Turning Market Shifts into Field Action for Medtech Commercial Teams - with Mike Monovoukas & Alex Wakefield of AcuityMD

Welcome everyone to the Emerge AI and Business Podcast. Today's guests are Michael Monovukus, CEO and co-founder of Acura TMD and Alex Wakefield, their chief revenue officer. Acura TMD combines real-world healthcare data, AI-powered insights and intuitive workflows to give MedTech companies the information they need to grow market share and get their innovative technology to more patients faster. Michael and Alex join us on today's show to discuss improving MedTech commercial strategy by replacing manual data entry with proactive market and field signals. Our conversation also explores achieving 10x efficiency gains through voice-driven workflows and using predictive insights to dramatically accelerate new hire onboarding and territory ramp time. Today's episode is sponsored by Acura TMD. Before we begin, a quick note for our executive listeners. Emerge invites enterprise leaders who are driving meaningful AI initiatives to share what they're learning with a peer audience. If you're moving real projects forward and want to be part of the conversation, you can learn more at go.emerge.com/expert. That's go.embrj.com/expert. Now the conversation with Michael and Alex. Michael Alex, welcome to the show. Thanks for having us. Guys, I think that most people have an intuitive sense that the R&D side of MedTech is incredibly con-complex. But what's perhaps less obvious or less talked about at least is the complexity on the commercial end. Markets are unpredictable, especially now in 2026. Knowledge transfer is subject to the rigor of the reps and the day-to-day is packed with uncontrollable variables that kind of make it difficult for leaders to prioritize where the team should focus. So I think in light of all of that, let's maybe start a little bit practically. You guys can answer as you see fit. But what are the typical bottlenecks that MedTech commercial teams are facing today? Yeah, well, Nick, thank you for that lead in. I think it's a fascinating time to be, you know, selling into provider space, into health systems. There's a lot of change going on in how hospitals are consolidating what drives purchase decisions, how surgeons receive information, the complexity of the products that are being commercialized to your point on the R&D side is exploding. So there's a lot of complexity, you know, in the MedTech commercial arena. And when you put yourself in the shoes of a, you know, field-based sales rep, right, they're the ones accountable for driving adoption and driving sales of their product portfolio. So they're being asked to navigate an increasingly complex sale, the one that involves not just the clinical side, you know, selling to the surgeon comfortable about the clinical benefits, getting them comfortable about using the product in the, you know, in the patient setting, but then also on the, you know, financial and administrative side of getting a product verbal. So the sale is getting more and more complex. And where I see, you know, the fundamental bottlenecks in breaking down execution is how the rep should adapt their approach, given all of the landscape changing around them. Historically, sales reps have not really been armed with resources to help them adapt their approach and help them stay on top of shifts and changes in terms of what, you know, what the sales organization is providing reps. And when you think about, you know, the tools and systems that reps are being given, you know, you think about the customer relationship management software, CRM, as a big category, which is a crucial, crucial software. It's really powered by data entry, it's powered by, you know, asking historical questions of the rep. What did you do, you know, you visit this account, what happened? By nature, those systems, even though they store a lot of data when compliance is high, they're looking in the rear view mirror about what's happened and they're sort of, you know, only given the lens of the rep or the company. And that misses all of this market signal about what's actually happening in the market to help these companies and the selling organizations be proactive or leaning about how to adapt to a changing landscape. Yeah. In an interview recently, I heard an executive referring to the variety of tools that their employees use as the Frankenstack. And I can imagine that in this space for these reps, also dealing with kind of a slew of different tools, the CRM from this provider, this piece of software from there, I can imagine it gets into a pretty messy space for these reps. But if we start to look, if we, we, we've discussed some of the, let's say, bottlenecks, broadly speaking, if we were to, let's say, double click on the reps, like out in the field, where is the greatest, let's say, what's taking up the most of their time in a typical reps week? You know, how much of it would you say is kind of administrative stuff versus higher impact work or something more strategic? Yeah, maybe I'll jump in on that one, Nick. Thanks. You know, MetTech reps, just focusing on field facing reps, have a really difficult job, a really job. I think it's one of the more difficult sales jobs that exist. They're pulled in a million different directions, whether they're covering cases or hosting events or as you implied doing some admin at the beginning or the end of the day whenever they can fit it in. It's challenging. They're pulling a lot of different directions. And I think the skill set of a lot of the existing reps today is very interpersonal. It's in still an interpersonal style. You have to, you have to interact with a variety of folks, surgeons, folks in the administrative office of hospitals. So it's a very interpersonal sale. And sometimes those personalities don't necessarily lead to tech forward adoption. So the MetTech industry is sort of historically kind of a late adopter of technology. Later on, this may help, but the efficiency of the field and where their challenge a little bit