From Busywork to Business: How AI Is Giving MedTech Reps Their Time Back

So we're going to roll right into our presentation, once again by our good friends at AcuityMD. We've got two great folks, Lee Smith, he's co-founder, head of commercial development at AcuityMD, and Brandon Hall, strategic account executive at AcuityMD. Lee and Brandon, welcome to DeviceTalks Tuesdays.

Thanks, Tom. Happy to be here. Happy to have you both. Lee, I know AcuityMD. As I said, we've been working together for a long time, but let's just assume that there's one or two people out in the audience who don't know exactly what you do. If you could give us a little bit of overview of the company, how are you helping the med tech industry? Yeah, absolutely. Hopefully, those are getting fewer and fewer as we continue to grow. But anyway- That's what we're working on... I'm happy to give an intro.

My name's Lee Smith. Yeah, I'm one of the co-founders at AcuityMD, so I've been here since we started the company about seven years ago. And AcuityMD is a software company. We have an AI platform for the medical device industry, really tailored just for the med tech industry. And really what we do is power kind of the entire go to market, from targeting to managing your pipeline, forecasting, evaluating new markets or M&A activity to get into. AcuityMD does all of that with our data model and our AI platform, which we will get into a bit today. So that's a little bit on us.

All right. Fantastic. I saw a couple of glitches there. Just to make sure we covered it all, and I'm not sure if anyone else did, so maybe it's my internet connection. But again, AcuityMD was founded, which year?

2019. Okay, fantastic. All right. So you folks were founded prior to the pandemic and found a way to plow through and grow during the pandemic. That must've been a real formative time. Well, it was a formative time for everybody, but for you in particular. Yeah. Yeah. Yeah, it certainly was. I think, and hopefully my audio's coming through. Let me know- No, you're great. Yeah. Okay. Yeah. Okay, good. I'm working out of hotel Wi-Fi, so if there are any issues, just let me know. But yeah, no, it was an interesting time to start a company for sure. I think, in hindsight, probably slowed down our commercial traction, but it allowed us to focus a lot with our early customers and go really deep with kind of a smaller base of customers from the start and understand kind of all the nuances of the industry, from small company kind of going through FDA approval- Mm-hmm... to big company, to all of the different specialties and nuances across the specialties that we serve. So I think it was an interesting time and kind of grown from there in 2019 where we started to, we just crossed 500 customers that we serve across the med tech industry today.

So that's kind of what our business looks like. That's great. And as I mentioned, we've been working with you for a long time. And you folks really kind of helped add a pillar to our DeviceTalks structure. We traditionally had focused on engineering, manufacturing, regulatory reimbursement. Commercialization, obviously there was a lot going on there, but I feel like the technology for commercialization really took off during the pandemic. Really, I guess, gave folks time and necessity to find different ways to reach hospitals, to reach physicians, to get the word out about their medical devices. I know you're doing a lot of work on surveying med tech reps on collecting data. You've done some surveys recently. Do you have some data that you can share, some highlights of your findings? Yeah, absolutely.

And so I'll jump into the slides here. Yeah, we recently did a survey of 150 medical device reps across the industry, and we asked a number of questions that I think kind of the starting point, we'll get into a few of these, is that 84% of medical device reps are losing between three and 10 hours every week on so-called non-productive tasks. And so that could be data entry. That could be digging into their CRM. That could be replanning their schedule if a case cancels. And so I think there's a number of reasons why this is the case. I think the medical device sales rep job is really hard. It's a lot harder, I think, or it encompasses a lot more than sellers in other industries because you have to provide service, you have to provide support, you have to obviously go sell and grow your business, you have to manage inventory, you have to go do product demos. And so there's just a lot that goes into the job. And you can get bogged down by other tasks. And so I think kind of the big question is, hey, is AI a really good opportunity to save these reps some time and help make them more efficient in their day-to-day?

So those are some of the initial findings that I think we came across. And Brandon, let's bring you into the conversation. Someone who's spent years as a med tech rep. Does this resonate with you?

Yeah, absolutely. Just to echo what Lee said, I probably spend at least an hour a day, so probably five-plus hours a week, just on those mundane tasks like CRM activities, call planning, honing in on specific sales messages.

