Alright. So first, I just wanna thank the chief in tech summit team, for bringing us together today.We're truly grateful for the opportunity to join you for this fireside chat with Jen Hamuda. I'm gonna start off with, question, Jen, just so the folks can get a little bit more of your background. You were named as the CIO of UnitedHealthcare, last June, and you're now leading a globally dispersed technology org. You've built quite a reputation for combining deep operational expertise with an AI first mindset. Can you start by sharing a bit about your journey to this role and what shaped your leadership leadership approach along the way?

Sure. So I have a little bit of an untraditional path to where I'm at. I actually started out in accounting and finance and, which is not typical for someone who ends up sitting in this seat. But I do think that it gave me a lot of perspective on the other lines of business and their importance in how you shape a technology strategy. And so I spent time in accounting and finance, some time in supply chain management, proposal writing. And so I've really played a role in most areas of the business, which I think helped me shape the strategy and understand the importance of inclusion of business and tying your technology strategy back to the overall business strategy. Also the understanding of how financials work, I think, one, just gives you more credibility.

But two, also help in your overall success in executing a strategy, if you can tie it and understand back to the overall business objectives what you're really trying to achieve.

Awesome. Next question. You know, leaders are excited about AI, but I think the workforce is also asking some really hard questions about what this means, what this means for our role and our jobs. How are you thinking about AI adoption across UnitedHealthcare without creating fear for your workforce?

Yeah. I think I think this is a really difficult question, but really, really important. And so we don't think about AI as a transformation to the world workforce. We think about it as transforming our business. Now underpinning that, we also understand that our business and our workforce must adopt AI. And so I'm sure you've all heard the saying that AI won't replace your job, but somebody using AI will. And I do think that that's a very important distinction when you're thinking about the change management plan and the communication. I was reading through some of the comments here earlier, and I loved, the comment around being able to accelerate your road map. And so if you think about AI as being the springboard for abundance, Imagine if you could do everything on your roadmap.

To me, those are the companies that are going to succeed. And that doesn't mean that you are going to dramatically cut your workforce, but what those people in the workforce do will start to fundamentally change. And as long as you give people the opportunity to upscale themselves, it makes the transformation a little less scary. The transformation is always going to be scary. And part of it is there are so many unknowns. This industry moves faster than anything we have, or we'll see in our lifetime. But I think as long as you're transparent with your teams on what is the path forward, what does it mean for them? And then just be honest about what you know and what you don't know at the time.

Awesome. And, Jen, I'm gonna take one question from the chat that ties to that, just around how you kind of personally cope with the fast pace of the AI technology changes and keeping your team up to speed and and kinda keeping up with it.

How do you cope? Apologies. That's my dog. So so what I try to do is create, a set of knowledge for myself. I'm so sorry. But we're at this point where there's more information and information out there than we can consume. And so you have to grade what I've called with my team as, like, a knowledge diet. And consumption and training just has to be part of what you do on a daily basis. And then make sure you set that expectation with your team as well. He he does have opinions on the content. But to me, the the winners in this AI race are those that are able to intake and adjudicate information in the best way.

So product exchange, partnerships change, and so really operationalizing how you consume and adjudicate information is just so very important.

Awesome. A lot of organizations, Jen, get stuff just AI awareness. What's different about how you're driving adoption at UnitedHealthcare?

So I really, really believe in this leadership shadow. And so there are very few things that I do that or I ask my teams to do that I didn't try myself. And so as we roll out these new coding tools, as we ask people to take trainings, I do them myself. I ask my leaders to do them do it themselves. When I talk to my CEO, he asked their leaders to do it as well. And so it doesn't necessarily feel like it's just going to be a grassroots adoption of AI. It's really our CEO and along with me setting what that strategy is, showing how we're doing it, showing where we've had success, and showing where we've quite frankly not had success, but just being honest about it.

And so, you know, AI is such a significant part of UnitedHealthcare's transformation as a company and what we wanna do with our members. And, having our CEO and the executive council really embrace that and use AI in all of their conversations is just so important.

Yep. Absolutely. So what tells you that AI adoption is actually working?

So, again, this is a really hard one as well. And you have to do it, I think, in some qualitative quantitative and some more subjective manners. But, overall, you have to just understand are people starting to change? Meaning, are they starting to use the tools? And so last year, we had about 50% of our developers using some sort of AI tool. Last week, I got my metrics. A 100% of my workforce is using AI, at least on a weekly basis, if not on a daily basis. And so that's kind of the are people starting to adopt? And then you start seeing it pull through some of the metrics. And so you were starting to see our cycle time dramatically decrease. We're starting to see our backlogs run out.