is doing the admin, doing the input. It's not necessarily a skill set or, you know, they're sort of tired of the day. So any of the rule stack, I do like Franken, Franken stack, that's pretty good. But any of the tech stack that requires time from the reps sometimes gets, you know, pushed down the priority list because their job is to make sure their product is front and center of their customers, make sure they're communicating effectively. And so some of the commercial operations that they're intended to input to give visibility back upstream into the leadership to inform forecasting and things like that. Those are the areas of breakdown that I see a lot out in the field. Absolutely. Yeah. I mean, you know, it feels like, as you guys have mentioned, when it is such an interpersonal job, when it is such a difficult tough sales process for these reps, I imagine that anything involving the tech stack, inputting data administration is nothing but burden for these people. So if this is, say, one of the key bottlenecks and it's the processes that are required of these reps are something of a stumbling block. The time that the reps have to have out in the field, interfacing with client surgeons, as you said, all of the various people throughout the system. I guess the next question would perhaps maybe shift to something a little bit more structural. What data flows and signals would you say kind of need to be in place to make commercial decisions more efficient or more proactive for the long term, if we're now shifting away from the reps on the ground and kind of thinking about how that data is flowing into these systems? So what signals need to take place to make better decisions, long term decisions that are actually going to benefit the company? Yeah. So I'll sort of break it down into two types of signals. You know, one type of signal is how the market is evolving around the rep and around the company. And these are signals that are inherently external to what the company can observe. These are things like physicians, retiring, physicians moving to different territories, fellows graduating and starting practices or joining practices in new geography. These are things like referral networks, shifting procedures, migrating from hospitals to ASCs or office-based setting, reimbursement shifts and changes that alter the financial incentives of providers, competitive product launches, pricing or contractual shifts with competitors. So these are all sort of external signals that really impact the ultimate question, which is what should the rep do next to hit their quote with the drive adoption of their product? And those signals exist, those external signals exist, but they're scattered across different systems and formats and the challenge is really connecting them accurately, sort of curating them and connecting them to the person who matters, right, the rep so that they can act. And so there's a huge effort on just the data side, but then also on the presentation layer to make sure they're relevant and personalized those signals for the reps. That's sort of, you know, one, one. categories that external single. I think the other category of signals that matter are, you know, Alex mentioned kind of the role of the MetTech rep. You know, they're in the field, you know, they're in hospitals, they're in operating rooms, they're observing their tip of the spear, observing how this market is evolving in real time. However, so they have a great source of insight and information about where the market's heading, where competitors are moving in, what, you know, product apps might exist today. However, you know, it's very, traditionally been very difficult to harness that, you know, sort of field-based signal into relevant context for the organization to act and decide on and form strategy around because, you know, the status quo is, you know, here's a static form that I want you to fill out every week or every month, you know, sharing these insights, which is not, you know, it doesn't completely fit the fluid field-based nature of how, you know, how the reps go about their day. And so they're spending, you know, one day a week doing admin work as opposed to being, you know, out in the field, you know, building relationships with customers. So that second source, which is all the field signals that reps see, but there isn't really a natural place to store that information or to collect that information, to drive strategy. And for MetTech organizations, you know, their largest investment category typically is the selling organization. And, you know, imagine the power of harnessing that, you know, that field signal at scale and understanding how the market is dynamic and evolving at scale without burning the reps and taking time out of their day to collect that information. So those are the two categories of the market signals that, you know, these companies just won't know about because they don't have heat on the street and they don't have, you know, that data living in their systems. And then there's also kind of the field-based signals that they do have heat on the street. They do have visibility into, but it's hard to collect and synthesize that information today. Yeah, I imagine, you know, just on those field signals, a lot of them are also, you know, from intuition, feelings, long-term relationships, things that I guess you truly can't necessarily document or document accurately or in real time, well, by any means. I just wanted to get a sense. You mentioned static, filling out a static form at the end of the week or the end of the month. How are these field reps actually kind of documenting the learnings or the, what they've done throughout the week, the month? Are they literally typing into a form? Are they filling out some kind of software? What are they actually? How are they documenting what they're doing and what they're seeing? Yeah, we've seen everything from, you know, software solutions like CRM having, you know, fields and notes and surveys built in to, you know, accelerates being sent around to, you