Just determining what physicians to see on what days. Were they in the lab versus the clinic, and kind of stack ranking them and just overall prioritizing my time. And then on top of that, trying to figure out market share, which physicians were growing and declining. And I covered a large geography and I had a lot of windshield time. So, I can definitely speak from experience that maximizing time was essential in that role. Yeah. Thanks for sharing that, Brandon. I think it's great to hear from the sales rep's perspective and certainly validates, I think, a lot of what we've found across the industry and with this survey. And want to kind of transition into AI and some of the more specific findings that came through during this survey. And it's an interesting time because some medical device both companies and reps are clearly starting to deploy AI in a few different ways. And so we ask kind of a few questions here, both do you use AI or what is the frequency of your use of AI-And then did you meet or exceed quota? And trying to get some signal if there's any correlation there. And kind of a couple interesting findings off the bat here is that, there was heavier use of AI or stronger correlation of use of AI with those that did meet or exceed their quota.

So, there's some signal that some of the higher performers or more effective sellers are starting to deploy AI more regularly. And then I think the other interesting finding here is that, there's still a very large chunk of no current AI use.

So you have, I think, some positive signs there that it is working, it is saving time, maybe, for a few more, I'd say tactical or straightforward use cases, which we can get into, but you still have some skeptics or some non-users as well. And so we'll certainly want to dig into that to understand what needs to change and what they need to see or what their organizations need to see to start to adopt it or have it be effective for them.

Do you have a sense as to why folks aren't using it? It's a divisive question, even in journalism and reporting. I'm pro-AI. I think you got to use every tool at your disposal. Some reporters prefer not to, obviously not for the writing, but for the research. Why are reps not using AI? What's the reason they give? Yeah. It's a good question. I think, from what we've seen so far, there's kind of a few reasons that it boils down to. I think a lot of it, is medical device companies often take a fairly conservative approach here, and so there's some privacy and security concerns. And so I think in some instances you have reps that are actually prohibited from using it or have been kind of directed not to from their organization. So that's definitely one category that we need to help them work around. And then I think you have another category that either they're slow to adopt or maybe a little bit, kind of on the tech laggard side, or they haven't seen the value, right? If the AI is not delivering them what they need, if it's not solving a problem, if it's not saving them time, if there's not a clear-cut use case or a clear-cut prompt that they can use to deploy into an AI system that's going to help save time in their day or help uncover something that they didn't know, then why should they use it?

And so I think, those are maybe the two buckets that we see most frequently. And what about the ones that are using AI? What are they using it for today? Yeah. I think, you definitely see some kind of basic functionality like, "Write me an email," or, "Map my route from hospital A to hospital B or along this route here." And so I think, we've seen a lot, I'd say the majority of what we've seen is on those types of use cases. That's maybe automating some basic workflows that are happening throughout the day, but maybe not yet tying together three or four different systems and actually having agents take over some of the work. And, I think, where we see maybe some future opportunity is not quite yet where the industry is, in large part due to the tools that exist and how new it is to the industry and some of the reasons I mentioned previously.

Interesting. All right. Brendan, I know there's no typical life or day in the life of the sales reps, but I'm a guy who spends most too much time at my desk. I'm guessing the sales rep life is a lot more mobile than mine. I'm just curious as to what is a typical day like, do you think, for a sales rep? Again, acknowledging that there's no such thing as a typical sales rep. Yeah. So in my role, when you are lucky, you would get notified of cases ahead of time, if you're lucky. Mm-hmm. So the first thing is you wake up in the morning and you kind of plan your day around your cases. So you cover cases, again, if you're lucky, you know you have a 7:00 a.m. case, and then maybe you have another one to follow.

For a lot of instances and situations, you don't know what you have going on that day, so you have to kind of fly by the seat of your pants and be able to pivot on the drop of a dime. So the thing where this is so impactful is those days to where, okay, you have a case in the morning and you know you have some free time, what are you going to do to maximize your revenue-generating activities? Mm-hmm. You have to be very structured with your day, and you have to be ready to essentially pivot, but then rock and roll when you get an hour or two to go see a physician, know who to see, who to call on, what message to deliver, know who's maybe declining in volume or where the opportunities are. And so that's always top of mind, I think, for reps these days is, first and foremost, it's serving the patients and the physicians with procedures, but then it's all the other activities on top of that you're responsible for to hit a number.

All right. That's really great. So do we have our next slide? Yes, we do. And, yeah. I think it's probably a good transition here because, I'll talk a little bit about AcuityAI. We just launched AcuityAI for any customers. You may have been part of our beta program. And if you haven't, it's fairly recent. We launched it about a month and a half ago, and really it's AcuityMD's first AI product. And so what we've done is built an AI agent directly into our platform, and it really allows you to automate a lot of the work that folks have previously done in AcuityMD, but previously using dashboards and now using an AI tool. And so essentially what we've done is take all of our data, all of our industry data, all-All of our claims data, all the modeling we do there, all the first-party data that we integrate in for customers. And so it reads all of the context that's necessary to generating an output, whether that's an output for targeting or growing your pipeline, or taking a next step, or preparing for a sales call. Takes all of that context, and then when you ask the agent questions, it's able to produce that next step or produce that output that you need.

