Tailoring AI Strategy for Healthcare Leaders: Product Adoption and AI Literacy

Ritu Chakrawarty: It is because people are not really productive for my body. Like uh, it is not in the flow. It is not easy for them to use it. Sometimes it is just the test it is for every company that I have a treat for you all.

Chris Hutchins: Uh good on location here at Plenty of Hollywood in Las Vegas for the Put Data First Conference. We are having a blast, and today I'm really excited to be joined by Ritu. Uh welcome to the Signal Room.

Ritu Chakrawarty: Thank you.

Chris Hutchins: Thank you so much for agreeing to just sit down and have a conversation. I think it's it's been remarkable how much passion and enthusiasm we're running into in this room over the last couple of days. And getting to meet you has been wonderful and meeting so many different people, it just seems like we're at a really different point because when you're at the beginnings of a transformation of any kind, people tend to be a little tentative and kind of laid back, kind of waiting to see how this is going to play out. But everyone's leaning in and they're so excited. I so just maybe just to start with, just tell me a little bit about your background. I mean, I I know you're doing AI strategy and you know, pretty cool stuff, but I don't think I've seen you without a smile on your face since since uh you I saw you yesterday for the first time. So you clearly are passionate about what you're doing. Love to understand what's behind all that.

Ritu Chakrawarty: Absolutely. First of all, thank you so much for having me here. Uh I am glad that I could make it. Uh I was kind of skeptical that should I be going it, like taking two days off in one day too, I'll say uh it's tough. But I think I made a right disease in three years. Uh there was so much in the room in terms of energy to learn that like uh from each other, uh how things are happening. But starting with my background, so I'm in this industry, I would say uh almost two decades, so very long. My uh degree, I would say, of uh I'm an engineer, and uh first the taste of ITI, I would say, was my my research, which I did uh in neural later. And during that time it was very specific use cases. So, how do you do the digital signal processing? That was my uh PhD paper uh in my engineering. And then uh that was also a time when uh software was uh taking shape. Right. So started my career as an analyst, and from there, uh uh I would say GI, it is like uh almost 12 years. Uh during the time like I left that neural uh engine and that uh neural processing, but then uh came big data, and that was just to talk of the town since then. I was part of uh execution strategy in consulting for applying intelligence, did my startup for a while, and then I realized that okay, I should be an uh enterprise doing something more in agenda to BI space. So now for every commercial, I'm on uh AI product strategy, putting together the AI product, which is our commercial.

Chris Hutchins: That's exciting. How are you finding it? The challenge that I've I've been running into because I've been on the chief data officer side in the healthcare sector. There's so many solutions coming at us from every direction. Generally, they they are addressing a really small part of a very large gap that we try to fill. And the difficulties with that are primarily financial ones because you can't afford to have 10 things to fill one gap, right? And then sometimes it's not even the right gap that we're trying to fill. So it's it's complicated, but you know, in your your job, what what you have to think about is that not only is it the right solution, but strategically, when do you do certain things and when is it me going to be meaningful? When is adoption going to be a problem? When is it a risk for a compliance issue? So many other, so many things that go into what you're responsible for. I just love to hear what your approach is.

Ritu Chakrawarty: Right, absolutely. And as you said, that uh there's so many solutions. So every day you see face something else, and then you wake up and you find another exunction in the market. So um, for a person like me who is responsible for putting together what the product strategy looks like, right? Finding how should we clone what is already in the market, or you uh like so that is the build part, or you just latch on on something which is already there and build on that. So my uh and and this is a build versus buy decision, is a very difficult. The way I approach is the starting from the value, what we are trying to achieve, where is the value lies? Yes, it's very easy, like looks like very complex, but looking from that, okay, where where it is gonna increase our revenue, where it is gonna give us a cost save. Starting from that angle, then going like like a double uh take a demo and say, okay, which are the areas where you can have these values quickly achievable? Right. So that low-hanging fruit. And then again, that I I applied litmus test for that. Very simple litmus test. Anything where AI could help us before even finding that which is the right solution. First of all, is it an AI solution or so that it comes to like do I have a digital data? So if that this information is digital or not, can I verify? If I can very because if you can't trust it, you can't use it, you can't adopt it. So this is the my first test for adoption. So once I have that, like a very quick list, let must test on the viability as well as the feasibility side and without involving too many people, then it comes to bringing the right because what I say that it's always the case, a product failed not because um LLM core the model is bad. It is because people are not ready to adopt it for multiple reasons. They are like uh it is not in the flow, it is not easy for them to use it. Sometimes it is just the status quo, they are very comfortable in their environment. Right. So that bringing them uh in uh like a mix from the beginning. So my question is I I use a very uh quick uh framework, stop easy and then flow. So basically, if I bring this product, what are the three things you are gonna stop at doing? So that's right to help me to bring them in this mix and the adoption from D. And then during the design, you design the research product in such a way it is in flow. So it's not another point to solution. So, for example, if I'm doing working on a like a um analyzing some information, right? And I'm in a lash, I don't want to go into another chat box and identify, okay, what's happening in the data. I want to know that okay, hey, here is the 3% F. Why it is happening? Can I do something about it? Right. So can I have a conversation about it? And that's where it is easy to feel. Similar thing if um I'm working in my SharePoint and I have a lot of my content. I want to know, like, okay, in last one month, right? What are the different things happening? Can I have a summary and just set it to my boss? Right. So I need to have that my chat or my conversation right there, right? Yes. So that's the flow. And then the easy part is like is it easy for me to navigate or do I need to do a three, four steps, enable certain things, and then only I can use my product. So these are the three things on the product designing side, which is like I'm working with a technical and that's where it actually helped me to not only bring a product which is useful, but people want to use it.