know, give feedback on, you know, at the surgeon level or at the account level, different, you know, different products. So it's a variety of, you know, templates, whether they're kind of software-based or, you know, file-based, I collect and harness that information. Yeah, I would add that out of the back of that Nick, sorry for stepping on top of you there, but what Mike said is correct, but I would also add that even in some of the more successful organizations that we work with, you know, all size of MedTech companies, some of the largest in the world, and even the largest organizations in the world that are very successful, there's a variety of ways that they do it across different businesses. Some might take manual notes. I mean, there's actually very little input sometimes in some of the more successful B's. Some organizations haven't even rolled out like laptops to the organization or CRM, and they're, and they're still successful. So it's a, it's a complete variety of ways to collect this information, and largely it's not done very successfully. So that's sort of the, how do you bridge the gap to meet reps where they are so that you can actually collect some signal from the field? Because I would argue that lots of real-time signal from the field, that the reps experience in their everyday conversations don't actually make it back into the planning and the strategy teams inside. And those are some of the things that, those are some of the big gaps that have opportunity to fix. Yeah, absolutely. Yeah, I mean, it feels like, a little bit like the Wild West to a certain degree, kind of anything goes, whatever works, and a lot kind of gets left in the gut feeling of the rep and the back of the mind of the rep and like the note that he's scribbled on a piece of paper that's kind of at the foot well of his car or whatever the case may be. And I, yeah, it just feels like, as you said, this is where the opportunity lies. The data that is being collected is likely not very high fidelity. I imagine it's not particularly time-y as either. And so, yeah, the opportunity for this technology to come in and start to get a little bit more proactive seems like the golden opportunity itself for the Maytech industry. So I would say that if we've identified, now we've said, okay, this is the huge opportunity. What does it take to start operation rising new kinds of data flows and new technologies such as the many types of AI? What does it take to begin to practically implement this for real on the ground workflows? Yeah, maybe I'll start on this one. I think the key is, I mean, adoption by the field, one could say, is important. But I think that takes the form of meeting the sales rep and process where they are because being in the car and covering cases, being in the operating room, whether you're a sales rep or clinical rep, whatever the function is, those things aren't going to change really anytime soon. So you have to meet the rep where they are. So that, to me, takes the form of in their existing day, whether it's in the car or in the waiting room, how do you feed information to reps its effective and how do you collect signal from reps that's effective? And I think that takes, we think that takes the form of, you know, you could sort of dispel the notion of like logging into a system or UI or user interface. And when you think about voice collection or voice dictation on both sides, all the rep in the car, audibly interact with their phone, for instance, that would give them all the information they need about a surge and about a facility about their practice and how many procedures they're doing and where they're doing them and iterate on all that you're in the car. And then sort of voice dictate back into the system data collection so that it can be fed back into internal systems. And the way that we think about it as far as how do you meet the rep where they are in the workflow today and infuse it into something that makes sense for them. And I alluded back in my first answer to where, you know, being a late adopter of technology might help because if they're not using laptops in the field or they're not disciplined in CRM, the use and the adoption of AI is a great way to sort of leapfrog that and take advantage of the technology becoming available today. Absolutely. Yeah, that ability to leapfrog, you know, you said certain companies may not even have issued laptops. I'm getting the sense now that, you know, if you're on the leading edge and starting to use some of these tools, you're from not having a laptop, you're going kind of straight to, oh, I can drop a voice note on my phone. And I can almost feel the relief of these reps as that kind of technology is coming to meet them probably for the first time in a way that's like truly, truly helpful. That's really exciting and super fascinating. And I imagine that what that allows is obviously far more rigorous documentation and just far more data being collected and then allowing for greater insight and a lot more information to truly be absorbed and for decisions to be made based upon that. Yeah, absolutely. I mean, I think one of the things that's fascinating to kind of think about is, you know, you can learn a lot more about a rep, their territory, you know, how their customers and prospects are perceiving them with a, you know, through a 15-minute phone call just interviewing them, then you can, you know, scouring, you know, their CRM notes and scouring their, you know, sales transactions. And you know, that kind of 15 minutes of context sharing, you know, can go so far and add so much depth to what's actually happening that, you know, is typically not captured in traditional systems. And despite spending a lot more than 15 minutes actually entering that information, right? So I think that's the key. And so, and you mentioned kind of the form factor shifting, you know, away from, you know, laptop to mobile. I mean, I think, you know, the next generation of, you know, AI products, like the form factor may evolve once again, right? I think NETA