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Becker’s Healthcare Podcast
How AI Governance and Use Cases Will Reshape Health Systems in 2026
00:11:54
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- [00:00]
A
This is Scott Becker with the Becker's Healthcare podcast. I am thrilled to weekly get a chance to visit with Molly Gamble. Molly's the vice chair or vice president in charge of editorial affairs at Becker's Healthcare long term editor in chief, and we visit with Molly regularly to talk about what stories she's watching closely in healthcare. Molly, let me turn it to you and ask you, are there a couple stories that you're watching most closely currently?
- [00:30]
B
Yeah. Thank you so much, Scott. It's good to be back with you. I had one story in mind that I kind of wanted to go a little bit deeper on today, and that's this predictions piece that was published early this week about healthcare, AI in the year to come. So in 2026, just trying to talk to some really smart and bright leaders in the field about how the conversation about AI and healthcare could change in the year ahead. It's certainly been a big focal point for 2025, and I think as a journalist and a communicator, you know, something you always want to look to do is make sure you're not relying on the same tropes or same jargon or mottos for too long after they're useful or effective. And I think that's something that's healthy to do at the start of a new year. So there were a lot of interesting points raised, Scott. Predictions can be tricky sometimes. You know, they come more easily, depending on what the topic is than others. But there were a few that I wanted to highlight for listeners because I thought it does signal, I think, a healthy way to move the conversation forward about AI that already we hear from executives all the time. You know, AI hype, AI fatigue, those things are real. So this struck me as an opportunity to kind of pause and then look ahead and talk again. Like I said to some, some really bright leaders about what they're anticipating over the next, you know, at least couple of quarters in 2026 when it comes to this form of technology.
- [01:52]
A
Thank you. And tell us what are some of the things that you're hearing. Talk to us about what you're hearing and what people are saying.
- [02:00]
B
Yeah. One of the bigger ones, Scott, was that this AI governance will really move from what's kind of been a backroom exercise or backroom checkbox to much more of a strategic engine in health systems. This is a really important one. You hear a lot about governance, but when it comes down to it, the resources health systems have for governance are relatively thin. In, in a couple years ago, only 16% of health systems had enterprise wide governance strategy for AI in in 2025, the average IT budget allocation to governance it still was only about 4%. So this is something that as one expert had told me in my interviewing from, from class, you know, he said that some systems have treated governance like infection control in the past. And there's anticipation from leaders that this will become much more vital, much more urgent, much more visible. It's going to become a way bigger part of leadership and also technology leadership and IT leadership, but also just more broadly at the CEO, cfo, COO level too. So there's anticipation that there'll be more oversight bodies from the state level, accrediting agencies, also federal regulators. But rather than being reactive to those external forces, there's also anticipation that health systems will really start to beef this up on their own and again make it more of a strategic layer of the health system versus what could be kind of a checkbox exercise.
- [03:28]
A
I think that's so fascinating and I think as AI starts to have so many different use cases and so many people throughout systems start to work on and utilize test cases, I assume that systems feel like more and more they need to have some guardrails around, what that's going to look like and what that's going to mean. And so it makes a lot of sense because you, you could see that where you start to see this evolution of so many different use cases and something get out, out in front of itself and going differently than expected. And there's going to be tests, there's going to be challenges, but sort of knowing what a system has decided to test and try and where the risks are seems increasingly important. Fascinating actually.
- [04:15]
B
I thought so too. And there was a lot of excitement about what AI will start to do meaningfully in the revenue cycle space. So you know, denials, these have long been one of the industry's most expensive like also just a demoralizing form of waste for clinicians and for health systems and patients. There's a lot of excitement from leaders about how AI will begin to not just make coding easier or CDI or denial management, but maybe eliminate some of those things that could trigger fights with payers before the fight is even started. So Dan Greenleaf, he's CEO at Dooley Healthcare here in the Chicagoland area. Scott, I know, you know, Dan, he, he even told me pretty black and white terms that he anticipates his revenue cycle management spend going down by half. I don't think that's in 2026 alone, but it'll start to move in that Direction. He said that the tools are going to be so sophisticated, there will be more alignment, that this does not need a prior authorization. This episode of care, this treatment should not be denied. And that AI's ability to kind of eliminate some of those payer provider fights that have so for so long defined the revenue cycle space will really be a line in the sand and a big sea change. So we'll keep an eye on this. 2026. We're seeing innovative things with AI between providers and payers. You might see denials begin to shrink, not go away completely, and not because payers and providers suddenly agree, but just because they may have fewer administrative reasons to disagree in the first place.