Chris Hutchins: So I think that's the way I uh I you're seeing AI getting the same kind of uh interest and reactions that what dashboards were at one point in time. And it was amazing when when we first started deploying them in my first experience, the very first one, it just caught on. People got excited, and all of a sudden they had dashboard envy. You happen to have a very well thought out problem that you wanted to solve, and the dashboard seemed to be the right thing. We work with you, you launch it, one of your colleagues sees it, they're like, Well, I want one. And they call me, tell me they want a dashboard, and my team is going through it. It's like this, they really just need a list. But then the the worst part is the over-engineering, these people that design some of the solutions, I mean the incredibly brilliant people. And what motivates them and makes them tick is creating something that's really, really useful and it's powerful, but they can get really excited and over-engineer it. And I'm not nearly as technical as most, but I have tended to over-engineer some things myself. But the problem is if it's not explainable, it's like a comedian telling a joke that no one understands the punchline. They're asking a question. If it's not self-evident, you didn't do it right. If you're not answering the very first question that someone needs to have it answered, like you brought up a great point, is it going to enable a better decision to get made? What you're showing me change any decision that I can make at all.

Ritu Chakrawarty: Improving my agency, right? Helping me to do something better. So and that's where it actually helps. Because easiness, it's in flow. I'm not taking three extra steps. Because as long as if you ask the people to do XYZ more, they say, I'm already overloaded. I already have so much in my plate, and you are asking me to use the Vradan. I have to do three steps. No, thank you so much. I am gonna use the same thing what I'm doing here. So, yeah.

Chris Hutchins: You know, it's interesting. The quick reaction sometimes is because this everyone's excited, is they want to come up with a new solution. But one of the most glaring solutions that I saw in the last few years was at my doctor's office. And what they were doing that I'd not seen people doing well was so simple. I'm walking out the door to the waiting room, and she made the appointment for me. Right then and there took her 10 seconds, and she handed me a bit a business card with the schedule on it. Gaps in care is a real problem in healthcare because the basics of clinical protocol are not pushed down to the levels they should be. So the physician knows what he needs to see the patient, but he's not he doesn't do the scheduling, doesn't probably even have access to touch the schedule. But it was really as simple as in that particular practice and that specialty, the kind of patients that they see there, the clinicians made sure that the the front desk people who are interacting with the patients, they knew what the standards were and they took care of it. In a piece of paper is something that people are trying to solve with a whole bunch of technology now. But the the right solution is is sometimes the really it's an easy one.

Ritu Chakrawarty: I always say that just because the AI is a shiny tool, not necessarily. That is not a AI solution. So do should or could test. Should I be using the DI or and then comes to could say can I do it? Right. So that's where the litmus test is. First is the viability about that should, and then could is like, okay, do I have a digital information? Is it right? Uh and also like if it is very easy for humans to do, like you gave examples, I should be making it complex and then put it into until I see that feature use it. Or I want to scale it so that it could be extending. So, yeah, this isn't as a product strategy.

Chris Hutchins: Well, but the good news is that people that are really smart and can do those things, they have you. So you keep them grounded in the thing, hey, slow down. I know you like to use your hammer, but we can actually use a piece of piece of tape on that. It's really not that important.

Ritu Chakrawarty: Absolutely. And that's exactly what happens because sometimes you don't need a full big dissolution. You just need uh and and that's where you rightly said this is such an important discussion because many times, especially if you're working with a tech team, to build a lot of space.

