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Empower your staff, Optimize your systems and transform patient care. Join the revolution in healthcare technology with ServiceNow. Discover more at thisweekealth. com slash ServiceNow, where healthcare meets innovation.

Welcome to This Week Health. I'm Sarah Richardson, a former CIO and President of this Week Health's 2 2 9 Community development where we are dedicated to transforming healthcare one connection at a time. Our interviews in action are a series of interviews catching up with healthcare leaders throughout the industry.

Now onto our interview

(Interview 1)

Slow everything down and drive up costs. Enter agent ai. In this episode, we cut through the hype to explore how AI agents can simplify operations, reduce administrative burden. And deliver real productivity gains, no clinical claims, no fluff. Just clear strategies to help health systems break free from the paperwork trap and embrace a smarter future.

Mike, welcome to the show.

Mike Vipond: Thank you, sir, for having me.

Sarah Richardon: Well, and as a previous ServiceNow customer prior to joining this week Health, I can contextually say yes, you guys do cut through the spreadsheet and paperwork, I think fluff and nightmares that are out there. So I'm so grateful to have this conversation with you today.

Mike Vipond: There's a lot of that to be cut through in healthcare, unfortunately, so we're trying to do our part.

Mike Vipond: I've heard the phrase lately and I'll steal it here that with something like ai, people tend to overestimate the impact in the short term and underestimate the impact in the long term.

And so I think we're kind of at that phase with AI and what the potential of it is. So I think there's, I. Probably two myths. The first myth is people who think this is just gonna magically come in and solve all of the technology and process issues that we've been struggling with for the last 20 years, which is not the case.

And the second myth is that this is all fluff. And this is a fad and I don't need to pay attention to it. Neither of those is true. This is real. It is going to be game changing. The words may change. It was generative AI a year ago. Now it's agentic ai. We'll come up with some new terms. I'm certain but this is going to change and transform how health systems operate.

It's not going to do it tomorrow, but there are things that everybody needs to think about preparing for

[Mic bleed]

But recently we're seeing more and more about agen AI being different from the automation we already have in place because people are using generative AI all the time. Many people are in their day-today, workflows, but the agentic like being able to manage. Agents versus managed people or a hybrid thereof, how is that different from what people have already been thinking about?

Mike Vipond: Yeah, I mean there's kind of three categories I think of it's just pure process automation as something ServiceNow has done for a long time. There's generative AI and there's agentic ai. And I think of the difference between automation and agentic AI, the difference between baking and cooking for people who are either bakers or cooks.

My kids, you know, maybe they don't like spicy foods. My wife or I chain some ingredients than the recipe. You're outta something. So you pull something outta the fridge and you have to be a little bit more comfortable with ambiguity. So automation is like baking. You have to follow very clear pre-prescribed instructions and you will get a consistent result, but it doesn't deal well with any ambiguity or kind of changing the game in the middle. Whereas what agentic and generative AI both do a much better job of is how do you handle that uncertainty and sort of infer context and objectives that aren't explicitly stated and sort of fill in those gaps.

Sarah Richardon: And having run service desks for like more than 25 years.

Hospitals get stuck with spreadsheets, swivel chairs, and that happens in the finance teams. And I mean, you look across a hospital system and there are so many opportunities to automate or to use agen capabilities, and yet you've already alluded to the fact that we don't want to just automate a process that's not great.

Why do you see those as problems and how can you get in front of them by using something like ServiceNow?

Business day after the one big beautiful bill was officially signed by President Trump that's gonna cut Medicare by what? Over a trillion dollars. His healthcare is in a real pickle in terms of needing to simplify operations and needing to reduce costs. And the current technology landscape, the most health systems are dealing with is a major barrier for that to happen because it proliferates the silos that were in place at the time those systems was created.

Sarah Richardon: What do you see though as some of the ideal business workflows or even IT workflows for an AI agent to handle within a health system?

Mike Vipond: Yeah, I mean, there are a few key characteristics and from our perspective obviously ServiceNow's roots are in the IT space, IT service management, IT operations management.

What most people don't know is that we've already expanded well beyond the IT space. We're doing a lot around HR operations, hr service delivery legal supply chain finance, and we're moving into more industry specific workflows within the healthcare industry. And when we think about what are use cases that make a lot of sense for a company like ServiceNow to apply AG agentic the first is that it has to be a workflow that's incredibly data rich.

