In this episode of Digital Health Talks, host Megan Antonelli, CEO of Health Impact Live, sits down with Mohan Nair, innovator, author, and former Chief Innovation Officer at Cambia Health Solutions, to explore what it truly means to stay human in an AI-obsessed world. Mohan's newest book, Unreachable: How Not to Lose Your Mind in an AI-Obsessed Era, is already an Amazon bestseller, and the conversation is as timely as it is thought-provoking.
In this episode, you'll hear about:
Mohan Nair, CEO, Emerge Inc
Megan Antonelli, Chief Executive Officer, HealthIMPACT Live
00:00:00 Intro: Welcome to Digital Health talks. Each week we meet with healthcare leaders making an immeasurable difference in equity, access and quality. Hear about what tech is worth investing in and what isn't as we focus on the innovations that deliver. Join Megan Antonelli, Jenny Sharp, and Shahid Shah for a weekly no BS deep dive on what's really making an impact in healthcare.
00:00:30 Megan Antonelli: Hi everybody. Welcome to Digital Health Talks. This is Megan Antonelli, CEO of Health Impact Live. And today I am joined by an old fabulous, wonderful friend and a builder, not an observer. He has done so much in healthcare and in business, and has been an ally and advisor to Health Impact for many, many years. In the past, he was Chief Innovation Officer at Cambia Health Solutions. He has launched six startups inside a nine point eight billion dollars enterprise. He's advised HHS. He's taught at Kellogg for many, many years, and now is a three time published author. And that's what we're here to talk to him about. Today is his newest book, unreachable and the The Urgent Blueprint. It is for staying Inside powered in an AI obsessed era. Mohan Nair, thank you for joining us today. Great to see you.
00:01:22 Mohan Nair: Oh, Megan, it's a wonderful pleasure. I can't wait for this conversation.
00:01:27 Megan Antonelli: You know, we were so thrilled to have you join us at Health Impact in February to talk about the book a little bit pre pre publish. And now it's been out there already on the bestseller list. But tell us before we get into the book specifics, tell us a little bit about your journey and you know how you got here.
00:01:44 Mohan Nair: Yeah. You mean how I got to the book story or the.
00:01:49 Megan Antonelli: The writing of the book and kind of your healthcare background in particular?
00:01:52 Mohan Nair: Yeah. Well, you know, particularly, I mean, relevant background, uh, healthcare is not really a it's not really a field. It's an ecosystem. Right? So whatever you bring to it, you can utilize if you have experience beyond it. So I've had, you know, thirty years of experience beyond health care. And in the course of that, I've applied most of those learnings and we can get into it a bit as to where those learnings applied. But fundamentally, I've been running companies, I've been installing companies in larger institutions so that we can create them from the inside out. And that experience really flowered itself with my relationship with Cambia Health Solutions, which is about eleven billion now. But when I was there, it was nine to eleven. And that growth cycle required us to really think about different ways in which we could optimize our margins. Be honest, because health care insurance margins are very low and sometimes below the number. So it's struggling, and we need to generate one hundred million dollars in margins to cover for probably one hundred million dollars in loss over the next ten years when I was there. Well, you can see it all come out now. Truly, all this stuff is going on in health care. Cambia is doing great from what I can see. But. But I left five years ago to really pursue what I truly wanted to do after my experiences there in launching nine companies with a small innovation team. But I also, for the first seven years was the chief marketing exec, and I ran the entire front end of all of regions, Blue Cross Blue Shield, and that gave me the experience and the understanding of the flow of money, the impact to community, the necessity to get closer to the consumer, and in some ways not just completely centered around institutional finance movements between different institutions, hospitals, physicians and patients. It was getting deeper and deeper as I started to learn more about more about our obligation to health care. And my obligation to health care has never left. It is still there because it's a human function. It is one where I am constantly in communication with CEOs at all levels of the healthcare ecosystem, and I'm learning from them what their most recent challenges are and also trying to help that process. Apart from being a tech guy, which you.
00:04:11 Megan Antonelli: Yeah. Well, I think it's really important to, to note, I mean, just going from sort of the chief marketing officer at Cambia to then being in charge of their innovations, you know, team and group and, and they were really one of the first healthcare organizations to begin, you know, innovating from within and investing in companies and starting startups. You know, it was really the model that, you know, now we see, you know, many health systems going towards and then independent venture firms, you know, kind of pulling together health systems from a venture side. But cambia was really early in that and, and had great success.
