Today in health, it nine actions, a CIO CTO. I can take with regard to generative AI. My name is bill Russell. I'm a former CIO. For a 16 hospital system and creator of this week health set of channels dedicated to keeping health it staff current and engaged. We want to thank our show sponsors who are investing in developing the next generation of health leaders.

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Stand, click on that to give today. We believe in the generosity of our community. And we thank you in advance. All right. As I said, yesterday, I came across, it seems like McKinsey. Went to all of their people and said, we need as much information as we can on generative AI. I know this is happening at Deloitte. I know it's happening.

At Accenture as well. This is a foundation. This is a disruptive moment in every industry. And all of these. , all these consulting firms and, , management consulting firms. Are trying to figure out where it's going to go so that they can help to lead many of their clients in that direction. This was an interesting article. I liked it because it's a.

, it's a guide CIO's and CTO's can take nine actions to re-imagine business and technology with generative AI. I'm going to give you those nine. I'm not going to go into much detail. You can read the articles. They're all on the mckinsey.com website. So here goes hardly a day, goes by without some new business busting development related to gender VI surfacing in the media.

The excitement is well-deserved McKinsey research estimates, generative AI could add the equivalent of 2.6. Trillion or 4.4 trillion of value annually. CIO's and CTO's chief technology officers have the critical role in capturing that value, but it's worth remembering. We've seen this movie before new technologies emerged the internet, mobile social media.

That set off a melee. Of experiments and pilots through significant business though. Significant business value often proved harder to come by. Many of the lessons learned from those developments still apply. Especially when it comes to getting past the pilot stage to reach scale for the CIO and CTO.

The generative AI boom presents a unique opportunity to apply these lessons, to guide the C-suite in turning the promise of generative AI. Into sustainable value for the business. Through conversations with dozens of tech leaders and an analysis of generate generative AI initiatives and more than 50 companies, including our own.

We have identified nine actions. All technology leaders can take to create value, orchestrate technology and data scale and data scale solutions and manage risks. For generative a I, and they have a sidebar really cool terms. I'm going to take a drink.

All right. You're ready. Here are the nine things they say a CIO CTO can do. To help their company to make this move. Number one, move quickly to determine the company's posture for adoption of generative AI and develop practical communications to. And appropriate access for employees. Okay. In other words, create the right communication about it and give people the ability to touch it and play with it.

Number two re-imagine the business and identify, use cases that build value through improved productivity. Growth and new business models develop a financial AI capability. That can estimate the true costs and return of generative AI. So in other words, have your business models in place to make sure you're measuring the ROI to determine the value.

, if you are going to imagine use cases, You can imagine them around productivity, around growth, around new business models. So those are the three things. That they say to focus in on. Number three, reimagine the technology function and focus on focus on quickly building generative AI capabilities in software development, accelerating technical debt reduction, and dramatically reducing manual effort in it. Operations.

Okay. So specifically one of the areas we can control, we have absolute control over is the it function. There are a lot of applications for generative. Yeah. And the it function. Look at those first, be a leader lead by example, I think is a good way of looking at this. That's not the only thing they say here that, you know, tech that is going to be a problem.

As you move forward, you have to educate these models. That data has to be right. So you have to look at those things and make sure. That your data's ready, that you are sunsetting older applications, that applications that aren't going are, aren't going to be able to take advantage of the. , AI capabilities that are, , on the horizon. Number four, take advantage of existing services or adapt.

Open source generative AI models. To develop proprietary capabilities, building and operating your own generative. AI models can cost tens of hundreds of millions of dollars, at least in the near term. I don't think that's the direction we're going to go in healthcare. I think we are going to tap into any number of the generative AI models that are out there.

We're going to go to. , Microsoft, if we're going to tap into open AI, we're going to go to Google. If we're going to med Palm and the rest of the models that are over there, Google Bard and whatnot. And I believe Amazon has launched some generative AI. , capabilities as well. So you have a lot of different directions in the large public cloud providers.

And a service providers that you can go to. And I think that's the direction we're going to go. I don't foresee. Too many health systems building out their own. Generative AI capabilities, just, , just my 2 cents. But I think it's worth more than 2 cents. Number five. Upgrade your enterprise technology architecture to integrate and manage center of AI models. Okay. I say this on the show a lot, and sometimes people look at me and say, what do you mean by architecture?

What I mean by architecture is the foundation by which your data, your information, your network, all the things, how they flow across that system and how they interconnect. And when you architect things, when you have an architecture, it thinks about how things piece together, how they flow together, how they work together to create value for the business.

And a lot of people in it, do not think from a business perspective. And so when I say architecture, I mean, step back. Look at how all of these systems, not just the one you're buying today, but on all of these systems that how they work together. I was talking to a group of people today. We were talking about how we're, you're still making the same mistakes.

Of putting in siloed systems. We've got to get out of this mindset. You've got to just step back and say, okay, we're putting this into a room. What are five or six different ways we're going to want to use? This same technology in different ways in this room. What are some other functions we're going to need in this room, so forth. And so, I mean, architecture takes into account the big picture. It takes into account account, the flow of information, creating value from that information, moving that information to the point of care. It.

