her for six years, and she is a game changer, and there's nobody I'd rather be on this panel with than Yasmine. You'll hear plenty from her. Really excited about her presenting what she's helped us do and really drove within Asure. We're gonna get right into it, but can't wait for the conversation. Yeah. yeah Thank you, Patrick. thank you patrick Hey, I'm really excited to be here today. hey i'm really excited to be here today Wow, we set up this as an adjunct investor meeting, and I got calls from employees and clients and friends that I haven't seen in a couple of years. wow we set up this as an adjunct investor meeting and i got calls from employees and clients and friends that i haven't seen in a couple of years It feels like everybody's talking about AI and wants to hear more about the topic. it feels like everybody's talking about ai and wants to hear more about the topic With me, Patrick introduced our CTO, Yasmine Rodriguez. with me patrick introduced our cto yasmine rodriguez I gotta tell you, I've been working closely with her for six years, and she is a game changer, and there's nobody I'd rather be on this panel with than Yasmine. i gotta tell you i've been working closely with her for six years and she is a game changer and there's nobody i'd rather be on this panel with than yasmine You'll hear plenty from her. you'll hear plenty from her Really excited about her presenting what she's helped us do and really drove within Asure. really excited about her presenting what she's helped us do and really drove within asure We're gonna get right into it, but can't wait for the conversation. we're gonna get right into it but can't wait for the conversation First of all, section one, AI is reshaping enterprise software economics. If I go to the next slide. Hey, there's always changes in technology, and, I'm old enough to think about whether it's mainframes and DOS to Windows to client server to the Internet to mobile to AI. Let's talk about that. With this model, if you think about it, remember when mainframe went to the PCs, COBOL for a long time was the fastest cruncher of data. Still today, there's COBOL systems in. It's not an either/or, but where we think it really is AI and software together that's ultimately gonna be the answer. First of all, section one, AI is reshaping enterprise software economics. first of all section one ai is reshaping enterprise software economics If I go to the next slide. if i go to the next slide Hey, there's always changes in technology, and, I'm old enough to think about whether it's mainframes and DOS to Windows to client server to the Internet to mobile to AI. hey there's always changes in technology and i'm old enough to think about whether it's mainframes and dos to windows to client server to the internet to mobile to ai Let's talk about that. let's talk about that With this model, if you think about it, remember when mainframe went to the PCs, COBOL for a long time was the fastest cruncher of data. with this model if you think about it remember when mainframe went to the pcs cobol for a long time was the fastest cruncher of data Still today, there's COBOL systems in. still today there's cobol systems in It's not an either/or, but where we think it really is AI and software together that's ultimately gonna be the answer. it's not an either/or but where we think it really is ai and software together that's ultimately gonna be the answer Before we even talk about the answer, if you think about how AI is reshaping enterprise software economics, similar to those days with COBOL, which was very narrow on a calculation engine, AI is different in that it gets data from all over the place very, very quickly and can come back with a probabilistic answer or a directionally correct answer very, very quickly. If you think of businesses that might be at a disruption risk, consulting and labor services around consulting, where they're looking for a large amount of probable outcomes and large amount of data, they're gonna be more apt to be disruptive. Next on the continuum for SaaS, where capabilities are increasingly getting automated, and AI can help not only in the software component of that, but also with agents as well as workflow items, etc. Before we even talk about the answer, if you think about how AI is reshaping enterprise software economics, similar to those days with COBOL, which was very narrow on a calculation engine, AI is different in that it gets data from all over the place very, very quickly and can come back with a probabilistic answer or a directionally correct answer very, very quickly. before we even talk about the answer if you think about how ai is reshaping enterprise software economics similar to those days with cobol which was very narrow on a calculation engine ai is different in that it gets data from all over the place very very quickly and can come back with a probabilistic answer or a directionally correct answer very very quickly If you think of businesses that might be at a disruption risk, consulting and labor services around consulting, where they're looking for a large amount of probable outcomes and large amount of data, they're gonna be more apt to be disruptive. if you think of businesses that might be at a disruption risk consulting and labor services around consulting where they're looking for a large amount of probable outcomes and large amount of data they're gonna be more apt to be disruptive Next on the continuum for SaaS, where capabilities are increasingly getting automated, and AI can help not only in the software component of that, but also with agents as well as workflow items, etc. next on the continuum for saas where capabilities are increasingly getting automated and ai can help not only in the software component of that but also with agents as well as workflow items etc System of records has some defensible and structural advantages, and that's operational data or the data that's proprietary that really is almost system of record data, but data where action could begin, where you need that data as a premise, as part of moving forward. There's to the right where you have execution infrastructure around it, where it's a regulated transaction, maybe money movement or API agencies or a risk legal kinda documentation compliance offering where you really have highly regulated data, and you have to be 100% right. Very, very different on the continuum. The next slide. System of records has some defensible and structural advantages, and that's operational data or the data that's proprietary that really is almost system of record data, but data where action could begin, where you need that data as a premise, as part of moving forward. system of records has some defensible and structural advantages and that's operational data or the data that's proprietary that really is almost system of record data but data where action could begin where you need that data as a premise as part of moving forward There's to the right where you have execution infrastructure around it, where it's a regulated transaction, maybe money movement or API agencies or a risk legal kinda documentation compliance offering where you really have highly regulated data, and you have to be 100% right. there's to the right where you have execution infrastructure around it where it's a regulated transaction maybe money movement or api agencies or a risk legal kinda documentation compliance offering where you really have highly regulated data and you have to be 100% right Very, very different on the continuum. very very different on the continuum The next slide. the next slide If we know that coming into it and we look at it, and we're gonna introduce some concepts here, but on the left, you have what I talked about on the bottom left, if you have, hey, I wanna be directionally correct, and I wanna have various levels of outcome, consulting and labor services, you can get there pretty quickly with AI. With just being directionally, perhaps, more advantageous than when it started. Now, if you wanna get pretty deterministic or with a very secure outcome, system of record will help in the top left. If we know that coming into it and we look at it, and we're gonna introduce some concepts here, but on the left, you have what I talked about on the bottom left , if you have, hey, I wanna be directionally correct, and I wanna have various levels of outcome, consulting and labor services, you can get there pretty quickly with AI. With just being directionally, perhaps , more advantageous than when it started. if we know that coming into it and we look at it and we're gonna introduce some concepts here but on the left you have what i talked about on the bottom left if you have hey i wanna be directionally correct and i wanna have various levels of outcome consulting and labor services you can get there pretty quickly with ai. with just being directionally perhaps more advantageous than when it started Now, if you wanna get pretty deterministic or with a very secure outcome, system of record will help in the top left. now if you wanna get pretty deterministic or with a very secure outcome system of record will help in the top left In the third quadrant there with feature SaaS, where your computation is probabilistic, your execution infrastructure is high, now that you have a lot of software tools for knowledge work, AI agents can replicate the features, you're gonna have some risk, but where you have execution infrastructure. If you think about it, the money movement, and we move roughly $20 billion today. We have 100,000 clients where we have platform of very, very secure data with Social Security numbers and wage, et cetera. Where its clients cannot easily replicate, that's a execution infrastructure that will actually accelerate where software meets an AI, especially if you embed AI with the software right from the ground up. In the third quadrant there with feature SaaS, where your computation is probabilistic, your execution infrastructure is high, now that you have a lot of software tools for knowledge work, AI agents can replicate the features, you're gonna have some risk, but where you have execution infrastructure. in the third quadrant there with feature saas where your computation is probabilistic your execution infrastructure is high now that you have a lot of software tools for knowledge work ai agents can replicate the features you're gonna have some risk but where you have execution infrastructure If you think about it, the money movement, and we move roughly $20 billion today. if you think about it the money movement and we move roughly $20 billion today We have 100,000 clients where we have platform of very, very secure data with Social Security numbers and wage, et cetera. we have 100,000 clients where we have platform of very very secure data with social security numbers and wage et cetera Where its clients cannot easily replicate, that's a execution infrastructure that will actually accelerate where software meets an AI, especially if you embed AI with the software right from the ground up. where its clients cannot easily replicate that's a execution infrastructure that will actually accelerate where software meets an ai especially if you embed ai with the software right from the ground up We're gonna talk a little bit about that, but we think we're in the right quadrant here, and that's why we are so excited about hitting this topic head on. Next question or next slide, I should say. Why the execution platforms behave differently. First of all, the revenue model will tell you where there might be disruption. You see in the news or you see on CNBC where seat subscriptions or SaaS companies that have a revenue model that's all around people as opposed to agents, they gotta kinda pivot to outcomes. The good news with execution infrastructure that Asure has, we already have that outcome where we get paid when people get paid. We get paid on the amount of transactions. The good news here is our model is in place, and our model doesn't change with AI. We're gonna talk a little bit about that, but we think we're in the right quadrant here, and that's why we are so excited about hitting this topic head on. we're gonna talk a little bit about that but we think we're in the right quadrant here and that's why we are so excited about hitting this topic head on Next question or next slide, I should say. next question or next slide i should say Why the execution platforms behave differently. why the execution platforms behave differently First of all, the revenue model will tell you where there might be disruption. first of all the revenue model will tell you where there might be disruption You see in the news or you see on CNBC where seat subscriptions or SaaS companies that have a revenue model that's all around people as opposed to agents, they gotta kinda pivot to outcomes. you see in the news or you see on cnbc where seat subscriptions or saas companies that have a revenue model that's all around people as opposed to agents they gotta kinda pivot to outcomes The good news with execution infrastructure that Asure has, we already have that outcome where we get paid when people get paid. the good news with execution infrastructure that asure has we already have that outcome where we get paid when people get paid We get paid on the amount of transactions. we get paid on the amount of transactions The good news here is our model is in place, and our model doesn't change with AI. the good news here is our model is in place and our model doesn't change with ai AI will enhance some of the execution, pricing on the model, which gives us in really a competitive advantage here. The AI on traditional SaaS, where it replicates features, the AI automates delivery. When I think of kind of our market, you have software tools, you have software enablement, you have software workflow, and you have ultimately people that execute that. Software with AI opens up a huge opportunity here where we might have played in one of those areas, but now we can potentially play in all four. When you think about operating leverage expense, let's just take the category of people. If you have, like we do, 100,000 customers where we have a payroll person potentially or an HR person, we have people within our service delivery infrastructure. AI will enhance some of the execution, pricing on the model, which gives us in really a competitive advantage here. ai will enhance some of the execution pricing on the model which gives us in really a competitive advantage here The AI on traditional SaaS, where it replicates features, the AI automates delivery. the ai on traditional saas where it replicates features the ai automates delivery When I think of kind of our market, you have software tools, you have software enablement, you have software workflow, and you have ultimately people that execute that. when i think of kind of our market you have software tools you have software enablement you have software workflow and you have ultimately people that execute that Software with AI opens up a huge opportunity here where we might have played in one of those areas, but now we can potentially play in all four. software with ai opens up a huge opportunity here where we might have played in one of those areas but now we can potentially play in all four When you think about operating leverage expense, let's just take the category of people. when you think about operating leverage expense let's just take the category of people If you have, like we do, 100,000 customers where we have a payroll person potentially or an HR person, we have people within our service delivery infrastructure. if you have like we do 100,000 customers where we have a payroll person potentially or an hr person we have people within our service delivery infrastructure If you look at the end-to-end process, and remember, end-to-end process starts at the customer wall all the way to our walls and back. Well, now you have four areas, whether it's people, whether it's workflow, whether it's enablement, or you also have the baseline kind of transaction, where now you have the ability to open up a bigger market. Some analysts, such as Sapphire and some of the work Gartner and others that have done it, opens up this possibility close to 50 times. Over time, we believe we're at a structural advantage that will ultimately compound and accelerate over time with software using AI. The next slide. What is it about our platform and execution infrastructure? This is the longest 11 minutes that Yasmine has let me talk unfettered. If you look at the end-to-end process, and remember, end-to-end process starts at the customer wall all the way to our walls and back. if you look at the end-to-end process and remember end-to-end process starts at the customer wall all the way to our walls and back Well, now you have four areas, whether it's people, whether it's workflow, whether it's enablement, or you also have the baseline kind of transaction, where now you have the ability to open up a bigger market. well now you have four areas whether it's people whether it's workflow whether it's enablement or you also have the baseline kind of transaction where now you have the ability to open up a bigger market Some analysts, such as Sapphire and some of the work Gartner and others that have done it, opens up this possibility close to 50 times. some analysts such as sapphire and some of the work gartner and others that have done it opens up this possibility close to 50 times Over time, we believe we're at a structural advantage that will ultimately compound and accelerate over time with software using AI. over time we believe we're at a structural advantage that will ultimately compound and accelerate over time with software using ai The next slide. the next slide What is it about our platform and execution infrastructure? what is it about our platform and execution infrastructure This is the longest 11 minutes that Yasmine has let me talk unfettered. this is the longest 11 minutes that yasmine has let me talk unfettered I'm gonna bring in Yasmine Rodriguez, our CTO, to talk about the execution infrastructure that we really have the foundation for, what we just talked about. I'm gonna bring in Yasmine Rodriguez, our CTO, to talk about the execution infrastructure that we really have the foundation for, what we just talked about. i'm gonna bring in yasmine rodriguez our cto to talk about the execution infrastructure that we really have the foundation for what we just talked about