00:04:49 Mohan Nair: Yeah, we were enjoying that. It required to tax me with a lot of stuff as moving from chief marketing exec. Chief marketing exec was a gift they gave me to learn about the business, and I ran most of the front end of that eleven billion dollars company. So trying to understand how to market, how to sell, how to engage customers, and then all the digital assets were under me, too. I think they finally moved me to chief innovation officer because I kept inventing and innovating. They had to create a formalism. I remember my boss telling me, we have this new role for you called Chief Innovation Officer. I'm thinking, oh, is this a side job? You know, have I finally lost my career? Because we did transform it from from regions to Cambia. And that transformation created twenty five different separate businesses under one umbrella. And I didn't really want to continue being the chief marketing exec anyway. So when they offered me this chief innovation role, I grabbed it because it was a chance to work with a small group of team members that I could select. It's like any movie you've ever seen. You build your own team and you select them one at a time. And I did do that. I was roaming around the company, roaming around the marketplace, trying to isolate ten to eleven people with a limited budget so that we had constraints to kind of build the future. And that's why idea management started to pick up how to manage ideas. The whole idea of design thinking came into frame. This was two thousand and four. Megan. Think about.
00:06:15 Megan Antonelli: It. I know, I mean, you know, I remember and I remember you sort of getting that title and it being one of the earlier, you know, if not, you know, perhaps the first chief innovation officer at a health care organization. So it's, you know, and having watched that in the last twenty, twenty years in terms of how that's evolved, you know, and the impact of the way health care is looked at and adopted innovation. And I think it just brings us to a really amazing place right now. And as we look at AI and what that is doing to the innovation cycle within healthcare and also to individuals. So that's and that's what I love about unreachable and, you know, sort of the tagline, how not to lose your mind in an AI obsessed era is it is it approaches it from an individual perspective as well. So tell us a little bit about that and tell us a little bit about the book. And then we can kind of get into where it really kind of speaks to the healthcare innovation person within.
00:07:13 Mohan Nair: Yeah, I tell you, you know, so gratifying, Megan, that you've noticed and you did it multiple times that this book was directed not to the governance of AI at a large scale, although it can be used there, but it is applied mostly to individuals. So instead of working on the boardroom book that every board will buy, I think it's going to be a dining room table book that every board member will buy anyway, because it's going to be both longitudinally affecting the dining table as well as the boardroom table. So my target was really to get deep with what individuals have to go through in understanding this, the concept all the way to understanding how they can play their part. When the the tidal wave of AI gen AI starts to hit the shores of their mind. What happens? Right? How do you know where your island is? How do you know where your job is? How do you know where your family is going to survive through this? Because it comes in ubiquitously and it reminds me of the Apple Macintosh, if you remember, that was denied by corporate America for many years. They kept saying, it's a toy, it's a pong playing thing. Let's not worry about it. And IT organizations banned it from the IT infrastructure. And then it started to seep in because the designers wanted it. And when the designers wanted it and were becoming more creative, all of a sudden doors started to open and now it's everywhere. So the same thing is happening in AI. It starts at the dining table. It will spread at the dining table. So to try and organize it the other way around in a top down way is, I think, naive. And I think that what we have to understand is individual restraint and governance will manage corporate governance and restraint. If we don't make those two meet, we fall apart. So my book, unreachable was to kind of tempt individuals at all levels in the institution to really take hold of their, their agency in terms of what they can bring to the AI world. And I noticed that there were tendencies in that world to bifurcate. One set of people tend to just be AI afraid, and another set tend to be AI obsessed. Neither are good, but they both seem to be the ones that are suddenly in the battlefield of AI. So we can get into what those definitions are. But I found that you can feel it. I don't need to define it. You can feel it around you. People are either into it or they're going to. They're either Skynet or they're Battlestar. They're Battlestar Galactica or or they're Star Trek, right? It's one of those two movies that you could watch. You could figure out which line they are following in terms of thinking that's reinforcing the way our culture is forming into a bifurcated society, and we can't let that happen. We need to bring it into something a little bit more empowering and driven with agency to individuals. And hence, that's why I wrote the book unreachable.
00:10:21 Megan Antonelli: Yeah. No, and I think that that, that sort of the, the fast adopter that, you know, we all want to identify with, you know, I, I want to be a fast adopter. I want, you know, I want to be there, but you have to do it sort of the, you know, recognition and you talk about sort of cognitive atrophy, right? And I mean, I feel it myself. And I, you know, I mean, we would say, I would say it with Google, you know, forget, you know, before you know it, I need my, I need my Google search to answer my questions. I can't remember things as well anymore. And now it's not just memory, it's creating. Right? We use it so much to create and if we become dependent on it. So talk a little bit about that and what you talk about as cognitive atrophy in the book and what that means. As you know, that's.
