Mouli Venkatesan on AI, Interoperability, and Connecting Healthcare at Scale

0:00But the most important thing, the biggest challenge in healthcare is not lack of data. It is a lack of connectivity between the data, the systems, and the many organizations that are there.

0:14Peter High: Welcome to Technovation. I'm Peter High, President of Metastrategy. My guest today is Mouli Venkatesan, the Executive Vice President and Chief Information and Technology Officer of Blue Cross Blue Shield Association. The association represents 33 independent Blue Cross and Blue Shield companies that collectively provide health care coverage to more than 115 million Americans, reaching communities across every zip code in the United States. As CITO, Moley leads the association's technology strategy and oversees capabilities that connect and support the broader Blue system, including data analytics, artificial intelligence, and national technology platforms.

0:49Peter High: His mandate includes helping the Blues use their collective scale while preserving the local relationships that have long distinguished the organization. Molley joined the association in early 2026 after nearly two decades at UnitedHealth Group, where his leadership responsibilities spanned UnitedHealthcare, OptumHealth, and OptumBank. Most recently, he led AI, data, and analytics across the enterprise. In today's conversation, we'll discuss the unique structure of the Blue system, how data and AI can help reduce friction and improve affordability in healthcare, and Moli's perspective on the future of a more connected, intelligent, and consumer-oriented healthcare system, among other topics I'm sure we'll cover.

1:26Peter High: Moli, welcome to Technovation. It's great to speak with you today. Good to talk to you and looking forward to the conversation. Thanks for having me on the show. Today's episode is brought to you by 11 Labs. Most enterprises trying to deploy AI agents hit the same wall. The agent itself is fine. The problem is that it sounds wrong. Robotic, flat, off-brand, and the moment a customer notices, the trust is gone. 11labs develops the AI voice and audio models that give agents a human-level voice, the tone, the emotion, the rhythm of real speech, and wraps them in the full stack you need to actually deploy.

2:00Peter High: Knowledge integrations, workflow tooling, multilingual support, and enterprise-grade reliability. Build human-level conversational experiences into your products, services, and operations. Head to 11labs.io backslash technovation to get started for free. And now on to the interview. It's a great pleasure. I'm so glad you're here. Let's begin with the Blue Cross Blue Shield Association, if you would. Take it from where I left off and share a bit more about the organization that you helped lead. That's great, Peter. You started off well in terms of, you know, let me give you an end to what you said.

2:39So Blue Cross Blue Shield Association is a national federation of independent, community-based, and locally operated Blue Cross Blue Shield companies. And the most operative word there is locally operated. And the blue plants collectively provide health care coverage for one in three Americans. For one in three Americans, if you take a step back and look at that, the scale in which we provide coverage and support for one in three Americans across the country. is, and you also in your introduction talked about, Peter, in terms of relentlessly pursuing and our mission, we relentlessly pursue affordable healthcare and peace of mind for the people we serve in every zip code.

3:23And that's important. That's what this Blue Cross Blue Shield of Association is.

3:28Peter High: Wonderful. Thank you for that overview. And talk a bit about your role as the Chief Information and Technology Officer, if you would. Great. So my role in this journey, in this mission is to serve. And I first forget about the title, forget about the name, the fancy titles. My role fundamentally, I look at this, is to serve the members that we are privileged to have as part of our 120 million in our communities that we are trying to do. How do we do that? And how do I do my part in that? I lead the technology organization. As you talked about, the technology organization that creates national level scale.

4:03The technology organization that creates in terms of how the 33 independently operated blue plants come along together as one unit for our members and from our providers and for many patients that we are privileged to serve. And drive, of course, drive AI in that context, drive data and analytics and a lot of solutions at a national level. But end of the day, my role is to serve every member that we are privileged to have as part of our Blue Cross Blue Shield plants.

4:34Peter High: Moli, I appreciate you offering some of those distinctions. Can you offer an example of where you provide a common technology across the entire system and why? So look at that. So one of the major reasons the Blues have been super successful for many, many years and many, many decades in terms of is Blues have the scale that comes from covering one in three Americas while continuing to operate locally. which means that the ability to balance a national level scale and the ability to go and be in every zip code and community is one of the primary reasons in terms of, which means that you can take a national level solution, a national level idea, a national level concept and make it work for your local clients.

