📍 Today in health IOT, where is the ROI for AI? CEO's struggled to find it today. We're going to take a look at that. It's a cio.com article. My name is bill Russell. I'm a former CIO for a 16 hospital system and creator this week health instead of channels and events dedicated to transform healthcare.

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One last thing, share this podcast with a friend or colleague use it as a foundation for daily or weekly discussions on the topics that are relevant to you. And the industry. A form of mentoring. They can subscribe wherever you listen to podcasts. All right, let's get to it. Where's the ROI for AI. CIO's struggling to find it. Nearly half of all AI leaders question how to estimate or demonstrate the value of AI related technologies. And for good reason, based on early implementations at many companies. And so my guess is this is, this feels a little bit like when we brought in the EHR and we didn't really know what we were doing, we were figuring it out. And we learned a bunch of things in it.

One is let the problems lead. The technology was one of the things we learned. Another thing we learned was training was so important. And it feels to me like we are making decisions and moving into this. Maybe without the proper preparation. Now I'm not saying we shouldn't move fast.

I'm not saying that because I've said that on several occasions. But I am saying move with, at the pace that your organization can handle. And so this comes from a recent Gardner survey of more than 700 it leaders at organizations that have adopted or plan to adopt AI nearly half the respondents pointed to challenges with showing its value. And they talk about all these experiments and a bunch of quotes here.

I'm going to skip some of these here. They need to be shown how to really use the tool in order to use it effectively. One of the quotes, a chisel in the hands of a trained professional. Can create amazing things, a chisel in the hands of an amateur. Can be a lost opportunity. That is absolutely true. The AI market is still developing and some companies are adopting the technology without specific use cases in mind.

He adds. Kane has seen companies rollout Microsoft copilot, for example, without any employee training about its uses. I found very few companies who have found ROI with AI at all this far, he ads, most companies are simply playing with the novelty of AI still, and they go on and talk about the Paris things. The nice thing about this article is they then lay out some things first, find a use case. The Gardner survey found gender VI to be the most adopted AI related technology with 28% of the respondents saying their organizations had rolled it out close behind where machine learning and natural language processing. Gardener expected the concerns about value given. That it was also a top barrier to entry in similar 20, 21 survey. Says, laner Ramos, a Gartner analyst focused on generative AI tracking in demonstrating ROI. Can be difficult for many use cases.

He adds Gardner recommends. CIO is thinking about deploying AI to first consider potential use cases. Establish metrics to measure value and run pilot programs before launching large scale projects. The second highest barrier to adopting generative AI specifically. Was the ongoing cost. Amen to that. As the number of users of generative AI increases, some organizations are surprised by increasing costs.

Don't be surprised. Your costs are going to increase. The reason that the partners are putting it in there is because they see that they're going to be adding value. Now, part of why they're putting it in there is to make sure that they stay ahead of the curve and do not become obsolete. Obsolescence is. Terrible in software.

It is not kind to those that allow their software to become obsolete think oh my gosh. Ah, man, there's so many cases. I'm trying to think of the old spreadsheet that was like Borland had something called. Quatro or something like that. No longer exists. Lotus 1, 2, 3, no longer exists.

You get the picture. Obsolescence is not a, is not kind. To software. And so they're trying to stay ahead from that perspective. The other thing is they're trying to continue to add value. Most of them are publicly traded companies. They have to continue to drive a number. After every quarter.

Okay. Tracking the value. What. Their next item. So identify the use cases, track the value. One company that has entered a, has embraced AI in a thoughtful way is C H, C N H industrial, a farming and construction equipment manufacturer, CNH. Uses AI and equipment health monitoring systems, enabling equipment owners to get notices about possible maintenance issues.

The company has also built an AI driven chat bot that gives service technicians, instant access. To equipment manuals and repair information. Now, instead of having to go to PDFs, the three ring binder and pull out a big book, they can literally say, Hey, I'm working on the And tractor and I need to replace an oil filter. They can automatically pull up the page with the illustrated instructions and they can either do it. On their phone or they can send it to a printer.

However they want to do it. Interesting start with the use cases, then track it. So with the service technician tool, we had a very high NPS score for those that have utilized it. NPS is one way to go. As AI tools get broader adoption, we would expect to see global NPS from our dealers go up these efforts to measure the value of AI are important.

He adds it's very easy for organizations to be enamored with new tech when they don't have the hard outcomes they're trying to strive for. So measure. So it's really only those two things. I was hoping to see more at the bottom of this article, but first find, use cases and then tracking the value. I would say, as I always say in these AI things. Get these kinds of articles in front of your named group within your organization, your governance group, whatever you have that is. That is staying ahead of this, your early adopters who are who are looking for use cases.

They are looking at the challenges of adopting AI. They are looking at training. They're looking at literacy. They're looking at. Policy and governance. And they are going to be the ones who identify those use cases, especially within healthcare. Hopefully you have that group identified named, hopefully they are. Staying ahead of the curve.

I hope you, as healthcare leaders are involved in your healthcare leaders are involved. I would say for anybody, who's a CIO right now, I would have a deck. And that deck would constantly be updated, but for the most part, I'd have a training deck that I would do for any kind of group that wanted to have me talk about where I was going. I'd be able to talk about what we are seeing as a technology, what we are seeing in our healthcare industry. What we are seeing as some of the early use cases within healthcare, I would also take a look at. If I thought about an outline, I'd also take a look at what we are understanding to be solid use cases. And I would probably talk about the challenges with the technology. How they are adapting. New methods to address those challenges within the technology. I wouldn't get too techie on it because I would want this to be something I could do pretty much at the drop of a hat for any group. An AI 1 0 1 for healthcare is what I think I would put together. And be ready to give.

I don't know. Maybe I will put something like that together. Who knows. Anyway. Hey, that's all for today. Don't forget, share this podcast with a friend or colleague, use it as a foundation for mentoring. We want to thank our channel sponsors who are investing in our mission to develop the next generation of health leaders. Notable service now. Enterprise health. Parlance certify health. And 📍 Panda health.

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