00:11:05 Mohan Nair: A common I mean, when I started to research this five years ago, I hadn't even surfaced. Right. But in the course of me studying innovation, right, the umbrella of innovation and how innovation is getting to be so much of a process. Now everybody's talking about it. There's always different ways to idea manage many ways to create companies, entrepreneurship. All that noise is now in the belly of the snake of healthcare, right? It's right there. And everyone thinks they know how to do it. Everyone's an expert on innovation now, and the word innovation has somewhat lost its meaning. So has disruption, the word disruption. Um, so I decided to pen a piece of work that would have some timelessness to it. That spoke to my experience of the last forty years and innovating in tech as well as in health care, and could also collect the innovative ideas that others had generated through the years. Those much smarter than me, frankly. So I try to put that all into a frame. But then came this gen AI thing that in the course of me writing and researching, I could see very clearly because my background is in AI. In the past I was in it in eighty two, believe it or not. Looking at it now, I had a real strange sense that I need to throw a Frisbee when the dog hasn't even arrived. And so three or four years ago, I started writing this and researching this where I could throw a Frisbee in a direction which required me to commit. And what was the the anchor of that? Now, if I told you that AI is great, and here's all about AI. It'd be just like any other storyline I needed to share with you both. The pleasure of AI and the pain of AI. And I wanted to show a paradox, which is a relevant paradox that would happen in the dining table. The more I use tech, the less skilled I am because I don't have to do that spreadsheet, so I don't have to count. If I don't have to count, I don't have to think. Those things started to bug me. So I did some extensive research. Meta research, not primary on that subject and found the word atrophy. Cognitive atrophy. And then I found research that showed that an over obsessed usage of anything causes atrophy. Mental atrophy functions because you don't use the muscle of your brain. So let's think about it. Um, I was at a hotel recently and I left the hotel and I asked the bellman directions and he said, I don't know. I don't have my phone with me. Well, last time I checked. The bellman gives you directions. Can't do it anymore because that part of his brain is shrunk. He's so reliant on the machine. That's just a micro example of how we obsess. Now, what does obsess mean before I go into atrophy? Do you mind if I go into obsession a bit? Obsession is defined by me in the clear terms of you go for the convenient. You just go for the convenient. Park your car really close so that you can walk in the mall, you know. So if your mental model is to park your car really close, you'll spend an hour parking your car trying to find a spot near the mall. But you do it because that small walk you don't want to take, and that small walk is the walk that you have to take as a cognitive, insightful person. But we don't we don't exercise ourselves. That's one. Number two is you go for the first opinion using the machine. So you ask the machine, what do you think of blah, blah, blah. Here's all the data. People brag about it nowadays. I put everything into the LM, I gave it my book, I gave it my stories, and it told me who I really am and what I should think. It gave me the first opinion on my paper. It gave me a good start because it's hard for me to start. Well, those kinds of things are the beginnings of obsessive behavior, where you give up your first opinion and finally you go for good enough. You know, some of these drawings you see on the web done by machines are horrible, right? I mean, you can notice the six fingers, right? But people are still doing it. They're doing videos that are embarrassing. They think it's art form. So now everyone can be an artist, a painter, a philosopher, a poet. All they have to do is pay and prompt. Well, that is the beginning of an obsessive society. Started with an obsessive individual not knowing that they are being obsessive. Now, if you think of any drug that people addicted to, that's their behavior pattern to It's the same three factors about addicting yourself to something, and most of the time they feel really good that they emaciate in their brain and mind and body, right? So we are in the early phases of what I think is true. So atrophy is a function of those three elements being utilized obsessively. You can I'm being a nutrition label, not a warning label. So I'm asking you to take that sugar less than normal. Try not to overdo it and watch it. I'm not saying don't do it. I love AI, I'm an AI person myself. I just dream of it, work with it. So it's really what happens to your brain when you don't fire as much across the multiple lobes of your brain. When you're writing a paper, when you're in college, when you're testing yourself, what happens to you? Does it shrink? Does it stay the same? All the facts that I have read imply yes, you do shrink and that that shrinkage is pretty significant. and it happens pretty quickly. So I am sending people a nutrition label on that right now.
00:16:46 Megan Antonelli: Right. Which I love. And I, and I think you make the point that, you know, the atrophy, the fear and the obsession are both, you know, that there's atrophy or slowness that that happens. So we have to find the balance between the two, which of course in healthcare, you know, we talk about a lot, you know, balancing the risk and the reward, right? Of technology in general. And, and we know from the very beginning of, of the discussion of technology to now what has evolved to AI, this discussion of, you know, is it going to replace physicians? Is it going to replace clinicians? And, and I think we're all a bit past that, but we are in this sort of, you know, almost a trough of disillusionment around what is it going to replace and how do we even begin to parse out what it does do? well and safely.
