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In this episode of the Becker's Healthcare Podcast, ELLKAY President & CEO Ajay Kapare discusses why many artificial intelligence (AI) initiatives in healthcare struggle to scale and what separates organizations seeing real results. He highlights the critical role of data integrity, interoperability, and governance as the foundation for successful AI deployment. Listen to understand how a strong enterprise data strategy enables long-term innovation, operational efficiency, and measurable return on investment (ROI).
Many AI pilots stall because they are built on fragile data environments. Kapare points out that persistent data silos, poor data quality, inconsistent formats, and inadequate governance are the primary culprits [1]. Without a disciplined approach to unifying systems and cleaning up interfaces, organizations cannot demonstrate ROI, regardless of the advanced AI tools they deploy.
Discipline around data strategy. Successful organizations prioritize data integrity, interoperability, and governance before investing heavily in AI tools, ensuring they have the infrastructure to support long-term, scalable outcomes.
The most important investment is in scalable infrastructure, not just the latest AI models. Because AI technology will continue to evolve rapidly, health systems must build a secure, compliant, and connected data ecosystem capable of sustaining innovation over a five-to-ten-year horizon.
Erica Spicer-Mason: Hello, everyone. This is Erica Spicer-Mason with Becker's Healthcare. Thank you so much for tuning into the Becker's Healthcare Podcast series. Today, we're going to talk about delivering real AI results and why enterprise data strategy comes first. And joining me for this conversation, we have with us Ajay Kapare, the President and CEO of ELLKAY. Ajay, welcome to Becker's podcast. Thank you so much for being here today.
Ajay Kapare: Thank you, Erica, for having me here.
Erica Spicer-Mason: Really happy to have you here. And I thought to get us started, it'd be great if you could share just a little bit about your background and also offer our listeners just a quick snapshot of what ELLKAY does. What are the types of data challenges that you're helping health systems navigate right now?
Ajay Kapare: So Erica, the last two decades I worked in healthcare and healthcare IT. And I joined right when we started with the wave of meaningful use. And from meaningful use, getting all the revolution done towards healthcare, electronification of EMRs and every physician in the US trying to actually adapt to that change to population health, community health. And now we all are in the AI wave. ELLKAY, to be honest, we play a central role towards all the things going around us. ELLKAY as a company, we are in five segments of healthcare IT. We are an enterprise interop solution provider company. Primarily, the three solutions that we offer and the three problems that we solve – we are LKOpera, which is a platform to orchestrate all the interoperability. Then we also take care of live and legacy data platform for a long-term digitization strategy with LKOasis, and then platform to expand the possibilities that things beyond connectivity with LKOrbit, our lab network is a pretty big place out there.
Ajay Kapare: And as we look at ELLKAY, the next generation where things are changing, we all are looking at what the power of AI and what AI can do. And I feel like we are the foundation for that clean and clear data that drives these strategic initiatives to make AI an enabler. This is where we are all actually very excited about.
Erica Spicer-Mason: Great to learn more about you, Ajay and ELLKAY as well. It's fantastic that you have this kind of central role as an organization. I think that's an important place to be, especially as we're seeing so much enthusiasm and even hype around AI and healthcare. And we hear from leaders across the industry that a lot of pilots struggle to scale. So, I would love to know from what you're seeing across your own client base, where is AI actually delivering measurable results? And conversely, where are organizations hitting walls that maybe they didn't anticipate hitting?
Ajay Kapare: I think if you look at it, as we talk about fueling the AI innovation with access to quality data, that quality data access is where we play the big role. If you look at it today, 91% of healthcare leaders believe AI or machine learning will be an integral part of their organization's growth. But at the same time, if you actually do a survey with 20 different CIOs, chances are you might get 20 different answers because everyone's strategy is different. Strategy is still a foundation. Where ELLKAY plays or ELLKAY tries to help them in the initiatives, what they're trying to achieve is data integrity, which also includes... Today, if you look at it, there are a lot of data silos. There is a lack of sufficient data. There is poor data quality. There are inconsistent data formats, inadequate data governance where ELLKAY can come and really put a foundation is.
Ajay Kapare: We can do the groundwork for AI and machine learning success by ensuring that there is a proper data integrity. We are actually ensuring that there is a quality of data which goes in. Otherwise, you are always going to see that garbage in, you're going to see the garbage out. So, we are the enablers of the data. That's the big role that we are playing right now with our data and interoperability strategy.
Erica Spicer-Mason: Oh, fantastic. Thanks for giving us a kind of on the ground feel of what you're seeing, Ajay. And when you look at the organizations that are seeing real traction with AI versus those that have not yet, what would you say is the distinguishing factor? And how much of that comes down to the data foundation that they had in place before they even started to leverage an AI tool?
Ajay Kapare: I think there is always going to be that excitement, looking at the use cases and looking at what you can actually achieve. A lot of times with that excitement, a lot of dollars gets actually plugged in. And then you see at the end of the day that there is no ROI. In today's time, when things are difficult, I mean, you open Becker's, the daily Becker's report, and you'll see that things are not that easy. And in these times, you really have to start fixing your data strategy with Data Foundation. The real organization who are seeing real traction, it's not just that here is a use case or here are the tools I'm going to use it. And it's not even the budget, it's the discipline. How do you put it together? You've got to make sure that you are unifying the system, clean up your interfaces, and you get serious about governance.