Chris Hutchins: They're great at it.

Ritu Chakrawarty: Where's the idea to say, oh, let's make a bed, let's have a 20-member team, then let's build it. And then my question is wait a minute, within our uh kitchen, you may have certain tools which you can immediately start using it and at least have a 30% benefit, right? So you so uh can we use that and then see the value, adoption? Are people using it? That is a signal. If people are coming back to your solution, even if it is halfway, then you know that they like it, and then you wanna make it better, better, and better. So, like uh just first of all, finding that do they want to go from point A to point B? So have that cycle and then make Ferrari for us to see that that like they are taking that farther.

Chris Hutchins: The interesting dynamics they tend to be cultural in a lot of ways. We've talked about this in so many different contexts over the last couple of days, but human trust is is is kind of a big deal. Um, there's fear involved, people are afraid it's coming for my job. When you you're working with with teams and identifying though the workflows that you're gonna go after, oftentimes there's the experience has been that, oh, here they come, they're gonna ask me to do something else that's gonna change my workflow. And to your point, it's not inflow. And that's something that you look at. What are some things that you you're dealing with trying to actually counter what those experiences have been in order to get them to be comfortable and willing to trust that, you know what, she's not coming for my job. She's she's trying to help me to become more valuable and work on more higher priorities.

Ritu Chakrawarty: This is such an important thing. And I think uh everyone, whoever is in like us uh shoe, need to think about because um so when we when I see that like an easy framework for stop easy and uh flow, uh the most important thing is then come start. So you're stopping something, what are you starting? So rather than asking that what are you gonna start it? My question is what it is gonna enable you to do if you want to do it today, but you're not in this and as soon as you say that, that's where you are catching on their trust because now they know that okay, sis, the tool is coming, help me to be a better version of myself. Uh like uh improve my uh not the productivity, I would say, improving my disease and the capabilities. So that's where the you actually latch on and say, your job is not going anywhere, rather, you are opening yourself for the better thing. And um, I like the way uh so I was reading about it and when must say most of the job would be gone uh with uh new tools that are coming with the physical AI, right? And that jobs are something which even do not want to do that if it is a dirty and difficult job from you are taking away from human case. Yes, that's nearly a lot for you. Because I don't want to go into a ditch and find out uh like uh or like do some kind of repair. That's difficult. I don't like to do it. But if something can do it and I will just operate from like while sitting on my desk and then remove move the robot, and that's and the robot can do. Right. That's what I would love to do. I'm not losing my job, but I'm getting a better which will help me not to put myself at right.

Chris Hutchins: You know, it's interesting working around data data uh analysts, data architects, ETL developers for a number of years. One of the things that I've thought observed, I'm sure you've seen it too, uh analysts spend easily 60 to 70 percent of their time wrangling the data, getting it fit for use, very little time doing actual analysis. And when you actually can automate the things, and they're they're a little nervous about it to begin with, because you know they're they see their value in a different way. So I've tried I've always had to coach my team, you're not here because you can do stuff with technology. So because you know all the technology. Absolutely. You're here because you're able to figure out what's the right solution to the problem that we're trying to solve. And it's what you what's in your head, what you know, and how you think, how you approach things, how you network with people, that that's the stuff that really is valuable. But if you're really like talk to um very effective to actually start to repair some of and restore some trust with the people who like to your point, they're fearful of losing their jobs, right?

Ritu Chakrawarty: Also, I would say um the most important thing, uh darkness is fear. So the fear is when you don't know. When you don't know what is coming and why it is coming. So start with educating your people and that's why AI literacy is super, super critical. And it has to be sponsored from the top. Like why, as long as human are able to know that why it is, what it is, then they they will find their own path. But if they don't know, then they will speculate. That's right. Because even for a good AI to work, needs as you said, that you are here for a reason because we know that this data works in a odd way, right? So you have institutional knowledge, you have that uh a kind of uh uh I would say the recipe that how people work. Yes, so going away. And as long as people understand that, that's where they will start leaning in. That's where they will start adopting it. So then then your whatever you see the barrier, it's slowly, slowly losing up. And that's where um start with literacy, making it uh uh like from the top side. So for example, you record video with a K Ian and then share with your team saying that okay, I'm super excited, I got this tool, I got it this video, and this has helped me to do the thing which I used to take a five takes, now it has done a one take. Tell me what's your feedback. Now people know that oh, my CEO is using it. And why don't I use it? So my CEO is not afraid, or my detail is not afraid. So that's where like uh you show them, inspire them, educate them, and help them to use.