00:17:41 Mohan Nair: Controversially speaking, you know, people ask me, well, come on, you know, uh, scribing automatic scribing is very useful. Populating the chart notes really quickly makes the doctor efficient. Are you telling us that, Mohan, you should be careful about that. And you know I can have a choice, right? I have to make a choice. If I say yes, be careful. Nobody's going to hire me and ask my advice. If I say no, I'd be lying. Because to be honest with you, to myself, I think chart notes, population scribes are wonderful. If you're a thirty year physician, you now don't have to practice chart noting. But if you're a first year resident, you better practice chart noting. Because if you don't know the art of the encumbrance of the inconvenient learning, because as you're charting, you're actually diagnosing. And that art form of pen to paper is lost. So what do new doctors become? What do new surgeons become when they don't understand their creative art form of surgery? They only understand the mechanics of surgery. So, I mean, I'm joking around and I'd say, you know, a karate kid would not have happened if it was for Gen AI, right? If you had Gen AI, he would just go to the web and figure the moves out and fight his own fight at home and get counseling from a clot or some other technology. He wouldn't have met Miyagi and Miyagi asked him to paint the wall and scrub the floor. Miyagi knew the relationship between that inconvenient learning and the art of being the Karate Kid. And that's the beauty of it, right? You realize what you were doing really has major implications. We have not gone deep into the work of a physician, the work of a nurse, the work of an insurance person who is doing a spreadsheet, but now using machines to replicate that thinking. Yeah, you can be above average, But can you be unreachable? No. To be unreachable, you have to work through all of that to be inconveniently learning, finding your aha and finding the first opinion. And if you don't do those three things, the chances are you're suboptimal in the long run.
00:19:54 Megan Antonelli: Right. I mean, that message of the art of inconvenient learning is, I think, one that applies to everything health care, education. I know you speak to a lot of, um, you know, folks on the education side too about what this means. And I think when I think about, you know, we've been talking about it for, you know, some time now, sort of the impact on the workforce and what it looks like. Um, but it, it also starts with the impact on education, right? And how we're going to change how we educate clinicians in this context of practicing with AI. You know.
00:20:29 Mohan Nair: I had a patient who, I mean, I had a patient, I know a patient who had a cancer diagnosis. He found out the cancer diagnosis from the chart notes. Because it comes out, the results show carcinogens. So he found that out. I never got a call from his physician for a week. And then he finally met the physician. And the physician came in and said, by now you probably read that you have cancer. I mean, that's not the model, but it exists. I can tell you from experiences that's that's happening. People are forgetting that information is not the same as touching of hands, the placing of hands on the patient. So as long as we understand that compassion is very different than comprehension, and that is very different than computation, we know the difference between the three. We're going to be a great health care economy. If not, I think we will lose so much in the process. So guarding against this cognitive loss, the seeking of convenience over efficiency and the ability to really have the time to engage is what we are losing now in health care. It is really going. And then we say personalization and individualism and, well, that personalization we think tech is going to replace. I challenge that. I think we have to understand what AI enabled and insight driven means. And I coined those phrases from combinations of other people's great ideas, but understanding AI enablement and then understanding what is insight over just general information flow, uh, is where I think the health care system ought to be going because people don't want to go see a doctor for information anymore. We can get that. We want the insight driven by the years of work that a physician has gone through with multiple patients that are like me or others, to come up with an insightful solution to a pending urgent problem that they're all facing. Information flow is. I think AI can handle that really well. There's no more need for that. Even contextually ready information for a person with a different context and another person with a different context. I think AI will get there. It'll replace things that are process oriented, that are understood by others. The knowledge you have will be replaced. The wisdom you bring to the instinctive way you do work will never, ever find a replacement. It'll just not happen. The question is, how much of your career is machine readable? If your career is machine readable, your machine replaceable. So I can't help that. That's the way life is. But if you think that you have something that is machine unreadable, that you bring value to the pro, to the process that is uniquely yours, that solves the problem, not just gives an answer. Then, then you, you really got it right.
00:23:30 Megan Antonelli: I mean, you talk about the aha moment and sort of the that how that's kind of core to the framework and, and, and in terms of how both organizations and individuals should be thinking about, about this in terms of like with, um, healthcare leaders kind of creating the, the circumstance for that, right? I mean, we're so focused, you know, on using the technology to drive value or drive a return on the investment, right. You know, and it really does a lot of the time in healthcare come down to money. And, and to some degree, it's also been where AI has focused the technology companies want to focus there, right? It's the lower risk, it's less less patient facing and drives more resources and resources. Ultimately, let's hope to some degree get freed up to give better patient care. But when it comes to, you know, what are we really what are we really going to use this for, to change healthcare to make it better? What you know, how are you guiding some of your, you know, uh, you know, C-suite colleagues on the healthcare side to think about this.