Ajay Kapare: The one struggling part that everyone is looking at is how the top of the layer will perform in this complex environment if the bottom of the data which is inserted is not correct. So that foundation piece, the quality and connectivity of your data, one has to look at it. And I personally feel anyone who works super hard on that foundation is going to absolutely be successful at the end of the day. The integration, the data aggregation, the quality and insight, and then the reporting of that, it all plays cohesively with each other. And that is the part I feel like we can really help a lot.
Erica Spicer-Mason: Yeah, Ajay, I know in a lot of these AI conversations that I've heard or participated in myself, the data foundation is something that's stressed pretty universally among experts such as yourself. So, I appreciate you sharing that. And I'd love if you could just walk us through what an enterprise data management strategy actually looks like in practice. Maybe there's a lot of moving pieces, so if we could just give our listeners a more granular sense of what that data management strategy looks like. And for a CIO who's heard that term frequently in vendor pitches, what does it mean to really get it right?
Ajay Kapare: Yeah. And we as a company, we are moving towards being enterprise interop solution provider company, and it's a journey for us. We started with being data plumbers. From being data plumbers, we started getting into becoming an enterprise interop solution provider company. And from there, as we look at it, we are slowly and slowly becoming an enterprise data management company. Or we call ourselves very proudly we are your enterprise healthcare data partner, but enterprise data management, it's a platform, is the foundation for data-driven healthcare strategic initiatives, and it's the innovation across the care of Continuum that we are trying to provide. Now, what comes in enterprise data management platform? It's your interface/interoperability, it's the translation of data, it's the aggregation of the data, and it's the access of the data. And as you look into it, there are multiple pieces to it.
Ajay Kapare: With our enterprise data management, we are bringing in, we are trying to build a network strategy, maintain legacy data, experience that speed to value that everyone is looking at today. You want to accelerate your innovation, you want to put your AI LLMs on top of it. That innovation we are trying to accelerate. If you look at the complete data visualization that is achieved – in small words, I can just say that we are trying to make sure the competitor advantage, the models that you are putting, it all starts with the quality and connectivity of your data. And we are trying to make sure we can do this.
Ajay Kapare: There are a lot of noise around enterprise data management or data strategy, it's easy to say it than to actually put it in place. But we have proved ourselves today, when you look at our lab network, two-third of this country, they access their lab order and result through ELLKAY. If you look at our partnership with CommonWell, there are more than 200 million patient transactions which happen through us. So, we are making sure that the AI play is not just a pilot mode, but we are trying to build a future of five to ten years strategy across the segment of healthcare.
Erica Spicer-Mason: I really appreciate you translating enterprise data management strategy for us, Ajay. I feel like we have a much better picture of what that actually looks like. And just to take this one step further, I guess I'm here to close us out, if you're sitting across the table from a health system leader today, especially someone who's in informatics or technology, what is the one infrastructure investment that you would tell them to prioritize in the next year to really set themselves up for meaningful improvements with AI?
Ajay Kapare: I think it's not even fair to say – if there was one advice I can give and that can solve all their problems, it's easy, right? But the fact is we are in this timeframe right now where innovation and the changes of innovation with AI are changing every day. A lot of excitement around that. At the same time, you have so much budget constraints. You're trying to do more things and less money today, and these budget constraints, they're real. And everyone is looking at it, how can I get the best out of a product with a great ROI? And my simple simplification with everyone is that you've got to actually look at your foundation. You have to look at your interoperability, you have to look at the number of systems that you're working and how you can actually bring all that data together with the one single strategy.
Ajay Kapare: Enterprise data management definitely plays a big role here. AI is going to keep evolving. New models are going to keep coming, new vendors are going to keep coming, new partners are going to keep coming, and you will end up doing more and more. But your foundation, and especially your data foundation, data governance, has to be on the top. That is definitely going to be one thing that is going to differentiate the organizations that win, they're not going to be one that are adopting any new technology first, but they are the one who are going to build the infrastructure to sustain it for longevity. Remember, you also have to look at the compliance piece. You have to look at the security piece. You have to look at the changes happening in regulations. And all those things can happen only with the foundation of the data layer that you're putting together.
Erica Spicer-Mason: Ajay, it's been so insightful hearing what a sound data foundation can enable in terms of innovating in the first place or just responding to the rapid changes that you're speaking to that are happening right now and will only continue as AI evolves. So, I just want to thank you for sharing your time and your thought leadership with our listeners today. It's been great learning from you.
Ajay Kapare: Well, thank you for the opportunity. And I always love Becker's. I come to Becker's (events) and I'm looking forward to attending in person and I hope more and more people can actually get advantage of the conference.
Erica Spicer-Mason: Oh, Ajay, thank you so much, and we're excited to see you at our events this Spring. And listeners, we'd like to thank you for joining us. And of course, would also like to thank our sponsor for today's podcast, ELLKAY. Be sure to tune into more podcasts from Becker's Healthcare by visiting our podcast page at beckershospitalreview.com.
About Ajay Kapare
As President & CEO of ELLKAY, Ajay Kapare leads the organization with a strong focus on driving innovation, building a customer-first culture, and delivering intelligent solutions that keep healthcare data moving forward. He is responsible for setting the company's strategic vision and ensuring alignment across all departments to meet growth and performance goals. Ajay holds an MBA in Marketing from Texas Tech University and serves on the CHIME Foundation Board of Directors, with active involvement in HIMSS and other leading health IT organizations.
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