Speaker 4: Thank you, Pat. It was a good time. I was good. I'm gonna start really by reframing a question. I wake up every morning, the first thing I look at, what is the latest post out there about AI? The question that the market keeps asking, is AI a threat to your business? I think in my humble opinion it's the wrong question, or maybe it's an incomplete one. The right question should be, does AI affect your specific business model positively or negatively? AI is absolutely reshaping the enterprise software economics. Absolutely. That's not even a dispute today. Software features are gonna continuously be automated. Cost structures are gonna shift across every category. The impact is gonna vary enormously by business model. For Asure, the answer is gonna be a positive impact, and we're gonna go through that today. It's structurally positive. Thank you, Pat. thank you pat It was a good time. it was a good time I was good. i was good I'm gonna start really by reframing a question. i'm gonna start really by reframing a question I wake up every morning, the first thing I look at, what is the latest post out there about AI? i wake up every morning the first thing i look at what is the latest post out there about ai The question that the market keeps asking, is AI a threat to your business? the question that the market keeps asking is ai a threat to your business I think in my humble opinion it's the wrong question, or maybe it's an incomplete one. i think in my humble opinion it's the wrong question or maybe it's an incomplete one The right question should be, does AI affect your specific business model positively or negatively? the right question should be does ai affect your specific business model positively or negatively AI is absolutely reshaping the enterprise software economics. ai is absolutely reshaping the enterprise software economics Absolutely. absolutely That's not even a dispute today. that's not even a dispute today Software features are gonna continuously be automated. software features are gonna continuously be automated Cost structures are gonna shift across every category. cost structures are gonna shift across every category The impact is gonna vary enormously by business model. the impact is gonna vary enormously by business model For Asure, the answer is gonna be a positive impact, and we're gonna go through that today. for asure the answer is gonna be a positive impact and we're gonna go through that today It's structurally positive. it's structurally positive Three things if I was to have you walk away with today after our presentation with Pat. One AI affects business models totally differently. Second, the revenue structure is what determines the AI impact. Third, and you heard Pat talk about it, the execution platform is where Asure sits across the board. You saw it on the spectrum, you saw it on the execution. Asure sits there. What we do is gain operating leverage as AI scales, not the other way around. Let's get started on how that works. Let's go to the next slide, please. Okay. We all know that AI can reason. Most of us has used it. It can analyze, it could summarize, it could recommend, it could generate. I mean, it's impressive. What it cannot do is execute in a regulated world of work without infrastructure. Three things if I was to have you walk away with today after our presentation with Pat. three things if i was to have you walk away with today after our presentation with pat One AI affects business models totally differently. one ai affects business models totally differently Second, the revenue structure is what determines the AI impact. second the revenue structure is what determines the ai impact Third, and you heard Pat talk about it, the execution platform is where Asure sits across the board. third and you heard pat talk about it the execution platform is where asure sits across the board You saw it on the spectrum, you saw it on the execution. you saw it on the spectrum you saw it on the execution Asure sits there. asure sits there What we do is gain operating leverage as AI scales, not the other way around. what we do is gain operating leverage as ai scales not the other way around Let's get started on how that works. let's get started on how that works Let's go to the next slide, please. let's go to the next slide please Okay. okay We all know that AI can reason. we all know that ai can reason Most of us has used it. most of us has used it It can analyze, it could summarize, it could recommend, it could generate. it can analyze it could summarize it could recommend it could generate I mean, it's impressive. i mean it's impressive What it cannot do is execute in a regulated world of work without infrastructure. what it cannot do is execute in a regulated world of work without infrastructure Traditional SaaS has features and a system of records. Asure has all of that, but in addition to that, it has three additional layers that are key. Statutory system. We are, at Asure, a registered IRS bulk filer. We are the legal agent with the authority to file on behalf of thousands of employers. We've been doing it for years. We are fully accountable to the outcome of our filing. That relationship is really earned through demonstrated operational history and regularity approval. It cannot be something you just download, and you get it. The tax laws that are out there are updated continuously. Sometimes agencies release detail right before a due date. One may argue AI is absolutely capable of reading an IRS update online in real-time. Yeah, it can. But reading a rule and being authorized to act upon it are completely different. Traditional SaaS has features and a system of records. traditional saas has features and a system of records Asure has all of that, but in addition to that, it has three additional layers that are key. asure has all of that but in addition to that it has three additional layers that are key Statutory system. statutory system We are, at Asure, a registered IRS bulk filer. we are at asure a registered irs bulk filer We are the legal agent with the authority to file on behalf of thousands of employers. we are the legal agent with the authority to file on behalf of thousands of employers We've been doing it for years. we've been doing it for years We are fully accountable to the outcome of our filing. we are fully accountable to the outcome of our filing That relationship is really earned through demonstrated operational history and regularity approval. that relationship is really earned through demonstrated operational history and regularity approval It cannot be something you just download, and you get it. it cannot be something you just download and you get it The tax laws that are out there are updated continuously. the tax laws that are out there are updated continuously Sometimes agencies release detail right before a due date. sometimes agencies release detail right before a due date One may argue AI is absolutely capable of reading an IRS update online in real-time. one may argue ai is absolutely capable of reading an irs update online in real-time Yeah, it can. yeah it can But reading a rule and being authorized to act upon it are completely different. but reading a rule and being authorized to act upon it are completely different Asure doesn't just know the rule changed, we file under it. We hold the power of attorney with tax agencies on behalf of our client. That is a legal trust relationship with the regulator. This is not just a software integration and APIs. Let's go to the compliance systems. Every payroll calculation has to be traceable, reproducible, defensible on demand under an audit. Federal law requires those payroll records to be retained for the minimum of three years, in some cases, seven. Regulators are not gonna accept it's because the AI said so as the documentation. A payroll tax filing error is not just a bug report on an integration. It results in IRS penalties, state interest charges, direct employer liability. That is that accountability that lands on Asure, not on the model that helped us actually calculate it. Last is your financial risks. Asure participates in ACH networks. Asure doesn't just know the rule changed, we file under it. asure doesn't just know the rule changed we file under it We hold the power of attorney with tax agencies on behalf of our client. we hold the power of attorney with tax agencies on behalf of our client That is a legal trust relationship with the regulator. that is a legal trust relationship with the regulator This is not just a software integration and APIs. this is not just a software integration and apis Let's go to the compliance systems. let's go to the compliance systems Every payroll calculation has to be traceable, reproducible, defensible on demand under an audit. every payroll calculation has to be traceable reproducible defensible on demand under an audit Federal law requires those payroll records to be retained for the minimum of three years, in some cases, seven. federal law requires those payroll records to be retained for the minimum of three years in some cases seven Regulators are not gonna accept it's because the AI said so as the documentation. regulators are not gonna accept it's because the ai said so as the documentation A payroll tax filing error is not just a bug report on an integration. a payroll tax filing error is not just a bug report on an integration It results in IRS penalties, state interest charges, direct employer liability. it results in irs penalties state interest charges direct employer liability That is that accountability that lands on Asure, not on the model that helped us actually calculate it. that is that accountability that lands on asure not on the model that helped us actually calculate it Last is your financial risks. last is your financial risks Asure participates in ACH networks. asure participates in ach networks We operate under NACHA risk controls. We maintain knowing your customers, the banking laws, anti-money laundering, the BSA Act. We hold money transmitter licenses across the state that require them. Each of these require separate application, and for those that ever went through this, it required a surety bond, audited financials, regulatory approvals. Some take up to 12-18 months just to review your application. In summary, AI can reason about the money movement, about all of it, but Asure is actually the one authorized to move it. If you keep in mind, knowledge is not what gives you authorization. Being aware of something does not hold you accountable. An AI system can know every tax code in every jurisdiction, and it still cannot file a single return on your behalf or bear a single dollar of liability. We operate under NACHA risk controls. we operate under nacha risk controls We maintain knowing your customers, the banking laws, anti-money laundering, the BSA Act. we maintain knowing your customers the banking laws anti-money laundering the bsa act We hold money transmitter licenses across the state that require them. we hold money transmitter licenses across the state that require them Each of these require separate application, and for those that ever went through this, it required a surety bond, audited financials, regulatory approvals. each of these require separate application and for those that ever went through this it required a surety bond audited financials regulatory approvals Some take up to 12-18 months just to review your application. some take up to 12-18 months just to review your application In summary, AI can reason about the money movement, about all of it, but Asure is actually the one authorized to move it. in summary ai can reason about the money movement about all of it but asure is actually the one authorized to move it If you keep in mind, knowledge is not what gives you authorization. if you keep in mind knowledge is not what gives you authorization Being aware of something does not hold you accountable. being aware of something does not hold you accountable An AI system can know every tax code in every jurisdiction, and it still cannot file a single return on your behalf or bear a single dollar of liability. an ai system can know every tax code in every jurisdiction and it still cannot file a single return on your behalf or bear a single dollar of liability Asure can, and we do that every single day. Now move to the next slide, please. I want you to look at the flow left to right, and because this is the architectural reality that works in our favor today. On the left is AI reasoning, agents, copilots, models. Excellent at that probabilistic reasoning. They analyze, they recommend, they decide. This is where the AI ecosystem lives today, your OpenAI, your Microsoft Copilot, all these models. The minute any of these need to act or take an action, they have to make a system request. They have to do it through event triggers. Notice what sits at the center of that request. It's Asure Luna. You guys are gonna hear me talk a lot about Asure Luna, our AI agent. Beginning of 2025 is when we actually released our AI agent, Luna. Asure can, and we do that every single day. asure can and we do that every single day Now move to the next slide, please. now move to the next slide please I want you to look at the flow left to right, and because this is the architectural reality that works in our favor today. i want you to look at the flow left to right and because this is the architectural reality that works in our favor today On the left is AI reasoning, agents, copilots, models. on the left is ai reasoning agents copilots models Excellent at that probabilistic reasoning. excellent at that probabilistic reasoning They analyze, they recommend, they decide. they analyze they recommend they decide This is where the AI ecosystem lives today, your OpenAI, your Microsoft Copilot, all these models. this is where the ai ecosystem lives today your openai your microsoft copilot all these models The minute any of these need to act or take an action, they have to make a system request. the minute any of these need to act or take an action they have to make a system request They have to do it through event triggers. they have to do it through event triggers Notice what sits at the center of that request. notice what sits at the center of that request It's Asure Luna. it's asure luna You guys are gonna hear me talk a lot about Asure Luna, our AI agent. you guys are gonna hear me talk a lot about asure luna our ai agent Beginning of 2025 is when we actually released our AI agent, Luna. beginning of 2025 is when we actually released our ai agent luna It's not just a chatbot AI Luna is capable of actually performing actions on behalf of the employees and the customer. We've done that in beginning 2025. We launched Luna really, and we kept on growing Luna with more actions taking. Luna is not connecting to our payroll system from the outside, she runs within it. Within our architecture, our infrastructure, we were at the right time of a modernization journey that we embedded her into the architecture. Luna, as you see there, is the bridge between that entire external AI and action-taking AI engine inside a live regulated payroll platform. Luna does not connect to the payroll again from the outside, she's within it. When a system request comes in and hits the system of record, whether it's payroll, tax, employee data, it is verified, it is audited, it is legally defensible. It's not just a chatbot AI Luna is capable of actually performing actions on behalf of the employees and the customer. it's not just a chatbot ai luna is capable of actually performing actions on behalf of the employees and the customer We've done that in beginning 2025. we've done that in beginning 2025 We launched Luna really, and we kept on growing Luna with more actions taking. we launched luna really and we kept on growing luna with more actions taking Luna is not connecting to our payroll system from the outside, she runs within it. luna is not connecting to our payroll system from the outside she runs within it Within our architecture, our infrastructure, we were at the right time of a modernization journey that we embedded her into the architecture. within our architecture our infrastructure we were at the right time of a modernization journey that we embedded her into the architecture Luna, as you see there, is the bridge between that entire external AI and action-taking AI engine inside a live regulated payroll platform. luna as you see there is the bridge between that entire external ai and action-taking ai engine inside a live regulated payroll platform Luna does not connect to the payroll again from the outside, she's within it. luna does not connect to the payroll again from the outside she's within it When a system request comes in and hits the system of record, whether it's payroll, tax, employee data, it is verified, it is audited, it is legally defensible. when a system request comes in and hits the system of record whether it's payroll tax employee data it is verified it is audited it is legally defensible It's not just a general database, it's a license compliance approved execution platform. On the right, that deterministic execution, the real-world outcome, money movement, as we said, tax filing, IRS, this is where AI recommendation becomes a legal transaction. Real accountability behind it. An AI agent all the way on the left cannot just skip and go right to the right side. It needs that orchestration layer. It needs our Luna. It needs our AI. The system of record, the regulated execution infrastructure that we built, and all of that does exist today in Asure. We're not competing with anything on the left, any of the AI models. We are that infrastructure that AI model will need to reach to the right. As AI adoption grows, that dependency only deepens. It does not shrink on our side. Next slide, please. It's not just a general database, it's a license compliance approved execution platform. it's not just a general database it's a license compliance approved execution platform On the right, that deterministic execution, the real-world outcome, money movement, as we said, tax filing, IRS, this is where AI recommendation becomes a legal transaction. on the right that deterministic execution the real-world outcome money movement as we said tax filing irs this is where ai recommendation becomes a legal transaction Real accountability behind it. real accountability behind it An AI agent all the way on the left cannot just skip and go right to the right side. an ai agent all the way on the left cannot just skip and go right to the right side It needs that orchestration layer. it needs that orchestration layer It needs our Luna. it needs our luna It needs our AI. it needs our ai The system of record, the regulated execution infrastructure that we built, and all of that does exist today in Asure. the system of record the regulated execution infrastructure that we built and all of that does exist today in asure We're not competing with anything on the left, any of the AI models. we're not competing with anything on the left any of the ai models We are that infrastructure that AI model will need to reach to the right. we are that infrastructure that ai model will need to reach to the right As AI adoption grows, that dependency only deepens. as ai adoption grows that dependency only deepens It does not shrink on our side. it does not shrink on our side Next slide, please. next slide please In a world where every company has AI copilot, let's say the future coming, what happens to the platform underneath it? The answer is right on the slide. They don't get bypassed. They become even more valuable. External AI system, whether Microsoft Copilot, any other agent platform, connecting through the Luna orchestrator to execute payroll, perform tax actions, compliance actions securely. The AI is the interface, Asure is the engine behind it. I'm gonna give you an example. It's a favorite for our CFO, by the way. A CFO is budgeting in Excel. He's living in Excel, picks up Microsoft Copilot, which is embedded in Excel. The CFO would type, "Model a 3% raise effective January first all the way to July first. And by the way, show me the payroll cost, the tax impact, the cash flow effect." Copilot invokes Luna, the orchestrator, via secure API. In a world where every company has AI copilot, let's say the future coming, what happens to the platform underneath it? in a world where every company has ai copilot let's say the future coming what happens to the platform underneath it The answer is right on the slide. the answer is right on the slide They don't get bypassed. they don't get bypassed They become even more valuable. they become even more valuable External AI system, whether Microsoft Copilot, any other agent platform, connecting through the Luna orchestrator to execute payroll, perform tax actions, compliance actions securely. external ai system whether microsoft copilot any other agent platform connecting through the luna orchestrator to execute payroll perform tax actions compliance actions securely The AI is the interface, Asure is the engine behind it. the ai is the interface asure is the engine behind it I'm gonna give you an example. i'm gonna give you an example It's a favorite for our CFO, by the way. it's a favorite for our cfo by the way A CFO is budgeting in Excel. a cfo is budgeting in excel He's living in Excel, picks up Microsoft Copilot, which is embedded in Excel. he's living in excel picks up microsoft copilot which is embedded in excel The CFO would type, "Model a 3% raise effective January first all the way to July first. the cfo would type "model a 3% raise effective january first all the way to july first And by the way, show me the payroll cost, the tax impact, the cash flow effect." Copilot invokes Luna, the orchestrator, via secure API. and by the way show me the payroll cost the tax impact the cash flow effect." copilot invokes luna the orchestrator via secure api Luna pulls live headcount. Why? 'Cause Luna is in the payroll system. It pulls tax directly from Asure Central, applies compliance awareness logic across every jurisdiction. You're gonna see some of that in our demo later. It returns a real P&L and cash impact instantly. There's no separate login. You don't have to log out of Excel, go into Asure Central to pull the data. There is no export. There's no manual modeling. Excel stays the interface, Asure remains the system of record, Luna remains the orchestrator. Let's take another one for HR. An HR manager gets a Slack message: "We're hiring three engineers in Texas and two in Pennsylvania starting next month. What's the fully loaded cost?" HR ask the Copilot Studio agent the same question. Again, what does the agent do? It invokes Luna orchestrator. Luna pulls current salary benchmark, calculates employer-side payroll taxes by state. Luna pulls live headcount. luna pulls live headcount Why? 'Cause Luna is in the payroll system. why 'cause luna is in the payroll system It pulls tax directly from Asure Central, applies compliance awareness logic across every jurisdiction. it pulls tax directly from asure central applies compliance awareness logic across every jurisdiction You're gonna see some of that in our demo later. you're gonna see some of that in our demo later It returns a real P&L and cash impact instantly. it returns a real p&l and cash impact instantly There's no separate login. there's no separate login You don't have to log out of Excel, go into Asure Central to pull the data. you don't have to log out of excel go into asure central to pull the data There is no export. there is no export There's no manual modeling. there's no manual modeling Excel stays the interface, Asure remains the system of record, Luna remains the orchestrator. excel stays the interface asure remains the system of record luna remains the orchestrator Let's take another one for HR. let's take another one for hr An HR manager gets a Slack message: "We're hiring three engineers in Texas and two in Pennsylvania starting next month. an hr manager gets a slack message "we're hiring three engineers in texas and two in pennsylvania starting next month What's the fully loaded cost?" HR ask the Copilot Studio agent the same question. what's the fully loaded cost?" hr ask the copilot studio agent the same question Again, what does the agent do? again what does the agent do It invokes Luna orchestrator. it invokes luna orchestrator Luna pulls current salary benchmark, calculates employer-side payroll taxes by state. luna pulls current salary benchmark calculates employer-side payroll taxes by state It includes local Pennsylvania data, applies the benefit load, and returns a fully loaded cost per head within seconds. No spreadsheet, no call to finance, no waiting, no separate login. The pattern is the same in both of those cases. AI handles the interface, Luna handles the orchestration, Asure handles the execution. The more AI copilot across our client organizations as they intake it, the more requests will come through Asure. That's not a threat. It's really a distribution advantage for us. Can I go to the next slide, please? In there, what I would like to do is I'm gonna ask the operator to run our payroll demo. What you're about to see is a payroll manager running a complete payroll cycle within Luna. You're gonna see proactive notification. You're gonna see live data retrieval, downloading. You're gonna see anomaly detection, which is key. It includes local Pennsylvania data, applies the benefit load, and returns a fully loaded cost per head within seconds. it includes local pennsylvania data applies the benefit load and returns a fully loaded cost per head within seconds No spreadsheet, no call to finance, no waiting, no separate login. no spreadsheet no call to finance no waiting no separate login The pattern is the same in both of those cases. the pattern is the same in both of those cases AI handles the interface, Luna handles the orchestration, Asure handles the execution. ai handles the interface luna handles the orchestration asure handles the execution The more AI copilot across our client organizations as they intake it, the more requests will come through Asure. the more ai copilot across our client organizations as they intake it the more requests will come through asure That's not a threat. that's not a threat It's really a distribution advantage for us. it's really a distribution advantage for us Can I go to the next slide, please? can i go to the next slide please In there, what I would like to do is I'm gonna ask the operator to run our payroll demo. in there what i would like to do is i'm gonna ask the operator to run our payroll demo What you're about to see is a payroll manager running a complete payroll cycle within Luna. what you're about to see is a payroll manager running a complete payroll cycle within luna You're gonna see proactive notification. You're gonna see live data retrieval, downloading. you're gonna see proactive notification. you're gonna see live data retrieval downloading You're gonna see anomaly detection, which is key. you're gonna see anomaly detection which is key That is actually gonna bring up any exception prior to processing the payroll. Then you're gonna get confirmation that the payroll has processed. Operator, would you please run the payroll? That is actually gonna bring up any exception prior to processing the payroll. that is actually gonna bring up any exception prior to processing the payroll Then you're gonna get confirmation that the payroll has processed. then you're gonna get confirmation that the payroll has processed Operator, would you please run the payroll? operator would you please run the payroll