5:24We all know healthcare is done locally. Healthcare is delivered locally, Peter, across the country. And Blues is a great example on how you can take a national level scale solution and deliver it locally and cater it locally to the communities because each community is not the same. Every community, every zip code is not the same. Healthcare operates and works different in different communities, as you and me know in this across the country. So that's what the Blues takes the national level solutions and take it to every community on a local basis. And what are some examples of solutions that are unique to a specific area?

6:01Peter High: Can you provide some of what you think about in terms of some of the nuance there? Correct. So if you look at, you know, in terms of the solutions around, for example, the association processes 400 million claims in a year in 2025, for example. OK, now why does the association process 400 million claims? is because if you take it, not everybody that's covered in a local market gets scared there. They might be a snowboard going from Minnesota to Florida and needs a coverage there. So now how do we process claims on a national level? And you also have employer groups that have got employees all across the country, even though they're supported by local group plans.

6:41So now how do you provide a national level coverage and a national level solutions for people, for this employer that has got employees all across the country? So you've got to create a national level solution for that. Take, for example, provider directory. How do you make sure that the provider directory is accurate? That cuts across. It doesn't matter whether you are in Minnesota or in Florida, that your provider directory gives you accurate information at any given point in time. The most important thing, look at clinical data. How do you exchange clinical data across the ecosystem between multiple payers, in this case, the 30-plus blue plants, as well as we've got to exchange that information between health systems, which in this case, hospitals or ambulatory surgical centers, and the payers.

7:23These are all the national level capabilities that we, from the association, there are many more than that, that we support. I'm just sharing a few examples to you, Peter.

7:32Peter High: And talk a bit about, given the data, you mentioned the statistical significance of the remarkable number of people who are covered here in the U.S., one in three, as you mentioned. Talk a bit about the ways in which you were able to leverage that data to have a better understanding of the needs of different patients and communities, as well as perhaps to benchmark or provide understanding of variations in care? And so that's a great question, Peter. So we have the privilege of having more than 100 plus million members, not just administrative data, but most of the clinical data as well. So once you have this more than 100 million Americans administrative and clinical data, you can longitudinally understand their care journey and their member journey.

8:24Once you longitudinally understand the member journey from the data sets, now you can normalize it. You can make sure that you create insights from the data set. That insights from the data set is created for three major reasons. How can we make sure that we can drive affordable care for that members? How can we make sure that the right clinical interventions can happen at the right time for the members that we are privileged to serve? And how can we generate insights into that space so that the local plan team, could be a care management team, could be a member service team, can proactively engage with the members for outreach and interventions?

9:03So that's the scale of the data that we have. And those are the use cases I just outlined a few to you in terms of how we can take the data, create insights and take it to the local market.

9:15Peter High: And how do you think about layering artificial intelligence on top of that MOLI in ways that can derive even greater value? I would be interested in some of the use cases you find most compelling. And I think when we talk about artificial intelligence, Peter, I got to take a step back because that is the most. We are at a decade. Our generation is so fortunate. And I'll say why. The most great things that happened in our generation is the advent of AI. I believe that being a technologist, I got to say that. And the best use case across many industries is healthcare. The intersection of AI and healthcare is where?

9:55Because healthcare is the most humane thing that could happen. And that is the most personal thing. So I believe the intersection of AI and healthcare is a phenomenal thing that we all have the opportunity and the fortune, good fortune, of helping shape the future of healthcare in this country. Now, with that said, your question around AI and what it means for the association and what it means for the strategies we have, I look at that in four sections. I want to make sure that you and your audience understands it very clearly. We start with mindset. AI is simply not an IT initiative. It is a way in which we could rethink how work gets done.

10:36It's a complete transformative approach from our standpoint. And so it starts first with a mindset. Second, heartset. What do we mean by heartset? Does mindset mean willing to rethink how work gets done? And heartset means how you can lead because healthcare is personal. How can we lead with empathy in creating that transformation for the people that we are privileged to serve? Second. Third, tool set. Which are all the frontier AI models? And which are all the ways in which technologies we could bring in? Which are all the tools that we can buy, build, and partner in terms of helping, driving?