And so that's kind of how it looks today, primarily for the end user, sales rep, sales manager. And as we continue staggering our launches, and building onto AcuityAI, we'll have a commercial leader agent, which will answer questions for sales leaders. We're about to launch our market research agent as well, which will help identify indication expansion or acquisition opportunities or product development opportunities. And so you can kind of imagine where this is headed with other commercial personas and even beyond that for a medical device organization. So that's a little bit about AcuityAI.

And I'll talk a bit more here about kind of how critical it is to ensure accuracy and differentiate, right? Because I think one of the common questions that we get in this space is, well, can I just use a typical LLM, or can I use Claude, or can I use ChatGPT?

Why isn't that sufficient? And it's a good question. And it may be sufficient for some of those basic tasks, right? You plug into ChatGPT, have it write you an email or something to that effect, and you're going to get a pretty good output. But when you're looking for information that goes a layer deeper, right, whether you're understanding who you're going to call on, why you're going to call that person, how you're going to call on them, what are the dynamics across my market, obviously, that requires a lot more context. And so kind of all the information that's beyond the surface is really how you can think about AcuityAI being much differentiated from a generic LLM. And so I think the number one thing to point to is the data ontology, right? We have a very differentiated, industry-leading set of claims data that we've invested in, built, modeled, and ultimately deliver a very strong representation of what's happening on the ground for a medical device company. So that's kind of the starting point, and then you layer in all the additional data on referrals, on publications, on industry relationships, the first-party data that we bring in as well. And the system, our model is obviously pulling from a much different set of data and information than what you'd get with a generic model. So that's kind of the biggest thing.

And then, the other things, there's a lot to point to here. I won't read every part of the slide, but the persona as well, right? If you're a sales rep, if you're a marketer, or if you're a president, actually reading that context and understanding, hey, do I need to respect some territory restrictions for this user, or do I need to respect a set of products or a business unit? That's really important as well. And then we talked about security and compliance, and that's really important, too. We know too, especially at a larger organization, they need to know that what they're feeding into the system is not improving the model or kind of breaking down the firewall between other organizations. And so having that confidence is obviously key and something that's very critical to how we're developing our AI products.

That's great. Pause there for a second, Tom. Any other questions you wanted to dig into on that? If not, I can jump into some of the use cases here. No, why don't we just get into the use cases? That'd be great. Excellent. Yeah, absolutely. So, I think this is the other common question that we see as companies start to deploy AI in general, and then specifically AcuityAI. It's like, wow, this is such a powerful tool, and you really need to harness that, right? It can do so much, which is great, and if you're creative and thoughtful and strategic, you can push the boundaries, which is awesome. But, for the whole organization, I think it's also really important to provide some guidance and some specifics on, hey, how should we be using this, or what are the highest value use cases that I can start with to learn if I may be newer to the technology? And so, these are kind of a few of the categories that I think we've seen as really strong starting points if you're starting to pick up AI or starting to deploy AcuityAI. And so, number one is kind of the core targeting use case.

And I'll just contrast this, right? If you were previously using any dashboard or dataset to target and you had a defined ICP, and maybe it's physicians doing a certain volume at a certain IDN with a certain trend, right? Layering in all those filters on a dashboard or in Excel, it takes some time. It's pretty cumbersome. But I think one of the best use cases for AcuityAI is that you can layer in a number of different variables or data points in one prompt, and it's going to spit out a much more focused, narrow ICP. So if you have a corner of the market that you know you're focused on or you know you have the right to win, it's a lot easier to get to that answer and democratize that across the organization. So, it's always a good starting point to say, okay, where can we layer in some other parts of our ICP and get very focused on where we think we have the best opportunity to go hunt? So that's, to me, one of the best targeting use cases. Then obviously making that specific to your organization is critical. Again, I won't read through every one, but another one, growing revenue inside your existing book, right?

And that could be leveraging your install base, right? And looking across your install base, okay, it's end of quarter. Where do I have low-hanging fruit that might be a shorter sales cycle to close? Where can I go upsell an account or maybe bring on a new physician at an account where I already have inventory in place or capital in place? Where can we expand our referral targeting? Can we identify where there might be referrals to go influence upstream? So that's another great use case as well. And then, for a new product launch too, starting to get focused on defining that ICP and going after early adopters, looking where you're going to place those first sets. That can be a big activity with a lot of analysis and AcuityAI is a great place to start for that.