00:24:36 Mohan Nair: They are all struggling with it. And I'm glad they are, because I want them to inconveniently learn this, too. I don't think it's going to be easy. Anyone who calls themselves an expert in this field is only one page ahead of you. So I my third book, actually, this is my fourth book, FYI, my third book was on strategic decision making, and it was fundamentally about what to deal with when the world is unknown, unknown, more than known. And I wrote that in twenty ten, believe it or not, it's still applicable now because the more of the unknown unknowns have happened. In other words, AI is an unknown unknown. We do not know the impact, the size of the impact of AI. We just know it's big. We do not know the incidence of it. We don't know when it's going to happen. And right now it's happening at a daily basis where change is occurring. So if you rely your backplane of your thinking on AI, you're going to be fluttering around everywhere. You'll be chasing your own tail. So what is the thing you anchor on that truly as an institution, you necessarily have to engage on and in a weird way, and in an almost obvious way, it's your values as a business and how you take those values into actual day to day operating table activities, how your people actually perform. Now, in my prior life, I spent seven years running a software company that had seventy six percent market share in the area of cost and performance management. So I was dealing with a field called activity based costing. And in that field, the main study was operating measures usually do not tell you what people are doing. They only tell you the outcomes of it. They're mostly lagging indicators. So where are the leading indicators? If you walk down the hallway and people are doing work that is useless, you're probably spending money, right? It's kind of obvious. If people are doing work and are really justifying their work and the work is not necessarily value added, you're probably spending money. So if you can fire people, you can lay off people, but the work get absorbed by other people. So if you don't focus on the work itself, the value added and non-value added work, you will always be shrinking, growing, shrinking, growing. Because the work as a whole is being absorbed and dissolved depending on whoever turns up. So focus on the activities. If you want to apply AI to anything, apply to the necessary activities. Removing the unnecessary activities. Caution label on this one instead of nutrition label the caution label is don't go remove non financially justifiable activities. Be very careful about that. It's not financially justifiable that the doctor called the patient when he had cancer, but it was absolutely justifiable in the values you want to deliver. And you're finally your Medicare score because that patient's going to give you a bad Medicare score. And then it's going to be seventy million for every star point that you lose. And you'll ask yourself why we did everything right. Well, one thing you didn't do right, which was that phone call. So I ask CEOs constantly to really align their activities to the values. So it's not a value proposition argument which look, we've beat that to the ground. What's your value proposition? How do you measure it? It's really your values proposition that you then use AI to enable. Now I have customer service groups in healthcare institutions that are now only solving the most complex problems, because all the basic problems are being solved by generative AI. You can get on the line and you can solve it. You can send people to the web. They'll do it, they'll do it. And now you're dealing with only the really serious problem. You know what's happening with the customer service people. We're only solving every day the most serious problems. They're getting depressed. They don't have any wins because most of the health care problems are long term, emotionally charged problems. So you've got yourself now you've got a group of customer service people that are fully engaged, like a nine one nine one one calls every day is edgy. And then you have to add on top of that facilities to calm them down, give them good training, meditation classes, you know, give them you're now adding even more value in to them. And next thing you know, the costs are the same. So really give them short wins. So the art of taking away the basics, the convenient learning opportunities are removed. They have no more inconvenient learning is not the way a CEO should think. Don't think efficiency is the answer to cost and performance in health care. We've tried that already. And where has it got us got us to four trillion dollars still in costs. So if you want to reduce costs, we have to think of it. Applying AI in a very strategic, directed, contained and successful beyond the pilot phase. We have one hundred thousand pilots flying around and nobody's getting anywhere. That gap is occurring today. So my my constant advice is CEO, you better think about your inconvenient learning. You better start showing the example of how you become an instrument of enablement for AI. And exactly, you decide what your dining table looks like as well as your boardroom table. And if you don't know that, just telling people, those who survive will be the ones who learn AI better, the rest of you have to go. That kind of nonsense is rather boring for me. And frankly, every fact I've learned and every fiction that I'm dreaming of doesn't fit that profile.
00:30:24 Megan Antonelli: Well, I think, you know, when you say when you talk about the convenient learning and then to think about, you know, those easy wins that you're eliminating the easy wins, you're eliminating the, you know, the learning process, you know, this, this sort of balance that you're kind of, you know, by applying AI to, you know, sort of every sort of easy solution that you eliminate that. And I think about, you know, think about my kids and handwriting and learning script and, you know, and that that's part of spelling and it's ultimately part of reading and, and writing and, and that whole process that we've, we have just eliminated. Right. And without, um, you know, thinking about the unintended consequences of all of it. And we are rushing, there is no question in both healthcare and across as individuals to, to kind of adopt. But what is that? You know, what, what are we leaving out? And what are we leaving behind? Which of course, is a lot of what you talk about, you know, in the book. Um, so let's talk a little bit, putting on your chief innovation officer hat, right. And talk about the what we've seen in healthcare innovation over the years and what that means now, because I think we're seeing a little bit of, um, kind of fewer, fewer chief innovation officers, more chief AI officers, you know, the innovation groups within healthcare are becoming the venture groups, if you will. They're the, you know, sort of finance investor groups and there's less innovation groups and so on. A broad spectrum innovation landscape has changed a bit within healthcare. I think we're also at this build versus buy. I mean, not that everybody in healthcare is going to be sitting and vibe coding, but, you know, they can get into these discussions. And so I'd love to hear your thoughts on what that looks like and what it needs to look like. Because if we're putting the, you know, sort of people in, people responsible for AI, you know, in the innovation role, if you will, or supplanting that with that. Um, what does that mean? You know what, what is, what does it mean for the, the kind of pipeline and, and solution solving, which is what I, you know, that's what I, I think of when I think of innovation, that's what meant that's what innovation should be to me is problem solving in healthcare. Um, we're not looking for the latest, you know, it's just fix the fix, fix how messed up it, right it is right now and make it better. And that's what your job is. As you know, from an innovation standpoint, how is that changing or how is AI? How should I change that?