has quietly built a massive glasses business. You have open AI also teasing various new form factors whether they end up being, you know, earphones or watches or whatever it ends up with glasses that's unclear right now. I see. some rumors of Apple also potentially having a pendant or something. So we shall see. Yeah. So that form factor shifts and becomes more kind of well adopted across the industry. I think there's another big shift that may happen as well. So I think that gathering context from sale reps is certainly one piece of the picture here, which is, you know, how do we automate the administrative work for them, that administrative work for them, save them time. So I think that's one huge unlock that AI will provide. But I don't think it's enough to really, you know, unblock or accelerate adoption in this space. I think the other big pieces, you know, showing reps with what they don't know or might not know and being sort of proactive and predictive about the insights we share to reps, you know, to help them, you know, really make a decision of what should you do next and how should you, you know, call on this position and what should you bring up in this conversation. And, you know, I think those types and where should you go if your case gets canceled, right? And you're, you know, in, you know, a hospital waiting room and, you know, you're, do you go home at 2 p.m. or do you have an opportunity to, you know, to prospect and maybe, you know, plant some seeds for future opportunities. So I think being proactive and predictive for reps to help, you know, help them as a, you know, is the other missing piece, not just like automating the administrative work, but also, you know, helping nudge them and giving them the, giving them the insights to that they wouldn't have been able to piece together themselves. Yeah, yeah. I mean, I guess it's, it's just, you know, you're, you're trying to frame it in a way that you're, you're giving them firepower, additional ammunition to go out there and really kill it in sales, I mean, they're filled. You mentioned earlier that, you know, a lot of these processes, many of the companies in the space, et cetera, are used to doing things a certain way. And I, I get the picture and imagine that perhaps the reps themselves are also very much used to doing things in a certain way. And the idea of new tech coming in is perhaps could be disruptive to the way they're thinking about things. Could be some pushback. Is it clear to them? Has it been clear to them from what you've seen that, that from the get go, there is value for them? Or are you seeing it, that it's a touch more difficult to get them to, to start using this, the software? I think on the, we kind of think about the framing of kind of proactive sort of, you know, nudges and help for the rep to, to get them to, you know, give them firepower to your point versus automating administrative work. I don't think we're, I don't think the industry is quite matured on either front today. On the automating, on the automation of administrative work, I think it's only got more complex for reps in recent years. You know, I think one fascinating thing is when you talk to sales reps at larger organizations, you know, the tools that the organizations are purchasing for the reps, there is a disconnect between the tools that are purchased versus the tools that end up adding value for the reps in discrete ways. And you see a lot of, like I've had examples of sales reps who, you know, will pay out a pocket for ChatGbT or Anthropic, cause it helps them, you know, break down problems, it helps them plan for, for calls, it helps them, you know, see around corners. And this is kind of, you know, the untrained to the industry version of these AI models. And the reps are paying out a pocket for that capability. And so, you know, I think, I think two things need to happen, you know, to kind of cross the chasm there. The first is, you know, we need to turn these AI models. We need to give them the context to add value in a, in a MedTech enterprise sense. And what I mean by that is number one, giving the models market context about what's actually going on in the, the specific clinical area that you're selling your products into, all those signals that we talked about earlier, very relevant pieces of context to get it to the AI model, the reason of them. And the second kind of piece is the user and organizational context that these companies have. So, on the user side, like what is the reps territory? What are their, you know, sales goals or quotas, you know, how, how tender it is the rep, what product are they selling, et cetera, et cetera. What are their historical, you know, activities or pipeline or sales transactions been like. And then on the organizational side, like what are the organization want to accomplish, you know, how are they positioned in the market, who are their competitors, are they organized, et cetera, et cetera. Once you infuse the models with all of this rich context and becomes much easier to ask the model or ask the AI system to accomplish a goal that is like very civic and personalized to the rep, but also in line with the, you know, broader enterprise strategy. And that right now does not exist because it required sort of a deep integration and understanding of the context of the organization as well as a deep kind of integration and context of the medical device domain and the data that kind of governs it. And so I think, I see a disconnect between what the reps do to see and find value. They're taking matters in their own hands or, you know, buying chat, you can see how to pocket. They are scouring, you know, the internet for leads. They're doing all this sort of external work to show value. And then, you know, the systems that, you know, are installed from an enterprise perspective, you know, are not necessarily connected with those kind of tools and initiatives. Yeah, I wasn't, I wouldn't add anything to what Mike said. I was just going to actually, as he sort of go back to it at the end, put a fine