If that's really the case, it's just something that should be automated on the other end of the spectrum, if you have something that's wildly heterogeneous and it looks very different every time. That's probably going to be a little bit difficult for AI to handle, at least at the current state of the technology. It has to contribute to administrative burden and operating cost. It has to be a problem where the juice is worth the squeeze, and that's something that if you can do it five times better, it's kind of a so what for the system. And sort of maybe the obvious one is low clinical risk.

I think at this point you know, we are very focused on staying outside of the clinical realm, and I think most of the adoption of AI is going to be in operational administrative areas for the foreseeable future. I.

Mike Vipond: Yeah, so a big part of ServiceNow strategy is to help facilitate application rationalization. Obviously we provide tools to IT shops and CIOs to help manage their portfolio.

And we're also going to be expanding our own portfolio of healthcare solutions into areas that's going to directly help to rationalize applications where the ServiceNow platform may be a better tool for the job. So a couple of things that AI in particular is going to help with. One is just making it easier for people to develop solutions where there doesn't necessarily need to be an additional point solution or health systems are not getting value outta some solutions to build that within another platform like ServiceNow or Power Apps with Microsoft or other providers that are out there.

But it's more about how do we use AI to not let that. Fact of having some disparate technologies be an inhibitor to innovation. So take an example of a time and attendance system, UKG, the predominant player. It wouldn't make a lot of sense for someone to try and recreate all of the business logic and payroll within a system like UKG, but how can I use AI to make it easier for managers and employees and executives to interact with the data within those systems?

Sarah Richardon: And it's easy to get distracted by the shiny AI object or solutions that have AI components built into them, and they get released accordingly.

When you do the evaluation of ai, you're in a hospital system and many of these hospital systems. Have governance committees that have either been spun up separately to handle ai or they have an AI component of their new governance systems. So what are red flags that you recommend systems look for when they're evaluating an AI solution for the business or even the IT side, perhaps even clinical when it comes to healthcare?

Mike Vipond: Yeah. I think it's surprising having been on the vendor side my entire healthcare technology career, and having worked in the AI space for a while now. That you rarely get asked the real tough questions. we're fortunate to be in an industry where everybody's very nice and polite and very mission driven.

What data are you using? What are you using to train the data? What data does it need to access from my own systems? What will happen with that data once it's incorporated into your AI,? And well run, companies will have very simple, straightforward answers to those questions.

And if they can't answer them very simply you know, that's something that you wanna make sure you understand before you decide to partner with somebody.

Sarah Richardon: You've recently joined the ServiceNow team. For all, many of the reasons we've shared the ability to do all of these different actions inside these systems.

What's a great example of how agentic AI has already helped a hospital or health system? Save time or money that you like to share when you're having these conversations with customers?

We have about a hundred AI agents in production already. We have another thousand or so that are going to be in production. And we're also really mindful of creating an ecosystem where our customers can create their own. AI agents will have interoperability with AI agents that have created through.

Google or Microsoft or other technology providers that are out there. So the easy places to start where we're seeing value today is things like, I have an IT incident. How can I have an AI agent who is automatically researching that incident, finding similar incidents that have happened in the past, the kind of

So that's a, I would say down the middle of the strike zone kind of core IT, application of agentic that's already being used by customers today. We're seeing other areas that are getting into more healthcare specific use cases. So something that we've been working on is a product called Care Team Operations.

And the premise of it is basically that a lot of time is spent by frontline care team members. On tracking and hunting and pecking nonclinical tasks and requests. So I have a patient who had cold food yesterday. How do I make sure that the dietary nutrition services addressing that I have a device that's broken in the room.

So it saves time for care team members. It saves time for the support services because we are using all the historical data to kind of propose and recommend what we think needs to be done and then having it all happen within a single platform like ServiceNow.

I'd say a third of the work that techs do doesn't get recorded, and then. Probably that equal amount of things that are broken or wrong don't even get reported because no one wants to take the time to log into the system. All of a sudden you're removing all of those friction points and you think about how much more eloquently and efficiently your system can run, how much better your patient care is because things are working because you made it easy for people to fix them.

Mike Vipond: Yes, exactly. it's Making things that should be easy, actually easy in a perfect world, and giving time back to our frontline caregivers to actually spend time with patients. So much of their time is not spent with patients. It's spent on dealing with all the administrivia.

Sarah Richardon: And I appreciate the ambient listening capabilities associated with ai. I also appreciate the fact that same ambient listening can understand food. Cold TV's broken and X, Y, Z also needs to be addressed and just feeding what it needs to feed, which is maybe a little bit of the two B architecture that is out there.