Speaker 2: Yeah. Yasmine, just before we roll it, we're gonna show you this example within our Asure Central application that we've rolled out in October. If you really think about this demonstration, the demonstration will take about three minutes or so. This is about it can be a full day of work, it can be a half day of work because what happens is there's a lot of coordination over time, getting information from the time clock. Maybe somebody didn't get paid. Were they on vacation? Were they not? Maybe the person has to ask a bunch of questions. Really pay attention to the workflow and how easy it is in when AI meets software as opposed to maybe where you have to pay people, 30 days ago. With that, operator, turn on the demonstration. Yeah. yeah Yasmine, just before we roll it, we're gonna show you this example within our Asure Central application that we've rolled out in October. yasmine just before we roll it we're gonna show you this example within our asure central application that we've rolled out in october If you really think about this demonstration, the demonstration will take about three minutes or so. if you really think about this demonstration the demonstration will take about three minutes or so This is about it can be a full day of work, it can be a half day of work because what happens is there's a lot of coordination over time, getting information from the time clock. this is about it can be a full day of work it can be a half day of work because what happens is there's a lot of coordination over time getting information from the time clock Maybe somebody didn't get paid. maybe somebody didn't get paid Were they on vacation? were they on vacation Were they not? were they not Maybe the person has to ask a bunch of questions. maybe the person has to ask a bunch of questions Really pay attention to the workflow and how easy it is in when AI meets software as opposed to maybe where you have to pay people, 30 days ago. really pay attention to the workflow and how easy it is in when ai meets software as opposed to maybe where you have to pay people 30 days ago With that, operator, turn on the demonstration. with that operator turn on the demonstration