point on what he's saying and what we're seeing in the field is that the adoption to some degree on AI tools is inverted in that the field is taking matters in their own hands, like Mike said, but they're also more forward requesting adoption and requesting AI based tools from leadership office teams. And it's a little bit inverted in that we have seen field reps definitely pull demand for these easier and easier and more comprehensive tooling. And it's more like the internal teams are actually taking a slower approach to adoptions. We're trying to keep reps, you know, as quickly as we can out in the field, but it's an interesting dynamic. Yeah, that is actually super interesting. I mean, I just trying to think about it in my head, you know, you're out in the field, you're surrounded by variables. It's a far less kind of black and white space, whereas on the administrative side, it's black and white. And if it's not precisely the way you want it to be, you're probably not going to use it, you're going to be hesitant. You're going to be, I guess, entrenched in the ways that you've already done things, whereas in a world where you're surrounded by the variables and you don't know what's next, any bit of technology that can come your way or that that adapts to you and could help some of these intangible problems would be accepted with open arms. So yeah, it's a really interesting idea. I'm going to store that one in the back of my head. Let's assume that the data and workflows are aligned. I guess the big hairy question in the room is leaders are still facing this kind of the capital allocation question. Looking ahead, we're in a fairly tumultuous time right now and things only seem to be accelerating with progress for the remainder of 2026 or just looking ahead in general. How should commercial leaders decide where to invest in AI and beyond that, once they have invested in AI, where they're looking in terms of ROI and how to measure that? Yeah, I think it's a really interesting time. I think there's a lot of, you know, originating from, you know, the AI labs and, you know, a lot of thinking in the Bay Area about, you know, AI is like a labor transformation in these larger enterprises and labor replacement. And I think that's wrong for a number of reasons. Number one is, you know, every major technology shift, you know, has, you know, labor, labor adapts to, you know, technology, right? And finds new kind of jobs to be done as technology shifts emerge. So I think like overall in the industry, I think that sort of, you know, framings incorrect. But then specifically in the MedTech industry and MedTech commercial, you know, it's such a personal in person sort of visceral job where the sales rep needs to go meet with the surgeon and the staff and train them and get comfortable and be present in the cases. And, you know, I think that that is not going to change, you know, with this way of in AI technologies. And so, so when I think about ROI from like a leadership perspective, I think number one, you know, you've got to, you've got to decide, you know, what, what you're optimizing for. You're optimizing for revenue growth. And what I would think is like, how do I help my reps be as effective as possible to the end customer and spend as much of their time with the end customer prospect as possible, right? So, so more productive reps who are spending more time in the field who are, you know, more effective sellers would be, you know, where I would start like revenue generating opportunities, a clear tie-in to ROI. And, you know, in order to kind of underpin that, start with sort of the more effective reps. Well, how do we get the reps to present better in front of their prospects, present as, you know, deeper subject matter experts have richer understanding of the clinical context, richer understanding of the competitive dynamics and differentiation, understand the physicians, practice and the, and the hospitals, sort of broader economic, you know, position, giving the reps those insights, making easy for them to learn. about their prospect as a critical part of that, 'cause they show up to a movie, and they blow away the competition because they're so well attuned to the need, and so well attuned to what they're selling and why it ties to those needs. We've already talked about the rep efficiency side, right? With how do we automate that work or make it easier to do on the fly? Whether that's, Perrepp is driving 30 minutes to visit a prospect, can we just knock out the administrative work on that 30 minute drive for a voice conversation, right? So I think that's what I would think about is, you know, what goals are you trying to achieve with any investment? I think, you know, on the commercial side, I think revenue growth is the clearest goal, and to me that breaks down into rep effectiveness and rep efficiency, and I think AI is a really powerful way to drive both those. - Right, right. Yeah, I like the way that you've characterized that. Alex, go ahead. - I was gonna add, I would just break it down to a very simple, thought process or analogy. It's almost like migrating from kind of physical books and research in magazines that would show up in periodicals and the dawn of the internet, and it's probably the most boring analogy ever. But if you're going to go in the mail versus going online to learn about it, then you've wasted a ton of time. Same thing to you, you know, the concept of AI has been around for a long, long time. It's finally effective because troves of information underlying it, allow it to actually help and be massively efficient. So if reps are doing research on LinkedIn and PubMed and Google and whatever and logging in to different applications to log activities, that is an utter waste of time. It should be instantaneously delivered as dynamic as possible with as many updates as possible and an interactive experience, like I said earlier, without necessarily the concept of a UI or a log on so that these things can gain, so that the reps can gain incredible, just massive efficiency gains. You