11:15That's important. Tool set. And fourth is skill set. How can we make sure that our workforce, our operations, not just in the association, but across the 30 plus blue plans, how can we make sure that we have the right skill set? That's the future looking forward looking skill set, not just on technology, but every function across every department across the blues. How can we make sure that we can create? So those are the four things when we talk about AI in the association and broader blues. Those are more important. And all of that, all the four things, the strategies that I talked about are grounded in responsible AI.

11:52How can we drive all of this in a responsible way that we protect the people that we are privileged to serve? Hopefully that resonates in terms of how we are thinking about AI. And most companies right, wrong or incorrect jump into tool sets right away. and in terms of I got a tool and we don't look at AI as a technology tool or technology problem, but we look at it a little differently, Peter.

12:19Peter High: I'd love for you to double click a little bit further on the balance between mindset and heart set, especially this whole concept of heart set, since of course you're coining a term there and leading with empathy as you contemplate how best to create value. Talk a little bit about the interplay between those. I think it's a really interesting nuance you're calling out there. Correct. Exactly. So what I mean by mindset, right? So what I mean mindset is I'm making the existing process incrementally better, aka take any process in the system. A member is calling us. Why does a member is calling us?

12:56And can I make the call handle time better? Can I make sure that the agent that is attending the call, we can create the content and the materials to the agent in a much faster time so that the agent can service the member in a faster way and incrementally make the experience better. That's one way to look at it. Or another mindset change that we're asking for is, can it completely eliminate the need for a member to call us? Can we serve the member where they are with the information that they need completely that they don't have to have a call with a healthcare entity for that matter? So that's a mindset shift we're trying to do.

13:37Now, in that mindset shift transformation, what we are talking about empathy is, again, healthcare is personal. It could be for various reasons. It's not like I'm not going to get a call at all. For the right reasons, I'm going to take the AI to a call. How can I make the same call that is happening if that means I'm calling for my mom? I'm calling for my loved one who's going through significant issues, which means A, understands the context of the conversation. that's happening between AI and the member. So the moment that understands the context of that conversation, it automatically routes to a human to engage in that conversation because it knows the empathy that is needed in that conversation.

14:21So it's context-based intervention that's happening. That's a very, very simple example I'm giving you in terms of how do you create empathy in the solutions that we put on because healthcare, believe it or not, Still, every health plan across the country gets millions of calls every year. And the fax industry thrives because of healthcare, Peter. So we got a job to do there is not completely eliminate faxes from healthcare.

14:49Peter High: Yeah, very interesting. And I'd love to, your third topic was the tool set. As you think about the difference across by building, partnering, the three vectors you talked about within that. How do you make the decision as to where to do each? I'd love to have an understanding of your philosophy there. And so, absolutely. So, in terms of toolset, what, you know, we sit in this great set of data. We sit in this great set of data, which is the shared data assets. Now, we got to make sure that we got to make this data assets interoperable, interoperable in an ecosystem with common AI foundations. That is absolutely claves and chill forests.

15:30In that ecosystem is what we look at build by and partner models in that. And it is for custom models that we need to build, large language models, for example, there are a lot of frontier model companies out there, Peter, their full-time job is building large language models. And I'm going to use those large language models. I'm not going to build those large language models, it doesn't make sense. The kind of investments they do. Now with that, and using the large language models and training them on the data set that we have for the 100 plus million Americans, how can we create valuable solutions?

16:11That is something that we are building. That unique opportunity is what? Which is small context-based models. Small context-based innovations. Small context-based interventions is what we are building using those large language frontier models in terms of patient engagement and intervention speed up.

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17:51Peter High: And now back to the interview. And talk a bit about the development of skill sets, the fourth topic. And I'd be curious how broadly you think about the development of these technology resources and non-technology resources alike. Talk a bit about that. And so we have this philosophy within the association that everybody should have knowledge on AI. Not necessarily the scale in which your knowledge of AI will differ based on your role as a contact center person to a technology AI engineer. You could be in finance. You could be in legal. You could be in HR. You could be in technology. you could be in operation.

18:35So the way in which you interact with the tools and what you ask the tools you wanted to be done for you might differ, but everybody should have. So we start with basic training and enablement for all our NTR workforce. Our NTR workforce gets a standard level of training. And then we provide multiple levels of training depending on if an operational product person needs a little more training than just a front-end call center person or just an HR person in terms of how to use certain models. And it goes by that. And then we create certifications for the highest level of the engineers that we have on the team.