So you can see a few others here on the screen, and then we're going to get into some, but again, good starting point for use cases for AcuityAI. That's great. And then we're going to be able to show folks what it looks like. Yes, we will. And I will hop us over to the demo right now.

Let's try it. So knowing what it's like to be a busy rep, I'm going to walk through a few specific use cases that were relevant to my old territory that will probably resonate with a lot of reps out there.

I'm going to show the difference between generic AI tools and AcuityAI, so you can see firsthand what purpose-built AI looks like in action. So here's a real-world scenario. Let's just say we launched a new therapy or a new product, and I wanted to get around to the different referring physicians in my territory. So I used to sell pacemakers, and let's say it was a new pacemaker feature. And I have a day where I don't have many cases or maybe just one I need to cover in the morning, and I have time to get around to these different referring groups.

Now, I know there are a lot of referring physicians in my geography because I have a pretty large geography that spans across two territories, but not only do I struggle to find time to get there, but it's hard to prioritize which ones to get to.

But I know they're out there, and I don't know who's referring what to whom, though. So my first prompt is going to be about targeting and finding top referring cardiologists in my territory. And so right off the bat, I'm going to use the voice feature, the voice-to-dictate feature, because we're all busy reps. We're in our cars a lot, we're traveling, and it's nice to be able to voice dictate into our AI tools, and we can certainly do that with AcuityAI.

So here's my first prompt. Find me the top five referring cardiologists for Dr. Malecki, spelled M-A-L-E-K-I, in New Brunswick, and map me a route to all their offices. All right, so here's the prompt.

Looks accurate. And what's nice about AcuityAI with other AI tools, it's going to tell you its "thought process" or what it's doing. Okay, so found Dr. Malecki in the area, and now it's going to pull the inbound referrals that are filtered to cardiology for her.

So as you can see here, this took what, a minute maybe? Top five referring cardiology groups or physicians to Dr. Malecki. And it also generates a map to the respective offices, which is nice because you can just open this into Google Maps. If you're on your phone with AcuityAI, you can open this up into Google Maps and start your day. Okay, so let's give it another prompt.

Great. Who else are they sending their cardiology referrals to? So again, this is going to be useful to determine which physicians that I need to prioritize in order to generate business from.

So here are the results in a matter of seconds. And as you can see here, it stack ranks all the physicians, and it also gives you some notes at the end of the list to, again, help you target and prioritize which physicians and which volumes that you should be going after.

So let's do another one. What about top cardiology referrers near Dr. Malecki that don't send any volume to her? Where do they send their referrals instead? All right, so make sure the prompt is accurate, which it is, and we'll see what it generates.

So this should come as no surprise, but this is an absolute time-saver in terms of the data and the information that's already embedded into AcuityMD's platform. AcuityAI can go through all that data and pull this together, again, in a matter of seconds.

So here's the list of nearby cardiologists not referring to Dr. Malecki. And this is great information because maybe I want to drive some more referrals to her, or maybe I want to understand just referral patterns in general so then I can go target specific physicians where these referrings are happening.

All right, let's give it another prompt. Okay, great. Now help me with personalized warm intros for these cardiologists discussing how our pacemakers address bradycardia management.

And bradycardia is just slow heart rate. So enter the prompt. And so what's nice about AcuityAI is it will be pretty candid with you, and it says, "I want to help, but I'll be upfront, I don't have any verified product materials on file for your pacemaker portfolio.

What I can do is, I have strong referral and practice data on each of these cardiologists. I can draft personalized intros for each one that are grounded in their specific practice patterns and referral relationships."

So what we could do is I could upload or voice dictate some of the features that I want to talk about, or I can be more specific about my intro email, or I can just keep it general, and then I could personalize it later. And I could also leverage this information, these warm intros, for talking notes if I can get in front of these physicians. But let's just say, what happens all the time is our day gets flipped upside down and we have a day mapped out, and we want to hit four or five different offices, and we can hit one or two. So it's nice to be able to, again, improve your efficiency with AcuityAI, so you can have this information to be able to deliver it to them either in person or via email.

And so it asks for a prompt, and I'll just say, "Go ahead and draft the intros, leaving the specifics for me." So I'll say, "Yes, proceed with drafting. And leave the specifics to me."