Takes into account. , X expandability working with partners, partners that you're not working with today. And how are you going to do that? Architecture allows for that. It's, it's bigger thinking than just individual applications. Sorry, little side note. , number six, develop a data architecture to enable access to quality data by.

Processing both structured and unstructured data sources where we have gotten better over the last decade of getting our data in order, it's still a little. , let's say muddy. But it's not as messy as it was a decade ago, but that depends. Have you put data governance in place? Have you pushed this forward? Have you pushed your data capabilities forward? Have you matured your data capabilities?

To the point where if you were asked to educate an AI model, On your, let's say your business operations, let's say you wanted to use generative AI. To get insights on your business operation. Not your clinical operation, your business operations. So it could look at. You know, where you're seeing patients, how many patients and those kinds of things, and you can give a capacities and then you can ask a question. You can query it based on the information that you gave it. Do you have that information?

Is it information that you could readily get to an feed into a model? I want to keep going. Number seven. Create a centralized cross-functional gender VI platform team. To provide approved models to product and application teams on demand. I think we need this capability within it. This is going to be a foundational.

, capability. Much like your network team, your cybersecurity team, you're going to have your generative AI team. And they're going to understand how to train the models. They're going to understand how to feed them. They're going to understand how to safeguard the models. They're going to understand how to.

Provide some transparency into the models and how they are interacting with the data and those kinds of things. You need those capabilities amongst other things, , you know, education. , prompt engineering. You name it. , it's all falls into that category. Number eight, invest in upskilling key roles, software developers, data engineers, ML ops engineers, security experts, as well as the broader non-tech workforce. But you need to tailor the training programs by roles.

And proficiency levels due to the varying impact of generative AI. You should be upscaling almost immediately within your it team. If I were a CIO today, I would be looking at every area in asking the question, how is AI, how is generative AI specifically? In this case, but how is AI going to impact.

This area. How is AI going to impact my cybersecurity operations team? How has AI going to impact. My, I don't know, my disaster recovery business continuity team. I don't know the answer to that question. I'm just, I would be asking that. And then saying, what capabilities are they going to need? A year from now, what do they gonna need six months from now? Where are they going to need a year from now? What are they going to need three years from now? And I would create that.

That matrix. We did this with the cloud. We had a matrix that essentially said, look, we're moving to the cloud. These are the capabilities that people have for on-prem today. These are the capabilities they're going to need to have within three years. And these are the capabilities we are going to have and develop. And we had levels of proficiency across those things.

We had a really cool chart. That people could look at and we could have conversations between the managers and the employees. I think you do the same thing on generative AI, quite frankly. Number eight. Invest in out. Upskilling, I did say number eight, number nine, evaluate the new risk landscape and establish ongoing mitigation practices to address models, data, and policies.

Not exactly sure what that is. Let me go down in the article a little bit. See if they can. Educate me a little bit on what they're talking about. And again, this is a much Largo longer article worth taking a look. Tenet of AI presents a fresh set of ethical questions and risks, including hallucinations whereby the generative AI model presents an incorrect response.

Yeah. And actually I was going to, I was going to make this point. Within healthcare, you're going to want an AI governance team. You're on an AI. , governance team that includes risk. That includes, , quality. That includes a business. , you know, because there are different businesses that you can start to think about different ways of delivering primary care.

, I had a. Tyler Davis on the show. And we talked about. The potential for having 50% of primary care delivered via a silicon-based workforce. Within the next five years. Think about that. Think about how much, , care could potentially be delivered in between visits. Reducing the overall, , load on the, , organization. But anyway, governance is really important. So Hey, this article does have a lot in it. I highly recommend it. I will put a link to it.

And the show notes and you can take a, take a look at it. Think it's really relevant. Keep in mind that this is not healthcare specific. It is more business specific. We are going to see this take off in other industries before we see it take off in healthcare. It's just the nature of healthcare. , plus healthcare is right now in a.

, what I would call a serious. A down cycle from the financial standpoint. So. I don't see anything revving up and moving. , too quickly, although I will say that the leaders. Have put their governance in place. They have put together models. For how they are going to, , upscale, they have talked about.

, different areas where they are going to pilot these things. So don't fall too far behind. Keep keep, even if you are. , financially strapped or whatnot sometimes when you're financially strapped, you're not doing as many projects, great time to upskill your team. Great time to, , bring people in from the outside who are going to educate your team on the possibilities and to give them the opportunity to play with some of the technology.

So anyway. , that's, , that's all for today. I want to thank you for being a part of the channel. And if you want to help us out, one of the ways you can do that is let somebody know that you're listening to the channel. And tell them to listen as well. They can find us on our website this week off.com or apple, Google, overcast, Spotify, Stitcher, you know, anywhere that you listen to podcasts.

We want to thank our channel sponsors who are investing in our mission to develop the next generation of health leaders, short tests and 📍 artists. I check them out at this week. Health. Dot com slash today. Thanks for listening. That's all for now.