Chris Hutchins: I I love that because I I think the the reality is there's a lot of people inside of large organizations that are taking it upon themselves because they're seeing enough, you know, whether it's through friends, family, colleagues, uh they're experimenting, they're learning stuff already. So you know, not only is it important for the CEO or the executive team to be aware of it and learning things for themselves, they also need to understand that their teams are already doing it. They don't have, they may not be doing it on their job, they may be. I I don't know the answer to that, but there are a lot of people that are actually learning it. And I think that the mistake that we can make is really not delving into it. Sadly, and this is something I'm I'm I'm glad we're you're here to you're the right person to talk about. For a CEO, their peer group are very high functioning people, they're very successful. Some of them may have a really great strategist that they lean on a lot, some of them may not. One of the things that I'm really concerned about now is if there's a CEO out there that doesn't have access to a strategist, how on earth are they going to navigate? Because it's human nature. I can talk about buzzwords, I know what you're talking about to a certain extent, but I might not have enough understanding to know what are the steps I can take in in the near term. And how do I avoid looking like I don't know anything, right? People need a trusted advisor, right? Maybe just talk a little bit about that. What should somebody be looking for? You know, what's a CEO really going to benefit from and what's so important about the work that you do? I mean, I understand it, um, but tell the CEOs out there how you can help them and what they should be looking for.

Ritu Chakrawarty: And I so it's super basic. Uh and it it is not starting from AI. As a CEO, you must understand where your strength lies, where are the gaps, right? Or in in that way, in any leadership role. So understanding that what I know, what I don't know. And then we used to call it like in the back in the days, Jori's window, that what you don't know, what what you others know. So do some kind of a strategic blend framework like could uh collapse and all that. So understand your um operating framework. Self-awareness is the critical one. Once you understand that, like what is my role and responsibility and what I bring on the table. Now you need to know that in order for me to fulfill my role and responsibility, here is the gap. Yes, and ultimately we are humans, accepting that with the self-awareness that here is the gap. Or have somebody on your uh like back to it as a strategist. Nowadays, AI tools are also helping you to at least have a kind of a starting point. Uh find out that okay, what these uh these uh like basic question at least, little awareness. So self you can self-educate yourself as well. But again, having said that, like you may have the superficially level information, right? But in order to like you are a CEO, right? So and you have a stakeholder uh responsibility as well. Yes, so understanding that gap and the filling, I would say that every CEO should have AI advisor directly reporting to them.

Chris Hutchins: Yes, but I agree with you.

Ritu Chakrawarty: And if you don't have you are if you are going by a path of CDO, CDO and Paul, yeah, I think that's a mistake.

Chris Hutchins: No, I I agree with you.

Ritu Chakrawarty: Because if you have an AI strategist who has a great knowledge about the subject and And then have spent good time. Again, I would say that this DI advisor should also be a mix of technology plus business. Because somebody who just knows technology does not understand us cannot be a good advisor.

Chris Hutchins: Thank you for saying that.

Ritu Chakrawarty: Choice of somebody who has that delivered uh outcomes in a business plan.

Chris Hutchins: That's right.

Ritu Chakrawarty: And they now have a strong knowledge of the A subject, they should be our account.

Chris Hutchins: Your best technical people are going to have a bias towards doing technical things.

Ritu Chakrawarty: Absolutely, you rightly say.

Chris Hutchins: And we want them to do that. Yeah. But what we have to have the two things coming together, and it it is a unique person that actually can see those things and figure out how to marry them and how they should collaborate and work together.

Ritu Chakrawarty: It's just like generalists who have seen a different uh facet of business. Have a business degree or business talent, delivered outcome, your revenue, and top and down batteries. And then you they are very good understanding of technology. That's the best combination you'll have be given.

Chris Hutchins: I totally agree with you. As we're wrapping up, if people want to get in touch with you, how do how do they find you?

Ritu Chakrawarty: Yeah, best way, LinkedIn. So and it is very simple. My first name, last name, you can find it.

Chris Hutchins: Beautiful. And for those of you listening, we will definitely put her information in the show notes. Ritu, it's been amazing to be able to sit down and talk with you. I really appreciate you taking the time and being with me. I'm excited. We've got so much great content that we've come up come out of these meetings with, and we've still got some more to go. But I I look forward to staying in touch with you. And I can't wait to have you on again. I'm sure there'll be plenty of new late breaking news for next time we talk. So again, thank you so much for taking the time. Thanks for being on the scene.

Ritu Chakrawarty: Thank you so much. And uh it was a pleasure talking to you.

Chris Hutchins: Thank you.