So as you can see here, AcuityAI says, "I already have rich referral and practice context from our early analysis, so I can draft these directly. Let me pull summaries for the five cardiologists to round out the personalization." So the summaries for the cardiologists are already embedded into the platform. So within AcuityMD, we have something called peer networks. We have different training connections, where they did their fellowship, where their education was, if they co-authored papers with any other physicians. Generic AI can't do that, and it would take hours upon hours to feed a generic AI all this information on top of the sales data that you might have or on top of the procedure volumes that you may have or you think you may know because, hey, you know what? We're all tenured reps, and we're in our accounts every day, and I was there in the same boat. I know who I need to target, and I know what the procedure volumes actually are. Well, do we really know that? AcuityAI gives you that rich context layer of referral patterns, of procedure volumes, of where the business is happening, where the referrals are going.

And so that's what's incredibly beneficial for somebody like myself or a sales professional, that they can leverage tools like this to increase their sales, to take market share. So I'll scroll down and just show, again, matter of seconds, personalized outreach emails that you can send to physicians or that you can use as notes if you're walking into a physician's office that you've maybe never been to before or you've never met.

All right, so let's give it one final prompt. Clearly, AcuityAI is incredible for warm referrals, rep efficiency, planning your day. But what about uncovering new opportunities or hidden opportunities in conjunction with uncovering procedure volumes and referral patterns?

So let's give it this prompt. "Can you help me find a few more opportunities in the New Brunswick market where the physician is at a small clinic or facility and has an upward trend in pacemaker volume?"

All right. Let's see what it kicks out. All right, so the initial search came back empty, so it tried again, and now it's uncovering opportunities. So here are the results. It uncovered the best matches, and it filtered out the ones that we've already been discussing with Dr. Malecki and the referrals.

So as you can see here, it will actually list you the procedure volumes and show you the trends, the upward trends, and therefore, you know who to target. And it looks like it gave the top three.

So just like your traditional AI models, it's going to continue to prompt you to dig deeper, and that's the beauty of AcuityAI, is the depth to where, again, you're not going to get this level of intelligence and actionable strategy from a generic AI. And so a couple of the themes here, like I mentioned before, are speed and efficiency, quality interactions with physicians, but also uncovering hidden opportunities. AcuityAI embedded in AcuityMD's commercial intelligence platform is an absolute goldmine for commercial teams and field sales reps.

By leveraging a purpose-built tool like this for med tech, you can absolutely improve your sales, increase efficiencies in the field, take market share, and grow your territories like never before.

Awesome. Well, that was a great demo, Brandon. Thank you for walking through that. I think it put a finer point to a lot of what we shared at the beginning of this on how it works and how it's differentiated, and how to think about applying it to your business. And hopefully, folks listening could take inspiration from the example you gave. Obviously, didn't apply to every single specialty, but you could see how it would apply to whatever type of product you sell or whatever specialty or segment you're in the industry. So it was a great overview. Figured I'd just wrap things up here with a few takeaways. And so I think, just to summarize here, we all know that med tech sales reps have a very demanding job, very busy, and they do lose time on a variety of tasks throughout the week.

And those are taking time away from them selling or strategizing or going to engage new accounts or new physicians. So there's great reason to try and put time back in their pockets. And, I think today we've seen early signals of some reps starting to use AI, but more so for email drafting and some more tactical use cases. So certainly an opportunity to improve upon that and responsibility across the industry, I think, to deliver more, which is exactly what we're trying to do with AcuityAI. And I think, maybe one of the reasons, back to point two, is that the generic AI tools really weren't built for med tech. They lack all of that context, that data ontology to really deliver a valuable answer. And so you can't ask ChatGPT or Claude some of the questions that Brandon was just going through and expect to get the right output and have it send you in the right direction.

And so I think there's tons of use cases for med tech, which we just uncovered. I think that's one of the really exciting things. There's a ton of power that we can unleash with all the data behind AcuityAI, and so it's important to balance the power of the solution and the power of all that data with some structure and some specificity on where to start and what use case and which prompt is most valuable for your organization or you individually. And I think, ultimately, what we have already seen a bit of and expect to see more is that, especially the top performing reps are really going to start to adopt this type of solution. And hopefully they're doing a lot less busy work, a lot less manual entry, a lot less analysis, and getting the insights they need to flow right to them to drive their day-to-day.

So hopefully that sums it up. Tom, I don't know if you have any closing comments, but I think we've got some time for questions as well. Yeah. Absolutely. I've seen a few questions coming in from the audience, but just as I'm watching this and listening, I know I'm kind of a skeptic when it comes to new tech. I think I probably bought a DVD player two or three years before streaming became a thing. I'm a late adopter. I'm sure there are skeptics out there about AI, reps who maybe have tried it, and it was something generic, and it just wasn't really helpful. Brandon, you gave a great presentation there. What would you say to them to advise them to give it another shot?