And so while that may not be a great thing, it's also an indicator. And we've been using it to help our business understand that they need to create strategies a bit faster. But to me, maybe the most important thing is the subjective component. And so sitting you have to sit down with your individual teams. So we talk to our scrum teams. We ask them to show us how they used AI in every phase of the SDLC. We talk to our business partners and ask them, does it feel like you are getting more for your dollars? Does it feel like everything is moving faster? And those things start to line up. You start to feel like you're really transforming as a business.

But as all of you know, speed and software development has never been something that's been easy to measure. The individual productivity of a developer is very difficult to measure, and so you almost have to take, like, this three pronged approach to it.

K. Jen, I think the audience would love to hear an example for UnitedHealthcare. We moved from a pilot, to real operational impact. Can you share an example?

Yeah. I'll share a couple of examples. One which is the probably most public facing in the news example, which is our, essentially, our chat GPT for our my UHC app, and it's called Avery. And you can talk with Avery about your benefits, your claims, upcoming appointments. Eventually, you'll have the ability to ask Avery to start to do actions for you, like schedule appointments. And, it's been a bit of a long journey where when most companies start out with AI, they use it for operational efficiency. And so we had a lot of successes there. But this was really the first time we deployed law large scale AI where we couldn't necessarily control the answer.

And so as you all know, with generative AI, it's a little bit of a black box in terms of explainability of the answers. And so we spent a lot of time talking about what were going to be the general criteria that we had to pass to deploy this functionality. How are we going to measure success of this? How do we figure out how quickly our road map can scale? And then how do we understand model drift along the way? And that's been a really, really interesting journey that has shaped a lot of our responsible use practices. So that's our external one. I'll I'll talk a little bit about some internal, ones as well. And we have released, partly agentic workforce in our provider area, and it's really more of our provider operations where we update, providers fee schedules and contracting information.

And, again, it's like, okay. So now I have an agentic worker. What does that mean? Do they need an employee ID? Do they need a supervisor? Do we actually give them names? All of that has been kind of a fascinating, technology and philosophical discussion.

K. Jen, I think we're wrapping up to the end of our time. So one more question. We'll see if there's anything else in the chat. But if a fellow executive asked you what they should do tomorrow to prepare for AI, what guidance would you tell them?

I think it's really easy, which is use it yourself. So you lose a ton of credibility if you, as a leader, are out out there saying, hey, everybody should adopt AI, but you don't have success stories to give them. And you're not creating the shadow of a leader in terms of transformation because what you're basically saying is that this isn't important to me. And you also don't truly understand the power of these tools and the transformation on your business if you're not seeing about seeing it, using it, hearing about it, and really, as I said, kinda tailoring your knowledge diet around those things that you need to understand to make the most appropriate decisions for your organization.

Alright. I'll take, a couple questions from the chat. If there's anyone else that wants to put a question in there, we'll see if we can get to them. We got a couple minutes here. So, Jen, one of them is around in health care. How do you balance efficiency, trust, and human connection when implementing AI?

Yeah. So we have a a very strict policy that we will not use AI, to change the relationships and interactions with our members. And so health care is deeply personal to anybody or to everybody. And ensuring that when you pick up a phone, the way that we've used AI is actually to make that, advocate much more effective to serve up answers faster. We understand that everybody's time, is priceless. And so we really draw the line and have these conversations as a leadership team all the time to make sure that we support our members, both effectively from a relationship perspective, but also understanding the areas where AI may not be mature enough to roll that out to our members is also just as important.

Alright. One other question. What are the auditing implications of an agentic workforce?

Yeah. So what we found, and my biz and the reason I'm laughing is my business laughed at this when we were deploying it out, but we actually deployed something called time travel with our agents. And so it's very easy to try to check your agents' work against an SOP, but really having somebody go back and watch exactly what that agent did through time travel, I think has been really important for us. Going back to there's an unexplainability component with generative AI. And so unless you can see kind of the thought process behind what that agent does with this time travel capability, you really don't know. And so that's really been an important component to our agentic workforce.

Awesome. Alright. I think we are at the end of our time. Any closing thoughts for the group, Jen, before we wrap up?

First first of all, thank you for the invite. Second, I apologize again for me being in the car and my dog barking and joining, the overall conversation. So you all were wonderful. I'm watching the comments and the chats. It's spot on. You are all asking the right things, and focusing in the right areas. And, again, just just thank you so much.