00:33:01 Mohan Nair: Well, um, when I received the role of chief innovation officer, I really didn't know what that role was. I had to define it. And there wasn't much, you know, job descriptions or things like you have now. And now you pretty much know that they are fit into a particular set of choices. Some people in the innovation role are actually portfolio managers. They collect ideas, they enable a process. They help the departments really achieve their goals by being a sort of a they're off balance sheet, right? And when you're off balance sheet, you got to change jobs every three years, right? Because every three years somebody comes along and says, why are we having that person? And then they always come out looking good because they'll start a consulting company or run off and do something else or join another organization. Once a chief innovation officer, twenty four percent of chief innovation officers report to the CEO. I was lucky enough to be one of them. When you're in that role, you have a moral obligation and a fiduciary obligation to ensure the functionality of the business meets the functionality of the customer need. There's no more playing around. I'm not implying that people who report to the chief marketing officer or the chief engineering officer, or whoever you report to has the same as has less or the same Importance, but they are subject to operating pleasures and as well as pleasures as well as budgets. So that doesn't work for me. I mean, if you're not reporting to the CEO as an innovation officer, you should ask yourself whether you have a direct line to the CEO to ensure the consistency across the entire business units you're working with, because you'll end up looking like an engineering officer or a marketing officer because you report to them. So I had a role where I had ten people and all of them were business designers, data DJ's. I used to call them. People would provide DJ at Instantaneous Power. I could run into a meeting and they would provide the data instantaneously while I'm doing design. We designed companies and businesses and looked at over three thousand ideas from employees, and turned most of those into operating impactful things within ninety days, or we threw them away, or we stored them in the archive. We recycled stories on a constant basis. We were a storytelling group, but not a design thinking storytelling group. We understood the tool, but we did not become the tool. And that happens with a lot of design thinking groups. They end up becoming advocates for their own design thinking methodology. So you don't need many hammers looking for nails in corporations. We have them with TQM. We had them in the old days. We have it now with innovation. We need business designers who can see the beyond the fog and can produce the answers to questions that have yet arrived. That's the art of throwing a Frisbee. The dog doesn't exist yet, and you're looking at five years out all the time because you're in a healthcare business where actuaries look out five years. So you need to build a model that is very exciting, that looks at the world differently. But apart from saying, how do I fit into that world? It's really, how do I create that world? How do I create the idea, the insight, and the scaffolding so others can climb? Example. Um, we looked at a social network in two thousand and four for healthcare. By the time we were done, people were telling us with torches, chasing us out of the building, you're going to get lawsuits, innovation companies, insurance companies, having a social network. That's like inviting people to come after you. Nothing of that nature happened. We had one point six to two million members on the social network. We created a media company. It had at that time, in two thousand and four had movie making quality. We made documentaries, we produced, uh, interviews, we did podcasts. We were podcasting before podcasting occurred. All that was created from the minds of the genius of the people around us who could just close their thoughts and open it to the future. That became a very successful play for us competitively. Yeah. Was there was there people filing lawsuits? No. Was there people yelling at us? Yes, but not that much. They were talking about their kneecaps. They were wondering about depression. You know, what are the top three things were in the social network over a five year period? Divorce, recovery, Relationship with children and then their own mental health. Those were the key ones. So when you watch that, you start to realize your member base is actually talking about things that are really substantive to their lives, and you could feed your products and services to help them, not to manipulate them. Right. So that's the role of a chief innovation officer. See the future, build the scaffolding. And AI officer is dangerously close to being a hammer looking for a nail. They're going to be highly trained depth first in the AI function. They're going to be less domain knowledgeable. And even if you put that in the senior officer ranks, you have to test that AI officer to ensure that the respect for the domain and the values driven by the domain have to be replicated. They can challenge it, they should challenge it, but they have to not challenge the fundamental core premises that drive health care to what it is today and what the social commitment we have. So AI can be you can build anything in AI, I. But you have to understand the necessary domain that made it happen. Starbucks had brought an efficient leader into the play many years ago. That person hermetically sealed all the coffee in all the retail stores. And Howard Schultz could not smell coffee when he walked into the stores. It didn't work. It was highly efficient. Supply chain was successful. But there was no smell of coffee. And that's the thing. You don't want AI officers to lose. They cannot lose that. They will come in big and bold. And my best friends are AI officers now. But combining the innovation role with the AI officer role is dangerously close to realizing that you don't need an innovation officer. But