19:15We create certifications in terms of like, are you a certified AI engineer with certain benchmarks that we have established based on a lot of industry norms in terms of, are you ready? Which is another version of saying that we are creating our forward deployed engineers within the organization. And how can they work on multiple frontier models and creating solutions for us? Hopefully that helps speed up.

19:41Peter High: It does. It does. Absolutely, Moli. Thank you for that. I know that you're also passionate about value-based care, and I'd love to understand how that's progressing and the steps that you and your team are implementing in order to deliver that? Correct. So value-based care starts with a simple promise of, or with the belief system of, if I can understand my member patient better, if I can understand not just their healthcare needs, but their social economic needs as well. I would be able to intervene at the right time, at the right place and with the right care that is needed for them so that we continuously make sure that we bring the, we make healthcare affordable and bring the healthcare costs down.

20:33That's the promise on value-based care. And how do we do that today? We do that through multiple avenues, Peter, you know, in terms of, again, with many blue plants, the exchange of information that I talked about, timely processing of claims. Clinical data. How can I attach the right level of clinical data to the claims? And that's important. In a value-based care setting, what's more important for the providers or for the patients is do they understand the longitudinal health record of the patient? The more I understand the longitudinal health record of the member or the patient, I would be able to serve them impactfully and effectively.

21:18So longitudinal data, timeliness of data available with whoever is the clinician engaging, whether it's from the payer side or the health system side, is the way we achieve value-based care. And so for that is where the interoperability comes in, which is very important. I know CMS has been behind that in a big way. and interoperability becomes very, very important to achieve that vision on value-based care.

21:47Peter High: Fascinating. And I know from our past conversations, Moli, you've talked about the role that technology can continue to play, not only in providing that value, but ultimately helping to, you know, this is the largest sector of the American economy, so the largest sector of the largest economy on earth. And the possibility of leveraging technology in profound ways to help reduce the cost of healthcare ultimately. Talk a little bit about some of what you see coming in the year or years ahead, as the case may be, that have you optimistic that that's possible. And so I'm generally a very optimistic person, Peter.

22:23So I'm a glass half full person. So you're going to see, you're going to hear optimism from me mostly. So the way I look at it is, as I said, we are at a great generation with AI, with the advent of AI. And broadly, across the industry, we've just scratched the surface of it. Genuinely, we just scratched the surface. There's a lot more to come there. But the most important thing, the biggest challenge in healthcare is not lack of data. Because we talked about how do we create a value-based model. If a value-based model creates a success for the future? How can we replicate it? But still across the healthcare industry, 90 % of healthcare industry is fee-for-service model.

23:04It's not yet in a value-based model. And how do we now enable that? How do we now enable that so that there is right value that is created in the ecosystem? And people talk about is, do we have the right data or not? And I strongly believe we don't have lack of data. It is a lack of connectivity between the data, the systems and the many organizations that are there. And that proliferation and that disconnect is what is creating fragmented experiences for the members of the patients that we are serving. So one of the major focus for us is to how to enable and how to enable that at a national scale across the equation.

23:46Now, I told you what the BCBSA does. BCBSA is nothing but an interoperable organization for 33 blue plants. We create this interoperability standard. We operate at scale. We cover 121 and 3 Americans. We do that services today for all the blue plants. So now if you take a step back and say that is the exact problem this industry needs to get solved. That is the exact problem. So I don't believe there's anybody else that can solve that other than the Blues because we have done that at scale and we have solved it at scale. And there's a great proof point that's there that's solved at scale. And that's what excites me is with AI and the ability to have the Blues system nationally worked and locally operated.

24:33How can I take it and solve for the biggest issue in healthcare, which is how can we make sure that this interoperable ecosystem? There are many things in terms of that are beyond this one, Peter, in terms of incentives and payment regulations and all of that. I'm going to leave that aside for a second. I'm going to focus on what from a technology and innovation standpoint we can help drive. Because if this solves for it, a lot of that will settle automatically is how I believe. And so that's what we are focused on. That's what with AI is how can we make sure that this connectivity becomes ubiquitous.