I also hear so often, Mike, that systems are just overwhelmed, either by disconnected tools or where to start with some of these things. So A CIO just had AI thrown on their plate, and you wanna make the right. Decisions or share the right ideas with your board, with your peers, C-suite, et cetera. When you don't know where to start, where do you begin?

Mike Vipond: you can't ignore the hard work. And most CIOs are also in a position of having to show some results sooner rather than later. because their CEO and their board knows about this is in many cases a board level topic. And they can't tell the CEO and the board that it's gonna take five years to show real results.

Easy down the middle of the strike zone use cases that I can apply today. They're gonna show real value and they have to be good about setting the expectations. I mean, there's not a lot of really, if we're being honest, agentic use cases that are gonna go save millions and millions of dollars right now.

A lot of it for now is gonna be productivity savings. Over time, I think we will get to a point where we're seeing real hard tangible cost savings at a lot of these use cases, but we're still in the first inning of what's gonna be a very long game.

Sarah Richardon: And so if you are thinking a couple quick wins I'm A CIO I call you.

I have your product, but I'm looking to leverage it more effectively. What are a couple of things that you would say, let's go look here now.

So I was on a conversation with you know, large regional health system earlier today that's going through a rollout of EPIC to some newly acquired facilities. So they're anticipating a massive volume of IT tickets when that system goes live. And so we're talking to them about, Hey, how can we use some of the automation tools already within our platform to drastically reduce the volume of those tickets drastically reduce the time that it's going to take your clinicians and frontline employees to get resolution when they run into issues when that system goes live.

So, I mean, that's a very easy example. There are other ones from an HR perspective

As long as you have. Some of the basic infrastructure in place, and ServiceNow has tools for this sort of thing as other companies do. You can apply generative AI very quickly. That's helping to make that an even more seamless experience for employees and then make it more efficient

Sarah Richardon: I appreciate that because often you'll buy a platform and you use X percent of its capability, and being able to pull in all the components that make sense for your organization is really key. Especially now with the advent of AI really pushing things, I think, faster than they ever have before, but how do health systems prepare for this real world impact?

Mike Vipond: You alluded to part of it earlier, which is governance. I mean, governance is part of the foundation of doing this right. And I think most health systems are doing something. So then there's been a lot of good resources and webinars already out there on, you know, what are people doing from an AI governance perspective.

But that really needs to happen first. I think AI is going to force everyone to really think about. Their data foundation. Again, AI feeds on data. So if your data is messy, it doesn't have to be perfect, but it can't be like my 9-year-old bedroom either. It has to be somewhere in between or you're not gonna get value out of AI because you're simply not going to have the data that's going to be able to feed it in a way that's actually going to get real results.

And so just putting AI on top of your old crappy broken processes is not going to accomplish anything. AI will add value by letting you totally reimagine how certain workflows are being done. So how are you going to do that with your current applications? And if you can't answer that question, you need to think about a different strategy from a workflow perspective because you have the best data, the best AI in the world.

If you can't actually put that into action through workflows that are probably different than your current workflows, then you're gonna be stuck.

Sarah Richardon: I always tell people, Mike, it's like, use AI as a way to help you get there faster in some cases. It's not going to replace the need for humans to still have human connection.

Mike Vipond: Great point.

I think with any technology in AI is probably creating more fear along this lines. It's not about replacing human connection. It's how do we amplify the human connection and create time for more of the human connection. You think about what it's like to be a manager within a health system. People get into management because they wanna spend time with their people.

They want to coach people, they want to mentor people, they wanna spend time with patients. And what do they end up doing? They end up spending all the times in spreadsheets and different systems, and dealing with different requests and stuff is always five times harder than it should be. So how do we use AI to take all those things off their plate that they shouldn't have to be dealing with so that they can focus more on human connection?

[Mic bleed]

Sarah Richardon: I mean, think about when you actually had access to like spreadsheets early on. You were like, this is really cool. Like I don't have to type in 10 key all of this stuff anymore. I can actually write formulas inside spreadsheets and yes. I came from the days of a 10 key, so there you have it. Well, , Mike, it has been such a pleasure. Thank you for helping us demystify what is real and what is possible when it comes to AI in healthcare. It's clear that this isn't just about tools, it's about transformation. We appreciate your insights on how health systems can move forward with clarity, confidence, and a lot less swivel chair time.

Thank you for tuning into our executive interview with Mike Vipond from ServiceNow. Mike, thank you.

Mike Vipond: Thank you, Sarah. This was great.

If you could do that, we would appreciate it. Thanks for listening. That's all for now.