The AI Leadership Playbook for Global Enterprises | Elena Alikhachkina

**Lesia** (0:07)
Hello, Data Storytellers. So this is an episode I've been looking forward to. I think Elena and I connected last week, maybe the week before, and quickly we had a conversation just sharing some takes on what's happening out there in the enterprise AI transformation world, which is a very dynamic space today. A lot is happening, there's a lot of confusion, there's a lot of noise, there's a lot of signal as well. So our goal today will be to bring as much signal into the conversation as possible. So without further ado, Elena, welcome on the show.

**Elena Alikhachkina** (0:43)
Thank you so much. I'm so happy to be here. Definitely a lot of interesting topics. And I had a chance to read your recent article, like a summary of your interviews and observations, and share it with many people. So people really got excited. So they can totally relate to your experience.

**Lesia** (1:01)
I appreciate it. I was glad to hear it. Actually, I still haven't published that article on like, I'm still, I still owe some of my advisory board members, just the fact that I should post it with some commentary. It was actually one of our advisory board members, Ilan Qazi, who said, hey, Elias, can I just share it, please? I mean, sure, go ahead. And then I'm happy, I was happy to hear back from you that I actually sent it to my team. So I'm glad it's really, it came from the heart, if you will, in the sense of, okay, I'm having these conversations, these great interviews, we're working on all these cool projects with these data and analytics and innovation and digital transformation leaders and some of the biggest and best companies in the world. But I want to capture something to just share with the general public, so to say. So we had this idea of creating the AI Executive Series, where basically there's a publication, there's some written pieces, but also interviews with people who have been leading different transformations relating to technology and the data and digital transformation and now AI and just kind of highlight what works and what doesn't work and explore some journeys and help people make better decisions and also just have fun while we're doing it. So when you reached out, we had a quick call and we set this call up. And I remember we actually are going to start with a very hot topic, which is agentic AI. I think this is one of those areas where there's just a ton of noise, but also so many cool things happening. So I want to explore that from a data perspective, but I think you told me when we first spoke that, hey, wait a second, Les, I think that when we look at this AI transformation, the data transformation might not be the right historical context. That's all I'm going to say. We're going to reveal what we're going to talk about. But I read this article, actually, I just went through this article that you wrote. You just sent it today. And I was looking forward to the podcast. I skimmed it in immediately. I was like, OK, I'm not going to read this because I want to hear it from Elena. It was a really cool angle, which is when we think about data foundations for agentic AI. And actually, a lot of our members are working on that too, rolling out a bunch of these agentic AI solutions. And we actually have an upcoming master class where we will talk about that from different aspects, from an AI strategy point of view, from a data foundations point of view, from a stakeholder management point of view, from an operationalization point of view. But the data foundations are so critical.
And with that, your take was that you're actually building data foundations for a different audience now, so to say. And I'm using audience in quotation. So can you just unpack that idea a little bit, because I find it fascinating.

**Elena Alikhachkina** (3:42)
Yeah, absolutely. So let me actually tell you why I personally like agentic, right? So I love it because this actually helps to go into the business deeply. So this actually helps to replicate the business process, right? So the way how I see the agentic is helping to speed up the process, helping to solve the task. And I'm a big believer as close we to the task, as close we the to the action. And there is a greater story for success, right? So this is why I'm like a believer into agentic approach, right? So of course it's still going to evolve, right? But my story today was actually about thinking in a way how we have been doing our data management for years, right? Building the data teams, building analytics teams, and we have been building our teams around different customers or audiences, as you said, right? So the primary audience is usually business people, right? So the business people or data analysts who requires access to the data, right? And we provide them databases, we provide them data lakes, you know, and everything, right? So then we started building access to digital applications. The different apps, right? So you want to draft personalization, you know, you attach to your data lake, now you can draft personalization, right? But if agents gonna be reproducing the business processes, so they could become the primary customer in the future, the primary audience, which completely changing a lot. It's changing a lot in terms of how we should be organizing data, how the data management should be happening, what type of checks we should be put in, you know, through the entire process, right? Plus, it also changes entire concept of the governance, because governance is not becoming like a theoretical concept anymore, or your metadata is not the theoretical kind of concept, right? So your metadata is almost becoming like a customer experience for your new customer, which is your agent, right?