25:07There are so many vendors that are operating today in this broken, fractured ecosystem that is actually not fixing healthcare, Peter. That's only fragmented even more. Because I wish the innovations of healthcare happened in the core of healthcare, Peter. But unfortunately, the innovations are happening in the places where the seams are broken. And that only divides the fragmentation more. So our focus is to make sure that we create innovation in the core of healthcare so that there is no seams that's broken out there.

25:42Peter High: And it strikes me, as you highlight, you have a unique opportunity given the scale in which you operate. And I must add, by the way, that this is one of your two most recent, this period of your career and the prior one at UHG. You have operated at extraordinary scale for quite some time now within this extraordinarily important sector of our economy. Talk a bit about now having worked for two different behemoths, the opportunity that presents itself when you have the ability to impact so many customers, ultimately patients, citizens, as a result of the strategic purchase that you've had. Right, Peter.

26:24And so I've been fortunate. I've been fortunate to work with some of the most talented teams throughout my career. And you picked the company and I've been so fortunate on it. So the blue system is built on independent plants that are deeply connected to the local communities. They serve. Many of the challenges the industry faces can be solved through collaboration, Peter. I genuinely believe that. And that's why so much of strategies are focused on shared foundation. How can we create a national level shared assets? How can we create an interoperable ecosystem so that two entities can interoperate in certain set of standards that can be applicable to both?

27:10How can we make sure that we can create a seamless exchange of information happening between multiple entities of healthcare so that we don't have to have organizations built because of lack of that standards or lack of that interoperability? That's what I feel with, you know, being my previous organization or now, but I'm fortunate to work with great people. I continue to work with great people. And that's what I feel the focus is for us to create the value at scale. And I always say that to my family and the people that I'm privileged to work with is, I want to sit in my dinner table many years from now, Peter, and tell my family, kids, grandkids, that the healthcare that they are enjoying today, I was part of the team that fixed it.

27:57That's the conversation I want to have.

28:01Peter High: That seems like a great vision, certainly. Thank you for sharing that, Moli. You mentioned earlier the necessity to think about AI responsibly. And I wonder if you could talk a little bit more about that as a philosophical point as well, when an algorithm can ultimately influence someone's healthcare experience. How do you think about baking in that responsible aspect? Because that's a very, very important topic for me personally and for the association and broader blues as well. Everybody that I talk to, it's a very important topic that's on top of mind. The way to control or the way to govern on this one, it starts with first your data.

28:41Your data governance gives you a great indication on how your AI governance is going to be. You first got to start with your data governance is how are you driving the data governance? What are the elements of the data governance you're trying to drive? In terms of access controls, in terms of how are you trying to, your ontologies and the semantic that you create on the data. And second, what we are trying to make sure that, you know, of course, there are many things in terms of bias controls and all the controls that we have in your governance will go through. And more importantly, what we are trying to do is to make sure that, you know, there's always human in the middle.

29:18There is always human in the middle when it comes to especially clinical decisions. When it comes to clinical decisions, there's always human in the middle in terms of making that. And then we continue to learn these processes. What I mean, we continue to learn these processes. The governance is never a one-time playbook. The governance is an extremely evolving playbook because what it is governing, it is never static. It changes every day, every minute. So the most important thing is how do we make sure that the governance process is not a rigid process, but the governance process is a very evolving process that understands how the model is changing, that understands how the solutions are changing, and so that we govern the right elements, not just have a playbook on it.

30:06Peter High: Very interesting. Prior to your time in healthcare, Moli, you spent time in manufacturing, in an industry obsessed with eliminating waste, standardizing processes, continuously improving quality. I wonder how much did your time there impact the way in which you think about the greatest impact of technology towards healthcare? I'm glad you asked that question, Peter. Yes, I do. I did start with manufacturing, and it's very simple in supply chain and manufacturing they teach you is value-added process, non-value-added process. Identify, lean it or eliminate it. It's a school that I was brought up in and that's a similar philosophy that I'm bringing into healthcare is what are the elements that need to get improved and what is the cycle time for that process If, you know, if it is seven days, can it be three days?

31:05Can it be three hours? What if it's be one hour or do we even need that process? That's a similar thinking that process improvement and process efficiency that healthcare also needs. And that's a similar mindset that I brought into healthcare as well.