know, we talk internally 'cause I run the commercial team about 10x efficiency gains. That's how people should think about it. And whether, you know, you may not replace people, reps with AI, but perhaps you can make them much more efficient in their territories and increase territory size. So keep the teams eyes, sell more, but there are such massive efficiency gains to be taken advantage of. It's, this is how you have to think about AI and grabbing ROI, like Mike said, either efficiency gains or revenue growth. But yeah, the use cases are pretty significant, I think, for field sales teams. Yeah, I mean, it almost feels like one of the kind of perfect cases. And I imagine that as we're able to track more and getting more data pulled into the system from various different sources, it's only gonna get better and better and better and give those reps greater insights. I just wanted to ask kind of a last practical question from the implementations and deployments that you're seeing out in the space at the moment. What would you say is kind of separating the cases that are winning and flourishing versus those that are not doing so. And I kind of floundering or falling at the first hurdle. I guess you could come at that from two angles. You could come at that from project efficiency and that sort of internal organization from our customer base that might not prioritize projects or put the right folks on it. I'll set that one aside. Because I think my answer would be at least from a field standpoint is, we see better return and better realization of value of solutions for field teams that have an open mind and nest to adopting technology and continuously improving the way they do business. So the core layer to that is people that have been selling for a long time that might think they know the entire territory, they know all of their docs, they know everything going on. That's where we see a limitation to improvement. So we've seen new reps and incredibly seasoned successful reps that have an open mind be really successful. But we think about psychology in the field. It's, am I open minded? Do I want to get better? Do I want to lead in technology? Or do I want to kind of think that I know everything going on in my network? - I think that's like absolutely speaks to kind of the ground swell and the kind of open mindedness that merges from, or should I, the success that emerges from being open minded. I don't think there's a replacement though for leadership buy-in and leadership kind of leading from the front. And I'll give you like an internal perspective for how we run the business, at a QDMD where we started to see a lot of the opportunity and AI both in terms of how we work internally, how we build software, how we analyze our business, how we run meetings, et cetera. But then also in terms of the types of products we can build. So, you know, there are kind of two different transformations going on right now, internally at a QDMD. One is transforming how we operate and the other is transforming the products we can deliver. And, you know, I think the strongest way to get an organization to buy into those shifts and to realize the benefit of those shifts is to lead from the front and, you know, have a leadership team really lean in and demonstrate, you know, how they're transforming, how they've done their job or how they operate the business or how they build new products, including, you know, your CEO and CTR getting back into the code and starting to prototype new ideas and demonstrate what's possible and really changing how we've worked, you know, the last five or six years since starting the company. And so, I don't think there's any replacement for, you know, leadership really leaning into the shift and understanding the impact that it can have on the business and on our customers and on our customers' customers and leading from the front, I think is critical. - Absolutely. Yeah, I mean, I guess kind of to nutshell a little bit feels like if you are leading from the front with your leadership, you are maintaining open-mindedness, embracing the technology and then developing the use cases or at least using the, or providing the tools that empower your reps, that meet your reps where they are, you will be setting your teams up for for the opportunity to achieve a lot more than they could have ever had in the past. - Thank you so much for your insights, guys. It's been a great lesson. I think our audience is gonna truly appreciate it. And yeah, great having you on the show and we will certainly like to have you back on someday. - Thank you, Nick. It was great to meet you and great to be in time if you think you're fully opportunity. (upbeat music) - Closing out today's episode, I think there are three key takeaways from med-take commercial leaders, SVPs of sales and even heads of revenue operations from our conversation with Michael and Alex of the QATMD. First, enterprise leaders should shift their focus from historical internal data entry toward proactive market and field signals that allow teams to adapt to real-time shifts in the commercial landscape. Second, operationalizing AI should prioritize meeting sales teams in their existing workflows, such as using voice dictation to convert travel time into productive administrative updates. And finally, the most significant returns on AI investments come from driving revenue growth through increased representative effectiveness rather than focusing on labor replacement. Position your brand alongside the Fortune 500 leaders defining the enterprise AI roadmap. For the opportunity to showcase your solution to the executives currently funding and scaling global initiatives, partner with emerged to reach the decision-makers holding the strategic mandate. Secure your partnership at go.emerge.com/partner. That's go.embr.com/partnir. For further executive level analysis and to join our network of leaders delivering workflow impact with AI, visit emerge.com. On behalf of the team at emerge, we'll see you on the next episode. [MUSIC PLAYING] [MUSIC PLAYING]