Speaker 5: We've logged into Asure Central, and we're looking at the Henderson Technology payroll area. The first thing we wanna do is confirm whether any payroll has already been processed. As you can see on the screen, there are no payroll runs listed, which confirms that no payroll has been processed for this company yet. This lets us safely move forward with the next steps. After confirming that no payroll has been run, let us follow Sarah, the user responsible for processing payroll. When Sarah logs into Asure Central, which is the entry point and landing page for users to access all of their Asure applications. When Sarah logs in, Luna displays an alert for an item needing Sarah's attention. This is displayed as a notification count above the Luna icon in the bottom right of the screen. Sarah sees the notification icon and would like more information. We've logged into Asure Central, and we're looking at the Henderson Technology payroll area. we've logged into asure central and we're looking at the henderson technology payroll area The first thing we wanna do is confirm whether any payroll has already been processed. the first thing we wanna do is confirm whether any payroll has already been processed As you can see on the screen, there are no payroll runs listed, which confirms that no payroll has been processed for this company yet. as you can see on the screen there are no payroll runs listed which confirms that no payroll has been processed for this company yet This lets us safely move forward with the next steps. this lets us safely move forward with the next steps After confirming that no payroll has been run, let us follow Sarah, the user responsible for processing payroll. after confirming that no payroll has been run let us follow sarah the user responsible for processing payroll When Sarah logs into Asure Central, which is the entry point and landing page for users to access all of their Asure applications. when sarah logs into asure central which is the entry point and landing page for users to access all of their asure applications When Sarah logs in, Luna displays an alert for an item needing Sarah's attention. when sarah logs in luna displays an alert for an item needing sarah's attention This is displayed as a notification count above the Luna icon in the bottom right of the screen. this is displayed as a notification count above the luna icon in the bottom right of the screen Sarah sees the notification icon and would like more information. sarah sees the notification icon and would like more information She clicks the Luna icon, which opens Luna. Luna greets Sarah, displays suggested actions, and shows the notification count above the bell icon. Sarah clicks the notification icon. Sarah has the permissions to run payroll for her company. Timesheets have been submitted for the pay period, and it is detected that a payroll is ready to be run. An alert is sent to Sarah that payroll is ready to be processed. Sarah closes the notifications and returns to the main section of Luna. Luna again greets Sarah and reminds Sarah that there is a payroll pending her approval. Luna asks Sarah if she would like for Luna to run the payroll or if Sarah has any questions about the payroll. Sarah has questions about the payroll and asks Luna how many employees are on the payroll. She clicks the Luna icon, which opens Luna. she clicks the luna icon which opens luna Luna greets Sarah, displays suggested actions, and shows the notification count above the bell icon. luna greets sarah displays suggested actions and shows the notification count above the bell icon Sarah clicks the notification icon. sarah clicks the notification icon Sarah has the permissions to run payroll for her company. sarah has the permissions to run payroll for her company Timesheets have been submitted for the pay period, and it is detected that a payroll is ready to be run. timesheets have been submitted for the pay period and it is detected that a payroll is ready to be run An alert is sent to Sarah that payroll is ready to be processed. an alert is sent to sarah that payroll is ready to be processed Sarah closes the notifications and returns to the main section of Luna. sarah closes the notifications and returns to the main section of luna Luna again greets Sarah and reminds Sarah that there is a payroll pending her approval. luna again greets sarah and reminds sarah that there is a payroll pending her approval Luna asks Sarah if she would like for Luna to run the payroll or if Sarah has any questions about the payroll. luna asks sarah if she would like for luna to run the payroll or if sarah has any questions about the payroll Sarah has questions about the payroll and asks Luna how many employees are on the payroll. sarah has questions about the payroll and asks luna how many employees are on the payroll Luna retrieves the information about the payroll and answers Sarah's question that there are 11 employees on the payroll for the given pay period. Luna also notes that one employee has no hours recorded for the given pay period. Luna then asks Sarah if she would like additional information or would like to run the payroll. Luna also provides suggested follow-up questions that Sarah can select if she'd like to, including one for, "Can you run the payroll for me?" Sarah still has questions and asks Luna for a summary of the payroll. Luna provides a summary of the payroll, including the pay period, pay date, employee count, a breakdown of hours per employee, and notes that Dudley Drew has no hours recorded for the pay period and that two employees have overtime. Sarah asks Luna if she can have the summary as a PDF. Luna retrieves the information about the payroll and answers Sarah's question that there are 11 employees on the payroll for the given pay period. luna retrieves the information about the payroll and answers sarah's question that there are 11 employees on the payroll for the given pay period Luna also notes that one employee has no hours recorded for the given pay period. luna also notes that one employee has no hours recorded for the given pay period Luna then asks Sarah if she would like additional information or would like to run the payroll. luna then asks sarah if she would like additional information or would like to run the payroll Luna also provides suggested follow-up questions that Sarah can select if she'd like to, including one for, "Can you run the payroll for me?" Sarah still has questions and asks Luna for a summary of the payroll. luna also provides suggested follow-up questions that sarah can select if she'd like to including one for "can you run the payroll for me?" sarah still has questions and asks luna for a summary of the payroll Luna provides a summary of the payroll, including the pay period, pay date, employee count, a breakdown of hours per employee, and notes that Dudley Drew has no hours recorded for the pay period and that two employees have overtime. luna provides a summary of the payroll including the pay period pay date employee count a breakdown of hours per employee and notes that dudley drew has no hours recorded for the pay period and that two employees have overtime Sarah asks Luna if she can have the summary as a PDF. sarah asks luna if she can have the summary as a pdf Luna provides a PDF for Sarah to download. All of Sarah's questions have been answered, and she has verified the data for the payroll. Sarah now asks Luna to run the payroll. Luna responds that she would be happy to run the payroll, but requests confirmation from Sarah, as well as noting that the payroll may take up to five minutes to run. Sarah confirms, and Luna runs the payroll. Luna informs Sarah that the payroll has been submitted and that it may take up to five minutes to complete. After a few minutes, the payroll has been successfully run, and a notification is sent to Sarah. The notification count increases from one to two. Sarah clicks the notification icon. Luna provides a PDF for Sarah to download. luna provides a pdf for sarah to download All of Sarah's questions have been answered, and she has verified the data for the payroll. all of sarah's questions have been answered and she has verified the data for the payroll Sarah now asks Luna to run the payroll. sarah now asks luna to run the payroll Luna responds that she would be happy to run the payroll, but requests confirmation from Sarah, as well as noting that the payroll may take up to five minutes to run. luna responds that she would be happy to run the payroll but requests confirmation from sarah as well as noting that the payroll may take up to five minutes to run Sarah confirms, and Luna runs the payroll. sarah confirms and luna runs the payroll Luna informs Sarah that the payroll has been submitted and that it may take up to five minutes to complete. luna informs sarah that the payroll has been submitted and that it may take up to five minutes to complete After a few minutes, the payroll has been successfully run, and a notification is sent to Sarah. after a few minutes the payroll has been successfully run and a notification is sent to sarah The notification count increases from one to two. the notification count increases from one to two Sarah clicks the notification icon. sarah clicks the notification icon The notification informs Sarah that the payroll for Henderson Technology for the 2/08/2026-2/21/2026 pay period has been completed and provides a URL to view. Sarah follows the URL and sees that her payroll has been processed. The notification informs Sarah that the payroll for Henderson Technology for the 2/08/2026-2/21/2026 pay period has been completed and provides a URL to view. the notification informs sarah that the payroll for henderson technology for the 2/08/2026-2/21/2026 pay period has been completed and provides a url to view Sarah follows the URL and sees that her payroll has been processed. sarah follows the url and sees that her payroll has been processed