31:21Peter High: Very interesting. Your authority is a bit different from a traditional enterprise CITO in as much as you're working across independent organizations. And I'd love to understand how you lead when influence matters more than control. Talk a little bit about that, if you would. When I talk about control, it's very fictitious in my mind, Peter, because the only person that I control is myself, nobody else. So, and so, you know, I'm coding there. And so the most important thing is how do you create? Again, as I said that, I'm a person that I anchor myself on the value that decision created, but the value I create.

32:02And the value that I create should be directly proportionate to how we are serving the members that we have privilege to serve. And the ways in which that can be achieved, it doesn't matter. It's an organizationally vertically integrated organization, or if it's a federation of organization that we need to collaborate and drive. Because healthcare needs this collaboration at the highest level for us to drive value because healthcare is never managed by one entity because you have providers, you have home workers, you have means-on-meals providers, you have locally operated Medicaid units, and then you have federal entities and regulators, and then you have providers and hospitals.

32:41So healthcare works on a collaborative unit. It never worked on an integrated ecosystem. So I always believed in collaboration and influencing, even when I had larger organizations. I always believed in making people buy into the vision and how do we drive change rather than dragging everybody through a direction.

33:06Peter High: So it's not as fundamentally different as one might expect. I like that. Great qualification to it. If we're having this conversation again, you know, in three or four years, I wonder, Moli, what do you see as being fundamentally different about the experience of being a Blue Cross Blue Shield member? What excites you in terms of some of the differences that are in the sort of not too distant future coming about? If I have to start with the end in mind, Peter, the blues are uniquely suited to lead through this defining moment. We have the scale that comes from covering one in three Americans that I've talked about while continuing to operate locally.

33:52And that's important. That's important because you've got to understand, make sure that the health care now and the health care for future is going to be delivered locally. So you've got to make sure that you don't understand. The combination of this national strength with local presence allows us to build big and bolder solutions. Now, there are a few aspects on a few years from now where, or many years from now, however you want to time box it, is the value-based care agenda that you talked about, that for every zip code that we have privileged to serve members there, We've got to make sure that the value-based care in whichever form that we are trying to drive drives more affordable health care for the people that we serve.

34:38The experience that we have made for them for health care is simpler. And we made every member that we have privileged to serve that health care is not sick care. And they come across health care in a meaningful way, not when they are the sickest most. And that's what the blues and the association that we are aiming for, how do we drive it? And today we have a great vehicle like AI. We have a great vehicle like technology. We have a great vehicle like data and interoperability. And even if that changes, pivots, we are willing to change and pivot as nimble as anybody would. Because our goal is not AI.

35:13Our goal is not just interoperability. Our goal is what I talked about is how do we create affordable healthcare for every people that we serve in every zip code across the country. That's our goal.

35:25Peter High: inspiring words certainly Moli uh finally I want to ask you uh what do you read or listen to to remain current that you might recommend to others are there any books or podcasts or blogs that you would suggest a podcast so I gotta say tech innovation podcast and I did you know I do I do listen to you know because for me the podcast has to be 30 minutes or below for me to engage myself. So as I do believe, without joking, I do look at your Tech Innovation podcast. Even recently, you had a couple of my friends with Verizon there on the call, and I didn't know that. And then AI Daily Brief is something that I look at, I listen to.

36:07It's a quick, because it's a 15 to 30 minutes on that one. And I understand what's happening on a daily basis, keep myself updated in the world. And another one that I really, really like, but it's a little lengthy, goes against is Dwarakish podcast, which is a little lengthy, but very meaningful. I could feed the technical side of me with a lot of inputs that he talks to scientists. He talks to model creators on that one. I do like it because yours provides an enterprise viewpoint, which I like, because it provides and enterprise viewpoint I like. And then I can talk about AI engineering on latent space.

36:47Latent space is another one that I listen to. And so these are the few of the podcasts, Peter.

36:54Peter High: Great suggestions, all. And thank you for the kind words, Moli. And certainly you're making this podcast that much better for the great conversation that we've had. Thank you so much for it. It's been an honor to speak with you today. Great. Thanks for having me in the podcast, Peter, and looking forward. Thank you. Appreciate it. Thanks for listening to Technovation. If you enjoyed this conversation, subscribe and leave a rating that helps more leaders find our podcast. Thank you. And I look forward to seeing you next time.