For those who are skeptical about AI? Exactly. Yeah. Well, specifically the difference with AcuityAI is it is grounded in med tech specific data, like we talked about. So like procedures, providers, accounts. So when you have a real context layer, it gives you something that, like we said, the generic chatbot just can't do. So, for those skeptical, I would just say give it a shot.

Think about something you do on a day-to-day basis that AI could, again, help you with either uncovering new opportunities or efficiencies, whether that's prepping for a sales call or researching an account.

And just be specific with it because, again, I think about AI kind of as like, it might be a teenager now, but it's almost like a toddler. You've got to kind of baby it for a little bit and when you first start out with it may not give you the results that you want. But slowly but surely, it's going to uncover some opportunities and give you the desired results. So, you've just got to keep on keeping on, as those of you out there who have kids. You've just got to keep at it, and you'll get some good results.

That's a great point, Lee. I think like a child, I think you get out of it what you put into it with AI. You mentioned having the context layer. Isn't that something anyone can build? What's unique about that, what AcuityMD has with that? Yeah. It's a good question, and the short answer is it takes a lot of time and a lot of money because we've been doing this for seven years, and we still have large teams solely focused on improving that context layer. And it starts with the claims data, and we have a number of partnerships across CMS, directly with payers, with clearing houses, and then a ton of work that goes into modeling all that data to actually represent which procedures are happening, which locations, done by which physicians. And again, that's kind of just the starting point. That's not to mention all of the other data that's layered in there, whether it be publications or industry relationships or IDN and GPO affiliations, upstream referrals, and actually being able to track the patient journey.

And so there's a ton of market data and modeling that requires a big team, a big investment to actually build out. And so we've done a lot of that work, of course. And then not to mention all of the first party data in order for the AI to actually generate a really valuable response, it also needs to respect your persona, what products you sell, what segments, and CPT codes you actually care about or don't care about. And so, when we talk about the context layer, that's what we mean. It's all of that information that the AI is scanning to generate an output that's ultimately going to be valuable. So, you can do it, to answer your question, but it's very hard.

Interesting. And Brendan, I know we may have some new users on here who are trying it, or some folks who maybe will sign up immediately after the webinar. That's our goal. What are some things that folks should think about when they're prompting AcuityAI to get the best possible response? Because so much of it is how you phrase questions and what your prompts are. Yeah, sure. No, you kind of said it right there. Yeah, you just want to be specific about what you want. Think about what you need and be specific about what you want, what you ask it. The more detail, the better the prompts, the better the output. So, tell AcuityAI the format. Do you want bullet points? The number of answers you want. Do you want a short paragraph? Do you want three paragraphs?

And again, going back to my analogy with children, have a back and forth with it. Ask it what it can do. Yeah. Tell it what good looks like. It's kind of funny to think about, but that's how it learns, and that's how it works well. So, just simple prompts like that, and then as you get more comfortable with it, then you can go deeper and deeper into sort of more of those business specific tasks. But yeah, just keep it simple at first and have a nice back and forth with it, and you'd be surprised. It's pretty intuitive.

And I always say please and thank you when I use my AI. So be polite to your AI. That never hurts. Right. We do have a couple of questions rolling in, but I just had a quick question for you, Lee. For sales leaders out there, or commercial operation teams, what types of organizational direction or structure should folks consider to develop as an AI forward commercial organization? Yeah. I think it's a really important time to actually transform your company around AI and give your company both the direction and the resources that they need to unlock all the benefits of AI. And I think, to answer that, Tom, it's about balancing structure and process with also giving your team and your sales organization the ability to go be creative and go think about outside the box and go kind of push the limits of the AI. And so I think, the ones that can set the tone and do both of those things and actually say, "Hey, here's how we expect you to use AI," right? "Here are the prompts that we expect you to be plugging into the system," or, "The automation that we expect to take place," or, "Here's how to set up X, Y, and Z," and give some specifics, right? So you kind of raise the floor, raise the lowest common denominator.

Mm-hmm. But, don't cap your organization, right? You don't want them running wild with no direction, but I promise you with how fast things are moving and how broad the capabilities are, some of your high performers are going to find new ideas, find new use cases. We're constantly seeing that as we roll out more functionality, and we see what users are inputting into the system. And they're very creative, and I think that's what's going to kind of keep moving the ball forward. So, if I were a sales leader, commercial ops leader, I'd be trying to strike that balance.