that's not because you didn't have a great innovation officer prior. You just didn't give that person enough room to kind of design the business structure that's needed. Medicare pricing is dropping reimbursement is falling. Individual to group margins are crashing. The negotiations between individual insurance companies and hospitals are becoming more tenuous. Hospitals are not able to function because they've relied on commercial business to support their Medicaid business. Now the commercial business is subzero, so they're relying on med advantage. But the med advances star ratings affect you. Not only that, the ability to handle med advantage now with pricing structures changing is reducing your margins. Where are you going to get your survival dollars? How are you going to function? Those are not AI problems. Those are real business model problems. And if somebody says, I can make nurses better, that's not the real problem. You can, but it's not in your zero based budget where you want to put your artificial intelligence solutions. So my field of work is to help others understand that the dining room is still the place to be. That AI applied to the dining room will automatically apply to the boardroom. If you know how to play that very successfully, and you have to be shrewd about it. Now, in terms of everyone being an enterprise, every person in the health care systems, they think now they can be their own consultant. They can also be their own innovation officer. They can also be the one person enterprise. I had a CEO tell me who has only five direct reports. He's running a significant business and he said, I hate humans because they're so boringly, you know, problematic. I just use AI agents. Now I have five directs, and I want to empower my directs to create agent technology. And I get updated every day and night, and I can get all the data I want. And he's looking at me and saying, if your book is telling me this, I agree with you book. If your book is saying that everyone has a right and and to be AI enabled and insight enhanced. Then I think it's wrong. It's completely wrong. And we had a long walking argument about that. Yeah. That is the world we live in now.
00:41:24 Megan Antonelli: Yeah. No I well, and I think what you're, I mean, what I'm hearing and what I think that, you know, there's this element of innovation that is about knowing the future and also understanding the past. And AI is an incredible predictive tool based on the past, but without a, you know, the human insights that are needed to predict the future. Realistically, you can't necessarily do the right thing. You'll just keep doing what you've been doing before, or you will.
00:41:51 Mohan Nair: Do what other people have done before. Because the large language model that you're using.
00:41:56 Megan Antonelli: Right, which is completely counter.
00:41:58 Mohan Nair: Yeah. And it's also, by the way, AI, gen AI is combinatorially powerful, like drug manufacture. I mean, OpenAI just signed a deal with, I think no. And that's because they want to do drug design. They'll do a great job of it. I think that they will find new and unused components that can be reused into the drug arena, and that could take their life to a whole new level. But the fact of designing the next original drug combination you may leave to the machine, but the fact of designing the next new drug is going to be found somewhere else.
00:42:33 Megan Antonelli: It'll be also an example of using AI for the for the problem is, you know, I mean, they're saying mounjaro and and the Lilly product has gotten market share. Well, it's gotten the market share because it's more effective. Sorry, Novo Nordisk and all my friends there, but it's more effective therefore. So you can throw any AI tool you want at it. But that's not going to change that, right? So we're throwing the tools, using the tools. But if we don't fix the fundamental problems, you know, and innovate better through to fix those problems, the AI is only going to, you know, give us the same, same results. Right.
00:43:09 Mohan Nair: I mentioned to you about activity based costing and how if you fire people, the activity still remains. The power of that is if you look at the activities that truly you need to perform now, don't look at the jobs, but what activities make you AI unreachable? You know, and those are not the repeatable, scalable ones. Those the machine will do, the documentable ones. Those are seldom. So the intangible set of activities that you perform that create the solution space that nobody else can create. So think of yourself as a master chef. The ingredients you have are the same. Everyone has the same ingredients. So if you try to protect IP by protecting the ingredients, you know hardly will work. But it's that final touch, that chef's touch that generates the beautiful, undeniable taste that is found. And people go, how? How did that happen? I mean, how did it happen now? I always kid around, right? Megan, you can come to my house for turkey dinner at Thanksgiving. I guarantee you will leave quickly. Right. But I could go to a master chef. The person uses the same ingredients, same ingredients, same proportionality. And it tastes beautiful. What is that difference? And we always like to mechanize our jobs, but the patient relationship between the equity of the relationship between patient and physician and nurse and caregiver, not repeatable and scalable. It's fundamentally uniquely driven around stories. It's driven around stories. So let me share with you one quick story. I went to my mother's memorial in New Zealand. Right. It was so horribly done. It was beautiful, right? Because there were eleven people who died and the nurse was the guitar player. No, the laundry person was a guitar player. The nurse sang and they sang, you know, stand by me in off key. Right. And they Each one of us went up and talked about our loved ones who had passed. I had four minutes. I stand up and talk about it. Everyone in the room is crying, including all the nurses that took care of my mother. Right? Tell me you can AI that one.