Speaker 4: Pat. Pat. pat

Speaker 2: Yes. Yes. yes

Speaker 4: Okay. I think now that we concluded the payroll, right, demonstration, we do have one more around tax. One of the most important thing in the compliance engine when it comes to tax is really knowing the rules. I want us to see that video first, but would you like to say a couple of things, Pat, before we get started? Okay. okay I think now that we concluded the payroll, right, demonstration, we do have one more around tax. i think now that we concluded the payroll right demonstration we do have one more around tax One of the most important thing in the compliance engine when it comes to tax is really knowing the rules. one of the most important thing in the compliance engine when it comes to tax is really knowing the rules I want us to see that video first, but would you like to say a couple of things, Pat, before we get started? i want us to see that video first but would you like to say a couple of things pat before we get started

Speaker 2: Yeah, about a two-minute demonstration. If you think about the conversation, you're gonna see Luna kinda look at is it a tax ID or is it a tax jurisdiction? If you see when Yasmine talked about kinda setting up Pennsylvania and different states, you'll see some evidence of this. Some of you have been asking questions around scale and kinda does it impact the model. I think by this demonstration you can see it sure impacts our model and our quality as well as our cost to serve. With that, operator, can you turn on the tax demonstration? Yeah, about a two-minute demonstration. yeah about a two-minute demonstration If you think about the conversation, you're gonna see Luna kinda look at is it a tax ID or is it a tax jurisdiction? if you think about the conversation you're gonna see luna kinda look at is it a tax id or is it a tax jurisdiction If you see when Yasmine talked about kinda setting up Pennsylvania and different states, you'll see some evidence of this. if you see when yasmine talked about kinda setting up pennsylvania and different states you'll see some evidence of this Some of you have been asking questions around scale and kinda does it impact the model. some of you have been asking questions around scale and kinda does it impact the model I think by this demonstration you can see it sure impacts our model and our quality as well as our cost to serve. i think by this demonstration you can see it sure impacts our model and our quality as well as our cost to serve With that, operator, can you turn on the tax demonstration? with that operator can you turn on the tax demonstration

Speaker 5: Logs into Asure Central, and a notification badge is visible above the Luna icon. Sarah opens the Luna widget and clicks the notification icon. Luna has detected that there are errors with Sarah's tax agency setup. "Action required. I found two missing agency IDs that must be resolved before your tax report can be forwarded to PTM." Sarah closes the notifications and Luna offers to help. Sarah asks what is wrong with her tax agency setup, and Luna shows the missing agency IDs. Luna retrieves Sarah's tax agency setup and highlights that she is missing agency IDs for Virginia SUI and Florida SUI. Luna gives a summary of the expected ID format for both agencies and then gives context on why these IDs are important to file and pay taxes. Sarah wants to update the missing information, but is not very familiar with tax. Logs into Asure Central, and a notification badge is visible above the Luna icon. logs into asure central and a notification badge is visible above the luna icon Sarah opens the Luna widget and clicks the notification icon. sarah opens the luna widget and clicks the notification icon Luna has detected that there are errors with Sarah's tax agency setup. "Action required. luna has detected that there are errors with sarah's tax agency setup "action required I found two missing agency IDs that must be resolved before your tax report can be forwarded to PTM." Sarah closes the notifications and Luna offers to help. i found two missing agency ids that must be resolved before your tax report can be forwarded to ptm." sarah closes the notifications and luna offers to help Sarah asks what is wrong with her tax agency setup, and Luna shows the missing agency IDs. sarah asks what is wrong with her tax agency setup and luna shows the missing agency ids Luna retrieves Sarah's tax agency setup and highlights that she is missing agency IDs for Virginia SUI and Florida SUI. luna retrieves sarah's tax agency setup and highlights that she is missing agency ids for virginia sui and florida sui Luna gives a summary of the expected ID format for both agencies and then gives context on why these IDs are important to file and pay taxes. luna gives a summary of the expected id format for both agencies and then gives context on why these ids are important to file and pay taxes Sarah wants to update the missing information, but is not very familiar with tax. sarah wants to update the missing information but is not very familiar with tax She mistakenly asks Luna to update her Virginia SUI rate instead of her Virginia SUI ID. Luna detects that the given value is not a SUI rate, and that Sarah may have actually meant to update the agency ID. Luna asks Sarah if she would like to update the agency ID value instead, and also points out that if this is meant to be an agency ID, that there has to be two leading zeros for Virginia SUI. Sarah asks Luna to update with the two leading zeros. Luna recognizes that Sarah means to update the agency ID, but asks Sarah for confirmation. After confirmation, Luna makes the update, shows Sarah the status of her tax agency setup, and asks if she would like to update the missing agency ID. Sarah asks for Luna to update the Florida SUI ID, and after confirmation of the change, Luna makes the update. She mistakenly asks Luna to update her Virginia SUI rate instead of her Virginia SUI ID. she mistakenly asks luna to update her virginia sui rate instead of her virginia sui id Luna detects that the given value is not a SUI rate, and that Sarah may have actually meant to update the agency ID. luna detects that the given value is not a sui rate and that sarah may have actually meant to update the agency id Luna asks Sarah if she would like to update the agency ID value instead, and also points out that if this is meant to be an agency ID, that there has to be two leading zeros for Virginia SUI. luna asks sarah if she would like to update the agency id value instead and also points out that if this is meant to be an agency id that there has to be two leading zeros for virginia sui Sarah asks Luna to update with the two leading zeros. sarah asks luna to update with the two leading zeros Luna recognizes that Sarah means to update the agency ID, but asks Sarah for confirmation. luna recognizes that sarah means to update the agency id but asks sarah for confirmation After confirmation, Luna makes the update, shows Sarah the status of her tax agency setup, and asks if she would like to update the missing agency ID. after confirmation luna makes the update shows sarah the status of her tax agency setup and asks if she would like to update the missing agency id Sarah asks for Luna to update the Florida SUI ID, and after confirmation of the change, Luna makes the update. sarah asks for luna to update the florida sui id and after confirmation of the change luna makes the update Sarah reviews the changes to the agency IDs and asks Luna to submit the changes for her tax agency setup. With Sarah's permission, Luna begins to make these updates for Sarah and provides a summary of the changes. When the tax agency IDs have been updated, Luna notifies Sarah that the task was successfully completed. Sarah goes to view the changes for herself and confirms that they were successfully updated. Sarah reviews the changes to the agency IDs and asks Luna to submit the changes for her tax agency setup. sarah reviews the changes to the agency ids and asks luna to submit the changes for her tax agency setup With Sarah's permission, Luna begins to make these updates for Sarah and provides a summary of the changes. with sarah's permission luna begins to make these updates for sarah and provides a summary of the changes When the tax agency IDs have been updated, Luna notifies Sarah that the task was successfully completed. when the tax agency ids have been updated luna notifies sarah that the task was successfully completed Sarah goes to view the changes for herself and confirms that they were successfully updated. sarah goes to view the changes for herself and confirms that they were successfully updated

Speaker 3: Okay. Okay. okay

Speaker 4: Pat, it has completed. Pat, it has completed. pat it has completed

Speaker 2: Great. If we go to the next slide. Okay. The structural advantages of Asure's execution platform. We talked a little bit about it, but really if we go to the next slide, the big advantage here. Next slide. Great. great If we go to the next slide. if we go to the next slide Okay. okay The structural advantages of Asure's execution platform. the structural advantages of asure's execution platform We talked a little bit about it, but really if we go to the next slide, the big advantage here. we talked a little bit about it but really if we go to the next slide the big advantage here Next slide. next slide

Speaker 3: I'm sorry. There you go. I'm sorry. i'm sorry There you go. there you go

Speaker 2: Yeah. And Yasmine, you hit it and I'll let you talk to it, but really if you think about our execution infrastructure, really whether it's regulatory, money transmitter licensing, whether it's the banking, Nacha payments, et cetera, security, compliance, IRS, state agencies, local agencies. Then on the bottom here, we really talk about all the kinda things that were happening. I know Yasmine and I both had as we go through the money transmitter licenses, we had to get fingerprinted, et cetera. I don't know if Claude has a fingerprint yet, but Yeah. yeah And Yasmine, you hit it and I'll let you talk to it, but really if you think about our execution infrastructure, really whether it's regulatory, money transmitter licensing, whether it's the banking, Nacha payments, et cetera, security, compliance, IRS, state agencies, local agencies. and yasmine you hit it and i'll let you talk to it but really if you think about our execution infrastructure really whether it's regulatory money transmitter licensing whether it's the banking nacha payments et cetera security compliance irs state agencies local agencies Then on the bottom here, we really talk about all the kinda things that were happening. then on the bottom here we really talk about all the kinda things that were happening I know Yasmine and I both had as we go through the money transmitter licenses, we had to get fingerprinted, et cetera. i know yasmine and i both had as we go through the money transmitter licenses we had to get fingerprinted et cetera I don't know if Claude has a fingerprint yet, but i don't know if claude has a fingerprint yet but we'll answer that question here at some point. But Yasmine, I think this is the real advantage here. we'll answer that question here at some point. we'll answer that question here at some point But Yasmine, I think this is the real advantage here. but yasmine i think this is the real advantage here

