Not a day goes by without artificial intelligence in the headlines. Are the big AI companies spending too much? How should the average American approach the AI boom? How will AI affect health care?

On this episode of HealthChangers, host Ashley Bach tackles these questions and more with Laurent Rotival, executive vice president and chief information officer for Regence. This is the second of our two-part conversation with Laurent about the future of AI. You can find part one here.

Listen to the full podcast episode on the player above. Below are some highlights, which have been edited for length and clarity. 

AB: I want to follow up on something we talked about in our first conversation. Can you elaborate on how generative AI can reinvent and transform organizations like Regence to be more predictive in what our members need?

LR: The ability to use AI ten years ago was reserved for the most well-funded and most brilliantly staffed institutions that had the resources, the talent, the ecosystem and the access to compute that nobody else had. And today it's, for all practical purposes, almost free. And what generative AI has done is put predictions and artificial intelligence in the hands of every single person on the planet that has access to a smartphone or a computer. And in the case of health care, the ability to predict risk and the ability to predict need, and the ability to proactively reduce the time from identification to matching you with the right doctor or the right service, is life changing. And to do so at a low cost is extraordinary because it has a direct effect on affordability.

AB: How is Regence using generative AI to bring about organizational change?

LR: We've leaned into how generative AI can change the way our company operates and our employees do their work. The first step is looking at our culture and providing those generative AI capabilities in a secure, private way to every single one of our employees. And so our employees have access to a personal AI agent that's available in a secure way within our internal networks. And they've been able to become familiar with the technology.

Our employees are reinventing their jobs by enhancing their productivity and rethinking the way they can do things: faster and better, ultimately, for our members.

The second element is going from looking at how generative AI can actually transform our existing processes, our existing workflows, inside the company. Those have given us some tremendous benefits of 10, 15, 20 percent [increased] productivity and that's, of course, very meaningful.

And where we're going next is to start thinking about, how do we rethink [into] AI–first processes or operations or business models? That's the next frontier for us. We'll be rethinking, rather than doing your job and just adding AI and generative AI to the way you've always done your work and making it easier and less bureaucratic, but how about we completely reinvent the way we do work?

AB: Some people think that AI will make health care robotic, or not as personal, but it sounds like it’s really the opposite.

LR: There is that perception, and there's a movie industry designed to make us all scared of AI and of all the horrible things that might happen. That's not the way we see it at all. We really see this as a way of eliminating the complexity, eliminating the bureaucracy, streamlining all of the preparation and documentation and filing and controls and ensuring that our employees with whom our members interact, who are deeply passionate and committed to serving our members, can actually do their jobs with minimal interruption. So we're pretty excited.

First and foremost, AI is allowing us to be more human, to be more personal, and to really focus on that human-to-human rapport, which is what we all miss in health care, unfortunately, from the last few decades.

AB: How can AI transformation apply to health care?

LR: We have this fabulous, really deeply personal, empathetic, clinical case management team at Regence that serves our most chronic members who have the highest need for care and assistance. And [those members] are 3-5 percent of the population we serve; and those are individuals that we don't need AI to know that they've got challenges, and they need help because they're already people with very significant care requirements. Imagine if we could, rather than serving just 5 percent of our population, with our most extraordinary, deeply human case managers, we could actually serve 10 percent or even going from 5 percent to 50 percent? Now you're not only serving people who are already diagnosed and dealing with various health care challenges and giving them personal attention, but now you're looking at people who have yet to be identified as high risk, and now you're helping them make better decisions to either prevent the onset of a later complication, or you're helping them manage it in a way that will significantly and materially reduce the development of that disease or those clinical risk factors.

And so, a 10x multiplier gives us that opportunity now, with the same clinical team, to impact over 50 percent of the population, rather than 5 percent. I mean that’s huge. That changes lives in ways that we've never seen before.

AB: I want to broaden things out and look at AI spending in general. People see headlines about these big companies, like Google and Microsoft, spending in the billions on AI investments. How would you differentiate the spending these large organizations are making, with the financial impact of AI for smaller organizations or individuals?

LR: Yes, building the data centers, acquiring the chips, the GPUs, the ability to build a team to be able to support these things, is extremely expensive. And that is the realm of, I don't know, 10 companies globally. It’s Alphabet/Google, xAI, obviously Microsoft, AWS (Amazon Web Services), OpenAI, of course. The computer power required is enormous. But that is not the game that most of us are in.

And I think for us at the enterprise level, at the consumer level, at the individual level, it's all upside, because we will get better technology, better models, richer capabilities, and then we will be able to continue deploying them.

AB: What has surprised you the most about the AI boom, especially these last few years with gen AI?

LR: I'm shocked at how fast it's moving. Six months ago, people had discounted Google in the AI race. They're like, “It's over. Google's missed it. They were the key players in the field, but they missed the window. OpenAI won.” Two weeks ago, Google came out with their own Gemini engine, and now everybody's like, “Oh, OpenAI is out, and Google's got it, and it's amazing. And they're changing the game.” And odds are, six weeks from now, there'll be another one of those events, and then six weeks later, there'll be another one, right?

And it's not just happening in the U.S., with the usual large companies. Because of the low-cost access of these solutions, there are many innovators that we've never heard about, six months from now, are going to do things that we never imagined possible. And if we did imagine them, we would have expected them to be five years from now or 10 years from now. And we're going to look at the price point. I mean, I'm the CIO for Regence and been buying technology for 30 years, and I'd say the solutions for the same problems that we are buying today, right, with AI are 10x less expensive, and six months from now, they'll probably be 20x less expensive. And so, the question is, how do you completely rethink your benchmarks, and your evaluation of what good is?

On one side, it's head spinning because it changes everything. On the other side, it's super exciting because you really can truly challenge everything and come up with different approaches.

Now, perhaps the hard part about AI is that you want to do everything, and by definition, as we all know, you have to prioritize to be successful. So there’s a lot of things we're going to leave behind, even though we know we could do better; and we're going to focus on, in Regence’s case, potential uses of the technology that really make health care better for our members, for our patients, and the people we serve in their communities.

That's our north star, and we're going to focus everything on, how do we provide our members better services? How do we make it easier for them? And how do we, in every way possible, use our experience, our professionalism, the human talent we have on our team, to make their lives better.