00:45:20 Megan Antonelli: Right?
00:45:21 Mohan Nair: Do I care that they sang it off key? I, in fact, I love they sang it off key because they sang right at the end. We took balloons and helium balloons. Now more expensive than ever, but helium balloons. And then we took it to the sky and all the nurses were out there. And when they talked about the patients that didn't have family members who passed, they couldn't finish reading their scripted communication. And I know that scripted communication was written with gen AI help. They put it to the GPT because it sounded so profound. Right?
00:45:52 Megan Antonelli: Right.
00:45:53 Mohan Nair: But they couldn't finish. That's the thing that is unreachable by AI. That's just an example. The commitment they had to the patient that traversed everything. Now, in the back of the room is the general manager of the retirement village. He's balling. He's balling at all levels.
00:46:13 Megan Antonelli: Mhm.
00:46:14 Mohan Nair: And one of the persons I invited to come with me, one of my close friends said to me, this is how I want to die. And that is.
00:46:24 Megan Antonelli: No. But that's it. It is about the humanity of it. And if there's no place where it's more important than health care. Right. And so I think that's why these conversations are, you know, resonate so much and the thoughtfulness that's required and the, and the, the time that we are taking to think of how we do this is so important. And that's, you know, sometimes I get a little concerned as I'm at these conferences and it's just adopt. Adopt, adopt. Go go, go. When, you know, it really is something that while the power is there, the promise is there. If we don't take it and be about how we adopt it. Um, you know, we lose that humanity. So I think the book is so important and, uh, you know, I'm so glad that you wrote it and that we're able to kind of amplify that, tell our folks, I know it's available everywhere now, tell our folks where they can, where they can get it.
00:47:19 Mohan Nair: Well, first of all, thank you, Megan, for giving me an opportunity, a platform that I totally respect and always respected the platform you've created because it has the balance of what we just talked about, you know, the efficiency, the effectiveness, and also the compassion required to really win in the markets. Um, I made sure the book was available to as many people as possible to get to the dining table. So I didn't make a hard card bound. I made a paperback and Kindle and ebooks. So it's very inexpensive, so it's easily accessible to everyone. Um, I'll make my money when it's turned into a movie and then, you know, that's when I make my money. Just kidding. But, but it's available on Amazon. It's available everywhere. It's an Amazon bestseller already, which is very gratifying. But any bookstore will not carry the book. You'll have to tell them to buy it, because I decided not to put it in bookstores. I prefer to put it in the the web world so that you can access it and get it delivered to your home. And so every Barnes and Nobles, every bookstore will have it. The, the actual bookstores that will also have it. If you just call them and ask them to order it, it'll be fine. If you want to go pick it up there. But the bottom line is connect with me on LinkedIn. Join a movement with me. I am seriously trying to be a nutrition label for people who are indexing over on the left or the right. They need to be in the middle, really focused on what their true, insightful self is and bringing that out. I mean, insight is known as a sudden comprehension or realization that solves a problem. And you know what? That happens all the time if you don't notice it. Well, you just ignore it every time you get an idea. That's because you don't build. And now our cognition is threatened. I think our cognition will be threatened more and more. And if you're worried about you and you are forty years older than normal, and like me and you're beyond your years, I'm not worried about AI taking my brain. Health and age is taking my brain anyway, so and pure laziness. So I'm not worried about that. The problem is the younger people who have not formed their cognitive agency yet when they overuse AI, their degradation is higher. So our next generation or generations to follow are what you should be concerned about as a CEO. Make sure that cognitive strategy is to ensure that they use their brain as well as they use the machine, right? So again, I hope this helps you and helps.
00:49:49 Megan Antonelli: Oh, it's so helpful. And I think it will be so helpful and insightful to all of our, our audience members. And I, you know, just that idea behind, you know, the inconvenient learning and the importance of that. Um, you know, which in healthcare, uh, can't be overstated for sure. So thank you so much. It's always such a pleasure. I look forward to our next conversation. Um, to those, our audience please. Um, unreachable, how not to lose your Mind and an AI obsessed era, um, available on Amazon and Barnes and noble dot com and, um, get out there, read it. And then, you know, we want to hear what you have to say. And if this episode has given you something to think about, subscribe to digital health talks and follow us on, on your platform. And we will be back next week to have more conversations. Don't miss what's next. This is Megan Antonelli signing off.
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