Speaker 4: Absolutely, Pat. You said it as well. These are the infrastructure layers that we talk about. Each one of them is defensible, and all of them reinforce each other. They come together as an infrastructure. The regulatory infrastructure where the money transmitter licensing, those state regulatory oversight, custodial fund handling requirement, these are legal relationship, keep in mind, we said it before, with regulators. They actually acquire years of history. The security and the compliance, what you need to go through the audit with SOC controls and certification, data protection controls, audit, compliance framework, annual audits really against defined standards. There are standards you have to follow. Operational maturity over time. This is not an overnight thing that you do. Banking and payment, we talked about the ACH network participation. There are some Nacha risk controls. There are the KYC. Absolutely, Pat. absolutely pat You said it as well. you said it as well These are the infrastructure layers that we talk about. these are the infrastructure layers that we talk about Each one of them is defensible, and all of them reinforce each other. each one of them is defensible and all of them reinforce each other They come together as an infrastructure. they come together as an infrastructure The regulatory infrastructure where the money transmitter licensing, those state regulatory oversight, custodial fund handling requirement, these are legal relationship, keep in mind, we said it before, with regulators. the regulatory infrastructure where the money transmitter licensing those state regulatory oversight custodial fund handling requirement these are legal relationship keep in mind we said it before with regulators They actually acquire years of history. they actually acquire years of history The security and the compliance, what you need to go through the audit with SOC controls and certification, data protection controls, audit, compliance framework, annual audits really against defined standards. the security and the compliance what you need to go through the audit with soc controls and certification data protection controls audit compliance framework annual audits really against defined standards There are standards you have to follow. there are standards you have to follow Operational maturity over time. operational maturity over time This is not an overnight thing that you do. this is not an overnight thing that you do Banking and payment, we talked about the ACH network participation. banking and payment we talked about the ach network participation There are some Nacha risk controls. there are some nacha risk controls There are the KYC. there are the kyc All of these have to be in place when you are actually in an HCM system where you're dealing with people's PII. Tax filing infrastructure, the IRS bulk filer status, you said it, you gotta get fingerprinted. There is a huge process in there. There are power of attorneys that actually where you hold them with the customers that you are representing. There are agency notices that come through and that needs to be reconciled. Years of operational history with actual tax authorities. Each of these reinforce each other. AI first without this infrastructure. Sorry, Pat, go ahead. All of these have to be in place when you are actually in an HCM system where you're dealing with people's PII. all of these have to be in place when you are actually in an hcm system where you're dealing with people's pii Tax filing infrastructure, the IRS bulk filer status, you said it, you gotta get fingerprinted. tax filing infrastructure the irs bulk filer status you said it you gotta get fingerprinted There is a huge process in there. there is a huge process in there There are power of attorneys that actually where you hold them with the customers that you are representing. there are power of attorneys that actually where you hold them with the customers that you are representing There are agency notices that come through and that needs to be reconciled. Years of operational history with actual tax authorities. there are agency notices that come through and that needs to be reconciled. years of operational history with actual tax authorities Each of these reinforce each other. each of these reinforce each other AI first without this infrastructure. ai first without this infrastructure Sorry, Pat, go ahead. sorry pat go ahead

Speaker 2: No, no. Yeah, I'm sorry, Yas, go ahead. No, no. no no Yeah, I'm sorry, Yas, go ahead. yeah i'm sorry yas go ahead

Speaker 4: I was just gonna say, the AI without this infrastructure in play really does not work. It becomes a liability. The hard part is not the AI piece, it's exactly what's on this slide, those four pillars. Go ahead, Pat. I was just gonna say, the AI without this infrastructure in play really does not work. i was just gonna say the ai without this infrastructure in play really does not work It becomes a liability. it becomes a liability The hard part is not the AI piece, it's exactly what's on this slide, those four pillars. the hard part is not the ai piece it's exactly what's on this slide those four pillars Go ahead, Pat. go ahead pat

Speaker 2: If you think about why this infrastructure's in place. It's really all the data gravity. What it is, if you look at the blue on this one, whether you have dental plans or health insurance or 401(k)s, local taxes, wages, Social Security numbers, that's why it's really legislated like it is. That data gravity is ultimately a compounding effect when you can use software with security, with AI to really drive transactions. Really, this infrastructure combined with the execution infrastructure and the data, this is a competitive advantage in what we can do for our customers. What we can do is really a game changer, and AI helps enable this to be really a multiplier customers. If you think about why this infrastructure's in place. if you think about why this infrastructure's in place It's really all the data gravity. it's really all the data gravity What it is, if you look at the blue on this one, whether you have dental plans or health insurance or 401(k)s, local taxes, wages, Social Security numbers, that's why it's really legislated like it is. what it is if you look at the blue on this one whether you have dental plans or health insurance or 401(k)s local taxes wages social security numbers that's why it's really legislated like it is That data gravity is ultimately a compounding effect when you can use software with security, with AI to really drive transactions. that data gravity is ultimately a compounding effect when you can use software with security with ai to really drive transactions Really, this infrastructure combined with the execution infrastructure and the data, this is a competitive advantage in what we can do for our customers. really this infrastructure combined with the execution infrastructure and the data this is a competitive advantage in what we can do for our customers What we can do is really a game changer, and AI helps enable this to be really a multiplier customers. what we can do is really a game changer and ai helps enable this to be really a multiplier customers

Speaker 4: Absolutely. Absolutely. absolutely

Speaker 2: If I go to the next slide. I'm sorry. On the operating leverage, I'm gonna let Yasmine talk about this, because really the effect of this with the data, the legislation, et cetera, now let's show and let's talk about ways that AI embedded in our software can really help us. If I go to the n ext slide. if i go to the n ext slide I'm sorry. i'm sorry On the operating leverage, I'm gonna let Yasmine talk about this, because really the effect of this with the data, the legislation, et cetera, now let's show and let's talk about ways that AI embedded in our software can really help us. on the operating leverage i'm gonna let yasmine talk about this because really the effect of this with the data the legislation et cetera now let's show and let's talk about ways that ai embedded in our software can really help us

Speaker 4: Yeah, absolutely, Pat. Thank you. I think if you think Luna becomes the cost reduction engine, it is one. It's that payroll query deflection. We saw it also, guys, in the demo. Fewer support tickets per cycle, guided compliance question and answers reduces the processor time. Where today a customer support representative have to answer those questions. The entry of a payroll, keying it in, that's taking it from minutes and probably 20-30 minutes effort into a two-minute and less. The automated amendment suggestion, they cut manual review. Onboarding acceleration, whether you're onboarding customers via conversational workflow that we have in our client onboarding module with Luna. Every payroll query that Luna resolve is a support ticket that doesn't need a human agent to handle it. Same revenue, lower delivery cost. In the near term, Luna becomes that revenue retention tool. Yeah, absolutely, Pat. yeah absolutely pat Thank you. thank you I think if you think Luna becomes the cost reduction engine, it is one. i think if you think luna becomes the cost reduction engine it is one It's that payroll query deflection. it's that payroll query deflection We saw it also, guys, in the demo. we saw it also guys in the demo Fewer support tickets per cycle, guided compliance question and answers reduces the processor time. fewer support tickets per cycle guided compliance question and answers reduces the processor time Where today a customer support representative have to answer those questions. where today a customer support representative have to answer those questions The entry of a payroll, keying it in, that's taking it from minutes and probably 20- 30 minutes effort into a two-minute and less. the entry of a payroll keying it in that's taking it from minutes and probably 20- 30 minutes effort into a two-minute and less The automated amendment suggestion, they cut manual review. the automated amendment suggestion they cut manual review Onboarding acceleration, whether you're onboarding customers via conversational workflow that we have in our client onboarding module with Luna. onboarding acceleration whether you're onboarding customers via conversational workflow that we have in our client onboarding module with luna Every payroll query that Luna resolve is a support ticket that doesn't need a human agent to handle it. every payroll query that luna resolve is a support ticket that doesn't need a human agent to handle it Same revenue, lower delivery cost. same revenue lower delivery cost In the near term, Luna becomes that revenue retention tool. in the near term luna becomes that revenue retention tool It's that proactive compliance alert that increases the stickiness. You saw it with the EIN and the rate, where a user may actually enter incorrect data, and Luna will add that prevention. It alerts the user of a possibility of an error. That creates stickiness. That AI-powered anomaly detection before a payroll run reduces errors that, in most cases, most of the time churn happens because of errors. Luna itself becomes that switching cost. A client who switches platform is no longer just losing the software, they lose the AI that already learned their business and their payroll. In the long term, Luna is that competitive differentiator, AI that only works because of Asure's data depth. We compete on AI intelligence, not just the features. The platform data moat compounds with every single payroll run. AI capabilities justify that premier tier pricing. It's that proactive compliance alert that increases the stickiness. it's that proactive compliance alert that increases the stickiness You saw it with the EIN and the rate, where a user may actually enter incorrect data, and Luna will add that prevention. you saw it with the ein and the rate where a user may actually enter incorrect data and luna will add that prevention It alerts the user of a possibility of an error. it alerts the user of a possibility of an error That creates stickiness. that creates stickiness That AI-powered anomaly detection before a payroll run reduces errors that, in most cases, most of the time churn happens because of errors. that ai-powered anomaly detection before a payroll run reduces errors that in most cases most of the time churn happens because of errors Luna itself becomes that switching cost. luna itself becomes that switching cost A client who switches platform is no longer just losing the software, they lose the AI that already learned their business and their payroll. a client who switches platform is no longer just losing the software they lose the ai that already learned their business and their payroll In the long term, Luna is that competitive differentiator, AI that only works because of Asure's data depth. in the long term luna is that competitive differentiator ai that only works because of asure's data depth We compete on AI intelligence, not just the features. we compete on ai intelligence not just the features The platform data moat compounds with every single payroll run. the platform data moat compounds with every single payroll run AI capabilities justify that premier tier pricing. ai capabilities justify that premier tier pricing Luna, not a feature, it's the mechanism by which our margin profile improve over time without proportionally cost grows. Pat? Luna, not a feature, it's the mechanism by which our margin profile improve over time without proportionally cost grows. luna not a feature it's the mechanism by which our margin profile improve over time without proportionally cost grows Pat? pat

Speaker 2: Yeah. If you think about it, the market expansion, given that it's not only tools, it's not only enablement, it's not only workflow, it's people, our market expands, the more people we can bring awareness to or bring AI to awareness to our company and our AI-generated marketing, et cetera, can help us. It's voice activated in addition to software, so that multimedia approach is gonna bring more adoption and more asks into our environment. From a revenue retention and sentiment analysis, we get so much learning that Yasmine says compounds, and what we're finding is we can get ahead of issues before they become issues. Ultimately, that's a competitive separator for us, and it's really, really is a game changer for the model. Next slide. AI embedded across software. I talked about tools, enablement, automation, and cost out, it. Yeah. yeah If you think about it, the market expansion, given that it's not only tools, it's not only enablement, it's not only workflow, it's people, our market expands, the more people we can bring awareness to or bring AI to awareness to our company and our AI-generated marketing, et cetera, can help us. if you think about it the market expansion given that it's not only tools it's not only enablement it's not only workflow it's people our market expands the more people we can bring awareness to or bring ai to awareness to our company and our ai-generated marketing et cetera can help us It's voice activated in addition to software, so that multimedia approach is gonna bring more adoption and more asks into our environment. it's voice activated in addition to software so that multimedia approach is gonna bring more adoption and more asks into our environment From a revenue retention and sentiment analysis, we get so much learning that Yasmine says compounds, and what we're finding is we can get ahead of issues before they become issues. from a revenue retention and sentiment analysis we get so much learning that yasmine says compounds and what we're finding is we can get ahead of issues before they become issues Ultimately, that's a competitive separator for us, and it's really, really is a game changer for the model. ultimately that's a competitive separator for us and it's really really is a game changer for the model Next slide. next slide AI embedded across software. ai embedded across software I talked about tools, enablement, automation, and cost out, it. i talked about tools enablement automation and cost out it at the client level. Remember, end-to-end process is not only at the four walls of Asure, but it's at the customer wall all the way and back. When you think about the people and you think about tools, you might need less L&D, you might need less HR. You can really provide and use Asure Central and our software, or you could say, "You know what? I'd rather have you use AI Asure. You get our back office, and we can grow our business." That's a much different message. It's a bigger message ultimately by embedding both. Then I know, Yas, you had a couple of examples here on product and revenue and operational efficiency. at the client level. at the client level Remember, end-to-end process is not only at the four walls of Asure, but it's at the customer wall all the way and back. remember end-to-end process is not only at the four walls of asure but it's at the customer wall all the way and back When you think about the people and you think about tools, you might need less L&D, you might need less HR. when you think about the people and you think about tools you might need less l&d you might need less hr You can really provide and use Asure Central and our software, or you could say, "You know what? you can really provide and use asure central and our software or you could say "you know what I'd rather have you use AI Asure. i'd rather have you use ai asure You get our back office, and we can grow our business." That's a much different message. you get our back office and we can grow our business." that's a much different message It's a bigger message ultimately by embedding both. it's a bigger message ultimately by embedding both Then I know, Yas, you had a couple of examples here on product and revenue and operational efficiency. then i know yas you had a couple of examples here on product and revenue and operational efficiency