Excellent. All right. We have a question here from Peter, and Brendan, maybe you can take a turn here. Peter asks, "Given the various concerns about AI adoption, do you think it would be helpful to add a specific requirement in the sales representative compensation plan to drive adoption among less willing sales representatives?"

Ooh. Yeah, right. What a great question. Being a former sales rep, yes, please. I don't know about required it, but that's actually a great idea. AI's here. It's here to stay. And the people that are using AI are going to out-compete and they're going to just beat the people that aren't using AI. So I think that's a great idea. And there's a clear ROI with AI, specifically with AcuityMD and AcuityAI. So I think it only benefits everybody the more that they can adopt AI into their daily lives, particularly within med tech sales. But yeah, I think it's actually a great idea to incentivize them to give it a try, and I think they'll be pleasantly surprised with how much it impacts their sales and their day-to-day efficiency.

We always ask this about physicians, which physicians are fast adopters, which ones aren't. Are sales reps fast adopters of new tech, Brendan, or do they have to be dragged kicking and screaming? Yeah, you know what? I can't speak for every company or industry, but mine, not to bash mine, but no. Not fast adopters. Yeah. We have a lot of tenured salespeople that are very set in their ways. The quote, "Can't teach an old dog new tricks," comes to mind.

But hey, this is a great way to try to get them to change and evolve with the times, for sure. Yeah. You get something that works and you're like, "You know what? It ain't broke," but you can still make it better even if it's not broken. Exactly. Lee, let's steer the next question from Ethan to you. Sorry. Got a couple more questions and it moved it out of my line of sight. Ethan asks, "What is the most recent market insight data populating AcuityMD tools that reps have access to? Healthcare data typically lags one plus years."

Yeah, it's a great question. We get this one a lot, and you're right. I think historically, a lot of the data that's been delivered in this industry has lagged quite a bit. We've done a lot of work to both ingest and model our data a bit more quickly. So, we are actually, this week or next week, we are launching the Q1, so calendar year Q1 2026 data. And so we always look at a rolling 12 months, and it lags a quarter. And so we're about to launch the Q1 2026 data, so that'll bring us up through the end of March of 2026, and then at the end of next quarter, we'll roll in Q2. So that's kind of the cadence that our claims data goes on. Obviously, we have a number of other data points that come in mostly on a more frequent basis, and we're starting to look at ways to even increase the frequency of the claims data. But to answer your question, yeah, that's the recency that we're looking at.

Okay, great. I did get a note from Chuck, long-time listener. If anyone's having issues with audio and you haven't refreshed, try refreshing. You'll pop right back in. You won't miss much at all. And if you have a duplicate of audio, it should clear it up.

Next question from Don. Lee, I guess, why don't you take this one as well? How have companies reacted to proprietary sales data or other data security questions as the data integrity is managed by CFO in startups or CIOs?

Yeah. It's a good question, if I'm understanding it correctly. So I think from what we've seen, and we integrate customer sales data as part of our standard process because it's an important data point for a sales organization to know, of course. If you need to understand what your footprint is at an account, that's going to make the output a lot more powerful. And so I think, of course, companies are always skeptical, I'll say, or cautious, maybe is the better word, that their sales data is remaining proprietary and not feeding another model or going to be seen by another company. And we have very strict, both contractually and then technically, firewalls in place to prevent that from happening. And so every company's data lives in its own instance and there's no risk of it leaking out or any security or privacy protocol being broken. So we take that very seriously. We know that trust is critical in this industry, and that we can't have any hiccups there. And so that's critical to us. And usually we have the conversation, we explain how it all works, and that answers the question. So of course, there's handfuls of exceptions here and there, but I would say that's mostly the reaction that we've seen.

Great. All right. Chuck, I'm glad you figured out your audio problem. A question here from Tristan, and Lee, if you want to continue. Sure. If you want to keep the mic. For large organizations, would it be better to provide a centralized AI platform with guardrails that provides the same set of capabilities to each sales rep? Or should reps be empowered to adopt AI on their own in whatever way works best for each person? Great question. Yeah. It is a good question. I think kind of goes back to my earlier point on, I think, balancing structure and process and standardization with the ability for folks to be creative. And so I don't know if it's necessarily an either/or, Tristan, but I think for the AI to be as powerful as possible, it needs to be centralized and it needs to have the right context, right? And so I think the risk of each person adopting their own AI system or whatever works for them is that it doesn't have enough context or enough structure for them to get as much as they really should out of it. And so I would kind of bias towards something that is centralized, that has all the context that's going to be most relevant to your organization.