- [05:49]
A
That's fascinating. We do hear sort of on the other side of that, just this increase in this arms race between payers and providers over so many of these issues. So it'll really be interesting to see how it actually sorts out and whether at some point it is machine stocking to machines and resolving more and more of it versus one machine saying no to another machine and not resolving more and more of it. I guess we'll, we'll see how that plays out over the next couple years to see if hopefully Dan's prediction is more right than wrong, that it gets closer and closer versus creating more of a burden for systems. I feel like right now the health system side, they feel like they're trying to keep up on the arms race to cooperate or compete with the payer denials and authorizations and maybe we can get to a world where they actually talk to each other in a more positive way and make things easier to resolve. It's fascinating to see if that will be the case.
- [06:49]
B
And Scott, I'm actually interested in how what we'll see, what we'll start to see from some of the integrated systems that have both, the payviders, if you will, those that have both health plans and then the provider arms, I think they could be a real hotbed for how that plays out. The other trend I wanted to point to is just how much clinical decision support will evolve over this next year from AI. So for a long time like CDS has been seen by what some experts described as like a glamorized search. It was just like a really high functioning search engine that was part of the ehr, that was part of the patient's chart. But now I think there's a lot more anticipation for AI to almost be a partner versus a tool for the clinician. So start to identify different historical trends, identify medication errors, tee up orders support diagnostic reasoning in a much more meaningful and robust way. So there seems to be a lot of excitement about this guy. I think the leap from being a really good search engine to then now be more of like a reasoning partner, it could be one of the bigger shifts that end users in the clinical world start to see from AI in the year ahead. And it seems to be there's great appetite for it too.
- [08:02]
A
No, I think that's right on. And we hear so much about that, this movement towards, you know, we've heard for years so many of the use cases in the revenue cycle, the administrative side, and then obviously this past year or two, we've had such an evolution of the use of it in the ambient listening stage to try and reduce the amount of documentation that doctors and nurses and clinicians have to do. And now you're seeing this next evolution where you're starting to see real use cases on the diagnostic side and as you say, sort of clinical decision support systems. And I think that's exactly right. And the hope is that again, these are able to handle a lot of sort of, to almost triage things, so physicians and clinicians could focus on the more complicated and the more challenging and the bigger problems and let the systems triage some of the issues that they can.
- [09:01]
B
And finally, just the last one I would point to, and this is what probably excites me the most in conversations with leaders, is, you know, there's all these internal ways AI will improve operations and improve finances, retention, employee and patient experience. I think the patient experience piece is something that probably doesn't come up enough. And then not that patients will be doing homework about how systems are using AI or what solutions or when and how their pilots went. You know, that's unrealistic to anticipate that level of engagement from patients. But will there be more noticeable improvements to their experience that start to really add up and inform patient choice? So if you've got a patient who's in a market and they've got a couple different options for where to receive care or procedure or where to go, will AI start to work as intended and give them time back, you know, fewer headaches, less complications in scheduling, all the things that for so many years we've gotten really accustomed to being complicated, slow moving and tedious will start to make a better experience for them overall, where it'll begin to build loyalty, or they'll start to see systems maybe in different ways. Those that are investing in a better experience for them thanks to AI, or those that maybe are just continuing on as business as usual. So, Scott, I think that's something that. It raises a lot of questions for me. I think this is something that for years and years we've been talking about patient experience. And it seems like if AI can start to really tip the scales towards the meaningful improvements for patients, it could be exciting to see how that turns into more of a movement versus just like a, you know, helpful side effect of this form of technology.
- [10:39]
A
Yeah, that's. That's simply amazing. Literally. And what's so interesting is even about, even with the patient experience, both systems, what they'll do, but also the ChatGPT, as you go to ChatGPT and say, which system should I go to for this illness or this challenge or this problem? Who's the. Who's. Who's the best for it? Who. That's fascinating. Literally fascinating.
- [11:00]
B
Yeah. Do you do that, by the way? I haven't done that. Have you tried that, asking it that?
- [11:06]
A
I've not done that, but I'm using more and more of it for just all kinds of things. And I'm finding it to be crazily helpful in so many ways. You're just kind of constantly using it in different ways almost daily now. And I could see where people start to use it for, if not diagnosis or to decide, okay, who should I go to for this or that? Like you used to go to Google for it, right?
- [11:28]
B
No, I think it's a great. You just help me appreciate it. You go further, it goes further upstream than just what they experience in scheduling. Right. It's like even just how it'll be used to inform where they try to schedule. So I think it's a really great point, Scott.
- [11:40]
A
No, a hundred percent. Molly, I want to thank you as always for joining us today on the Beckers Healthcare podcast. Always. Fantastic. Thank you so much for joining us.
- [11:50]
B
Thank you so much for having me.