Speaker 4: Absolutely, Pat. On the, for me, more on the R&D and the product itself, right? Today, approximately 70% of any new code is generated with AI tool as a co-assistant, as a copilot. Our UX prototyping, where you used to have to spend probably days coming up with a prototype just to share the idea of the vision of a solution, now it's done in minutes. Where we are not only able to show the prototype, we're allowing them to walk through the functionality before we write the line of code, get in alignment. Legacy code translated and modernized by AI. We're only shipping faster with the same team. We are running faster through our roadmap because of the use of AI. I think on the revenue itself, productivity, right, Pat? If you wanna take on what our team is doing today as well. Absolutely, Pat. absolutely pat On the, for me, more on the R&D and the product itself, right? on the for me more on the r&d and the product itself right Today, approximately 70% of any new code is generated with AI tool as a co-assistant, as a copilot. today approximately 70% of any new code is generated with ai tool as a co-assistant as a copilot Our UX prototyping, where you used to have to spend probably days coming up with a prototype just to share the idea of the vision of a solution, now it's done in minutes. our ux prototyping where you used to have to spend probably days coming up with a prototype just to share the idea of the vision of a solution now it's done in minutes Where we are not only able to show the prototype, we're allowing them to walk through the functionality before we write the line of code, get in alignment. where we are not only able to show the prototype we're allowing them to walk through the functionality before we write the line of code get in alignment Legacy code translated and modernized by AI. legacy code translated and modernized by ai We're only shipping faster with the same team. we're only shipping faster with the same team We are running faster through our roadmap because of the use of AI. we are running faster through our roadmap because of the use of ai I think on t he revenue itself, productivity, right, Pat? i think on t he revenue itself productivity right pat If you wanna take on what our team is doing today as well. if you wanna take on what our team is doing today as well

Speaker 2: Yeah. Just in the interest of time, I'll let you read or let the investors read, but really some nice changes that we've highlighted on the earnings call. On the next slide. When you look at kinda some of those operating leverage and AI adoption, what it really does for us and Yasmine, I think you talked about the three items initially that you wanted to bring home. Maybe, Yas, if you could do that, and then I'll wrap it up for questions. Yeah. yeah Just in the interest of time, I'll let you read or let the investors read, but really some nice changes that we've highlighted on the earnings call. just in the interest of time i'll let you read or let the investors read but really some nice changes that we've highlighted on the earnings call On the next slide. on the next slide When you look at kinda some of those operating leverage and AI adoption, what it really does for us and Yasmine, I think you talked about the three items initially that you wanted to bring home. when you look at kinda some of those operating leverage and ai adoption what it really does for us and yasmine i think you talked about the three items initially that you wanted to bring home Maybe, Yas, if you could do that, and then I'll wrap it up for questions. maybe yas if you could do that and then i'll wrap it up for questions

Speaker 4: Yeah. Sure, Pat. I think the most important thing that we wanted to, those three items, AI affects your business model differently. It does. Not all software are equally exposed, absolutely, is your second, whether it's a labor hour or it's an execution platform. The market has been really pricing AI risk broadly across multiple software. So what matters, the execution layer is what is important, and Asure is in there. We are not hoping. Yeah. yeah Sure, Pat. sure pat I think the most important thing that we wanted to, those three items, AI affects your business model differently. i think the most important thing that we wanted to those three items ai affects your business model differently It does. it does Not all software are equally exposed, absolutely, is your second, whether it's a labor hour or it's an execution platform. not all software are equally exposed absolutely is your second whether it's a labor hour or it's an execution platform The market has been really pricing AI risk broadly across multiple software. the market has been really pricing ai risk broadly across multiple software So what matters, the execution layer is what is important, and Asure is in there. so what matters the execution layer is what is important and asure is in there We are not hoping. we are not hoping

Speaker 2: When we look at When we look at when we look at

Speaker 4: Sorry. Go ahead, Pat. Sorry. sorry Go ahead, Pat. go ahead pat

Speaker 2: I'm sorry, Yas. There's a little bit of a delay, so I apologize. I'm sorry, Yas. i'm sorry yas There's a little bit of a delay, so I apologize. there's a little bit of a delay so i apologize

Speaker 4: No. No. no

Speaker 2: Go ahead. Go ahead. go ahead

Speaker 4: No, I was just gonna talk a little bit more about the execution platform, but in the essence of time, I'll let you do it. I'll let you run it this time. No, I was just g onna talk a little bit more about the execution platform, but in the essence of time, I'll let you do it. no i was just g onna talk a little bit more about the execution platform but in the essence of time i'll let you do it I'll let you run it this time. i'll let you run it this time

Speaker 2: Okay. With that, all across Asure, we create structural operating leverage, and we talked about that. What that means for you as an investor over time is if you look to the next slide, what you have is. The next slide, Patrick, is over time here, what we've done a nice job is building a business, and then where we build the business, we're at $200 million, roughly 30% margin. We see opportunities to accelerate growth. We see opportunities to have fixed cost absorption. We also see opportunities we can grow revenue faster than cost with really using AI embedded with software in the sense of where we can look at tools, we can look at enablement, we look at workflow. Ultimately, we look at people and where we can grow faster the revenue. Okay. okay With that, all across Asure, we create structural operating leverage, and we talked about that. Wh at that means for you as an investor over time is if you look to the next slide, what you have is. with that all across asure we create structural operating leverage and we talked about that. wh at that means for you as an investor over time is if you look to the next slide what you have is The next slide, Patrick, is over time here, what we've done a nice job is building a business, and then where we build the business, we're at $200 million, roughly 30% margin. the next slide patrick is over time here what we've done a nice job is building a business and then where we build the business we're at $200 million roughly 30% margin We see opportunities to accelerate growth. we see opportunities to accelerate growth We see opportunities to have fixed cost absorption. we see opportunities to have fixed cost absorption We also see opportunities we can grow revenue faster than cost with really using AI embedded with software in the sense of where we can look at tools, we can look at enablement, we look at workflow. we also see opportunities we can grow revenue faster than cost with really using ai embedded with software in the sense of where we can look at tools we can look at enablement we look at workflow Ultimately, we look at people and where we can grow faster the revenue. ultimately we look at people and where we can grow faster the revenue By looking at the end-to-end process, not only in our four walls, but also within the customer, that opens up huge scale advantages, not only in payroll, but if you think about our business, whether it's insurance, 401(k), money movement, tax filing, all the agencies, now you have an infrastructure that can be accelerated with AI as opposed to at risk. If we go to the next slide. We talked about execution infrastructure. Yasmine talked about it, why it's a strategic advantage. We feel it strongly that it is. We see where we're positioned. We wanna make sure as a discerning investor, you look at the opportunity of Asure software, and you look at our business in a different way or in a way that really is an acceleration here. We're excited to offer that point of view today. By looking at the end-to-end process, not only in our four walls, but also within the customer, that opens up huge scale advantages, not only in payroll, but if you think about our business, whether it's insurance, 401(k), money movement, tax filing, all the agencies, now you have an infrastructure that can be accelerated with AI as opposed to at risk. by looking at the end-to-end process not only in our four walls but also within the customer that opens up huge scale advantages not only in payroll but if you think about our business whether it's insurance 401(k) money movement tax filing all the agencies now you have an infrastructure that can be accelerated with ai as opposed to at risk If we go to the next slide. if we go to the next slide We talked about execution infrastructure. we talked about execution infrastructure Yasmine talked about it, why it's a strategic advantage. yasmine talked about it why it's a strategic advantage We feel it strongly that it is. we feel it strongly that it is We see where we're positioned. we see where we're positioned We wanna make sure as a discerning investor, you look at the opportunity of Asure software, and you look at our business in a different way or in a way that really is an acceleration here. we wanna make sure as a discerning investor you look at the opportunity of asure software and you look at our business in a different way or in a way that really is an acceleration here We're excited to offer that point of view today. we're excited to offer that point of view today With that, Patrick, if we have questions, Yasmine and I would be happy to answer them. With that, Patrick, if we have questions, Yasmine and I would be happy to answer them. with that patrick if we have questions yasmine and i would be happy to answer them

Speaker 3: Okay. Great, Pat. Just getting some questions here on the web, and we'll check for any people that are submitting questions online. First up, just one question is: What would it actually take for an AI company to become an IRS bulk filer and start executing payroll tax filings directly? Are the barriers primarily regulatory, operational or technical? Okay. okay Great, Pat. great pat Just getting some questions here on the web, and we'll check for any people that are submitting questions online. just getting some questions here on the web and we'll check for any people that are submitting questions online First up, just one question is: What would it actually take for an AI company to become an IRS bulk filer and start executing payroll tax filings directly? first up just one question is what would it actually take for an ai company to become an irs bulk filer and start executing payroll tax filings directly Are the barriers primarily regulatory, operational or technical? are the barriers primarily regulatory operational or technical

Speaker 2: All three. All three. all three

Speaker 4: I was gonna say. I was gonna say. i was gonna say

Speaker 2: Yasmine, I don't know if you wanna add any color there. Yasmine, I don't know if you wanna add any color there. yasmine i don't know if you wanna add any color there

Speaker 4: No, it's absolutely, it's what you said. It's all of the above. It requires all of it, right? It's you gotta become a reporting agent, that is, the forms that you have to fill in, and that is, of course, the fingerprinting. There is a lot that needs to be in place. Plus, what comes with it is really the knowledge and the authority that you have gained throughout years of experience with the IRS. It's not something that any company can just turn on and become an IRS bulk filer. No, it's absolutely, it's what you said. no it's absolutely it's what you said It's all of the above. it's all of the above It requires all of it, right? it requires all of it right It's you gotta become a reporting agent, that is, the forms that you have to fill in, and that is, of course, the fingerprinting. it's you gotta become a reporting agent that is the forms that you have to fill in and that is of course the fingerprinting There is a lot that needs to be in place. there is a lot that needs to be in place Plus, what comes with it is really the knowledge and the authority that you have gained throughout years of experience with the IRS. plus what comes with it is really the knowledge and the authority that you have gained throughout years of experience with the irs It's not something that any company can just turn on and become an IRS bulk filer. it's not something that any company can just turn on and become an irs bulk filer