It has your selling methodology. It has, obviously, the ICP and the segment that you focus on. It has all of your call sheets and your FDA-approved on-label language and things like that are going to give it all the context and allow you to direct your team. But also probably give your team, because even with that type of tool, the guardrails likely won't restrict folks from identifying new use cases that are kind of within the bounds of what you'd hope they'd do. So I kind of lean towards that for that reason.

How about you, Brandon? I thought we'd continue with our child analogy here, but I'm going to just step away from it entirely before we beat that one to death. Do you want guardrails or do you want folks to run free?

No, I'm trying to think of a good child analogy. I don't have one yet, but I'll just piggyback off of Lee. Maybe a playbook in there in sports and coaching. I think, quite simply, you want everybody to operate from the same playbook. How about that one? So I think it just makes sense for your commercial strategy to marry your sales execution, I think have a one centralized platform where everybody can operate from the same source of truth, operate from the same data, just makes sense. Again, speaking from experience, I was just in the field literally like three or four months ago and didn't have anything remotely close to this tool, which is one of the reasons why I joined this awesome company. I think it just makes sense that everybody's operating, again, from the same playbook. They can speak the same language, and they have the same objectives and priorities that they can execute on in one centralized platform.

Absolutely. So I'm not seeing any more questions from the audience. If you have one, get it in quickly. If you don't get it in time to be asked live, it'll still go to AcuityMD. And of course, if you're watching this on demand, you'll still be able to get your questions answered. They'll go directly to AcuityMD. I should've said something at the top.

Let's close things up. Brandon, back to you. You mentioned how quickly this field has evolved just over the last couple of years, over the last two years or three years with this particular tool. But sales rep, the job has changed, I think, or at least the tools available to sales reps have changed considerably over the last half decade, from my perspective. What do you say to that, and how different is it now than it was maybe 2018, 2019?

Yeah, it's the old adage, the only constant is change, right? Yeah. Right. Everything's evolving so fast. And as a rep, I always look for that little added edge. I think we've all been there when we're just kind of going through the motions. We don't have new products to sell. We've kind of gone over all the clinical trials and what not, and you're looking for that edge. And this is it, and this AI tool is it. It's specifically embedded in this great data platform. And so I would just encourage everybody to give it a shot.

Use everything to your advantage, not only within your company, within your marketing materials for your products, but also the tools like this to anything to give you that added edge. Because again, if you're not keeping up with the times, I can promise you there's some up-and-coming rep that wasn't in the field in 2018 when the old ways were working, who's going to use this and is going to take it to you.

Amazing. And Lee, we'll give you the last word. As you mentioned up top, you co-founded this in 2019 with Mike Monovoukas and Dan Coe. At the time when I first started talking to you, I wasn't quite clear sort of what you were doing and where you're going to fit, but you folks are sort of riding a wave of this revolution. What do you see happening not only with this tool, but also more broadly in the sales rep industry going forward? Is more change coming? Is this just the tip of the iceberg?

Yeah, I think this is just the tip of the iceberg, to be honest, because we're still in the very early stages of this, especially for this industry. I think med tech, for a number of reasons, maybe lags behind when it comes to technology.

And so I think we're still in the early days, and so I think where this is going is we're going to see a lot of systems start to integrate, right? And a lot of the stuff we talked about today was a bit high level on the workflows that med device reps and commercial teams are responsible for. But when you really get into the organization, that encompasses a lot of different systems. You've got a CRM, oftentimes. You have a targeting platform like AcuityMD. You have an ERP system. You may have a number of other systems. And being able to let all of those talk to each other so that a sales rep truly is automating or making some of their day-to-day a lot more efficient, and probably some of the rest of the organization as well is making their responsibilities a lot more efficient, a lot more powerful. And so where we think this is going, back to AcuityMD, is as we start to launch more AI capabilities, more persona-based agents, AcuityAI is not going to be just for a sales rep. It's going to be, as I mentioned, for senior leadership at an organization. It's going to be for strategy and business development and upstream marketing groups to actually figure out where to go next, right?

And what indications they need to expand to or what new call points they're going to go after or what companies they may think about acquiring. And so, by way of integration and MCP into other systems and also through further capabilities, I think it'll be really a starting point, a very powerful starting point for a lot of the commercial workflows in this industry. So yeah, very exciting times, moving very quickly, and we're looking forward to playing a role in this phase of bringing AI to medical device. That's great. And we at DeviceTalks have been grateful to play a role in AcuityMD's rise. So thank you for joining us today, Lee Smith and Brandon Hall.

Thanks, Tom. Thanks, Tom. Great to be here. Thanks.