Speaker 2: Patrick, I always go to the example, I go to the mailbox every day, and I have 100,000 companies that we process payroll and taxes for, and I'm always disappointed because I never get a letter from the IRS saying, "Hey, Pat, great job on those taxes." If there's a problem, I certainly get a letter, and we work through with our clients to make sure those get resolved. It's a negative satisfier business where perfection is expected, but if you have risk and you have a problem, it takes a little bit of know-how to work through in getting those problems solved, and that's really the key. We think we can use AI to our advantage, and we don't think it'll replace it anytime soon. Next question. Patrick, I always go to the example, I go to the mailbox every day, and I have 100,000 companies that we process payroll and taxes for, and I'm always disappointed because I never get a letter from the IRS saying, "Hey, Pat, great job on those taxes." If there's a problem, I certainly get a letter, and we work through with our clients to make sure those get resolved. patrick i always go to the example i go to the mailbox every day and i have 100,000 companies that we process payroll and taxes for and i'm always disappointed because i never get a letter from the irs saying "hey pat great job on those taxes." if there's a problem i certainly get a letter and we work through with our clients to make sure those get resolved It's a negative satisfier business where perfection is expected, but if you have risk and you have a problem, it takes a little bit of know-how to work through in getting those problems solved, and that's really the key. it's a negative satisfier business where perfection is expected but if you have risk and you have a problem it takes a little bit of know-how to work through in getting those problems solved and that's really the key We think we can use AI to our advantage, and we don't think it'll replace it anytime soon. we think we can use ai to our advantage and we don't think it'll replace it anytime soon Next question. next question

Speaker 3: Let's see here. Where are you already seeing tangible reductions in cost to serve from AI? Support operations, compliance, workflows, onboarding or somewhere else? Let's see here. let's see here Where are you already seeing tangible reductions in cost to serve from AI? where are you already seeing tangible reductions in cost to serve from ai Support operations, compliance, workflows, onboarding or somewhere else? support operations compliance workflows onboarding or somewhere else

Speaker 2: Yeah. Honestly, all of the above. I think I thought Yasmine and Luna did a great job, and Sarah on the demo to point out the payroll, the tax filing. If you think about the workflow within your own company, how quickly we went through that demonstration and how streamlined those questions got answered and the process got run. If you think about where we are as a growing business, I think you're gonna see us grow more revenue faster than we're adding people, and that's by layering in those opportunities, and then we're expanding our marketplace because we're taking on more. Really excited about that opportunity, but those are the items that you've seen. Yeah. yeah Honestly, all of the above. honestly all of the above I think I thought Yasmine and Luna did a great job, and Sarah on the demo to point out the payroll, the tax filing. i think i thought yasmine and luna did a great job and sarah on the demo to point out the payroll the tax filing If you think about the workflow within your own company, how quickly we went through that demonstration and how streamlined those questions got answered and the process got run. if you think about the workflow within your own company how quickly we went through that demonstration and how streamlined those questions got answered and the process got run If you think about where we are as a growing business, I think you're gonna see us grow more revenue faster than we're adding people, and that's by layering in those opportunities, and then we're expanding our marketplace because we're taking on more. if you think about where we are as a growing business i think you're gonna see us grow more revenue faster than we're adding people and that's by layering in those opportunities and then we're expanding our marketplace because we're taking on more Really excited about that opportunity, but those are the items that you've seen. really excited about that opportunity but those are the items that you've seen

Speaker 3: Okay. Operator, can we just check to see if we have any questions from folks that may have dialed in on the phone here? Okay. okay Operator, can we just check to see if we have any questions from folks that may have dialed in on the phone here? operator can we just check to see if we have any questions from folks that may have dialed in on the phone here

Speaker 1: Yes. I don't see any questions. Yes. yes I don't see any questions. i don't see any questions

Speaker 3: Okay. We'll just continue with ones that are coming in over the web here. Next question is, "The Luna value proposition is very clear, but can you please talk about how are you going about monetizing the product and driving adoption? Okay. okay We'll just continue with ones that are coming in over the web here. we'll just continue with ones that are coming in over the web here Next question is, "The Luna value proposition is very clear, but can you please talk about how are you going about monetizing the product and driving adoption? next question is "the luna value proposition is very clear but can you please talk about how are you going about monetizing the product and driving adoption

Speaker 2: Yas, do you wanna talk about that or you want me to? Yas, do you wanna talk about that or you want me to? yas do you wanna talk about that or you want me to

Speaker 4: You could go ahead, and I'll add to it, Pat. You could go ahead, and I'll add to it, Pat. you could go ahead and i'll add to it pat

Speaker 2: Yeah. No, I think what first of all, monetizing adoption, we could do a lot more. If you think about all the data that we have, what's interesting is we bring Asure Essential together. We're talking about attach rates. We're talking about revenue per unit. Because now when we sit on this kind of data and we have the tools, the workflow, ultimately now, when somebody has 50 employees and they need work site reporting, we can automatically enroll that client. All they have to do is check yes in work site reporting. That comes with a fee. It also is regulatory. 20 employees, COBRA starts. It comes with a fee, it's regulatory, and we can ask them proactively if they want us to handle it or themselves. Yeah. yeah No, I think what first of all, monetizing adoption, we could do a lot more. no i think what first of all monetizing adoption we could do a lot more If you think about all the data that we have, what's interesting is we bring Asure Essential together. if you think about all the data that we have what's interesting is we bring asure essential together We're talking about attach rates. we're talking about attach rates We're talking about revenue per unit. we're talking about revenue per unit Because now when we sit on this kind of data and we have the tools, the workflow, ultimately now, when somebody has 50 employees and they need work site reporting, we can automatically enroll that client. because now when we sit on this kind of data and we have the tools the workflow ultimately now when somebody has 50 employees and they need work site reporting we can automatically enroll that client All they have to do is check yes in work site reporting. all they have to do is check yes in work site reporting That comes with a fee. that comes with a fee It also is regulatory. 20 employees, COBRA starts. it also is regulatory 20 employees cobra starts It comes with a fee, it's regulatory, and we can ask them proactively if they want us to handle it or themselves. it comes with a fee it's regulatory and we can ask them proactively if they want us to handle it or themselves If you think about the bigger kind of question as well, we can go to a small business and say, "Listen, we have all the products and services that you can use with software, but if you want Asure to help you and do it all for you or with you, we can do that." That opens up a big marketplace. Then, I don't know, lately, if you've seen all the work we've done with tax filing, money movement, treasury management. We have an ability to continue to grow to help customers. AsurePay is a prime example where we now have earned wage access in addition to a default, kind of opportunity to get people paid right away and get a little bit interest on their bank account. Number of different ways, we're gonna continue to talk through all those items on the quarterly call. If you think about the bigger kind of question as well, we can go to a small business and say, "Listen, we have all the products and services that you can use with software, but if you want Asure to help you and do it all for you or with you, we can do that." That opens up a big marketplace. if you think about the bigger kind of question as well we can go to a small business and say "listen we have all the products and services that you can use with software but if you want asure to help you and do it all for you or with you we can do that." that opens up a big marketplace Then, I don't know, lately, if you've seen all the work we've done with tax filing, money movement, treasury management. then i don't know lately if you've seen all the work we've done with tax filing money movement treasury management We have an ability to continue to grow to help customers. we have an ability to continue to grow to help customers AsurePay is a prime example where we now have earned wage access in addition to a default, kind of opportunity to get people paid right away and get a little bit interest on their bank account. asurepay is a prime example where we now have earned wage access in addition to a default kind of opportunity to get people paid right away and get a little bit interest on their bank account Number of different ways, we're gonna continue to talk through all those items on the quarterly call. number of different ways we're gonna continue to talk through all those items on the quarterly call

Speaker 3: Okay, Pat. Looks like we're just about out of time. I don't see any other questions popping in at this second, so I don't know if you wanna take a minute and kind of wrap things up. Okay, Pat. okay pat Looks like we're just about out of time. looks like we're just about out of time I don't see any other questions popping in at this second, so I don't know if you wanna take a minute and kind of wrap things up. i don't see any other questions popping in at this second so i don't know if you wanna take a minute and kind of wrap things up

Speaker 2: Yeah, absolutely. First of all, I wanna thank Yasmine Rodriguez. I tell you, she's a Chief Technology Officer second to none. She's done a great job here building the foundation with AI and Asure. She and I talked about this with our management team probably a little over two years ago and really excited about it. What you're seeing sometimes, the best laid plans happen either overnight or a couple years in the making, and in this case, it was a couple years making. We believe we're at a really good inflection point within the business. We hope you came away and you learned something today or you understand a little bit more about Asure. And we have quarterly calls. We also are available through investor relations. Patrick always makes himself available. Yeah, absolutely. yeah absolutely First of all, I wanna thank Yasmine Rodriguez. first of all i wanna thank yasmine rodriguez I tell you, she's a Chief Technology Officer second to none. i tell you she's a chief technology officer second to none She's done a great job here building the foundation with AI and Asure. she's done a great job here building the foundation with ai and asure She and I talked about this with our management team probably a little over two years ago and really excited about it. she and i talked about this with our management team probably a little over two years ago and really excited about it What you're seeing sometimes , the best laid plans happen either overnight or a couple years in the making, and in this case, it was a couple years making. what you're seeing sometimes the best laid plans happen either overnight or a couple years in the making and in this case it was a couple years making We believe we're at a really good inflection point within the business. we believe we're at a really good inflection point within the business We hope you came away and you learned something today or you understand a little bit more about Asure. we hope you came away and you learned something today or you understand a little bit more about asure And we have quarterly calls. and we have quarterly calls We also are available through investor relations. we also are available through investor relations Patrick always makes himself available. patrick always makes himself available As if you have questions or comments, please reach out to us. We're excited about the opportunity and really wanna thank you for taking and investing some time today. As if you have questions or comments, please reach out to us. as if you have questions or comments please reach out to us We're excited about the opportunity and really wanna thank you for taking and investing some time today. we're excited about the opportunity and really wanna thank you for taking and investing some time today

Speaker 4: Yes, thank you all. Yes, thank you all. yes thank you all

Speaker 3: Thank you all. Operator, I think we can log off now. Thank you. Thank you all. thank you all Operator, I think we can log off now. operator i think we can log off now Thank you. thank you

Speaker 1: Thank you. Thank you. thank you