A (4:54)

Yeah, absolutely. So you had pandemic. You have the AI stuff that you mentioned. And then Nancy Rainasek, if I remember right, she was, Wasn't she there for more than 20 years or something like that?

B (5:05)

She was an auditor with the state prior to her time with dir and, and with. In. In cyber.

A (5:12)

Right. So in any case, yeah, big, big stuff happening in the world. And then longtime IT officials moving on to new pastures. So as the state's former AI chief, I'm curious, does AI play. Do you think that experience has changed how you'll address the technology? Does it give you any insight? Does it have any effect on you?

B (5:36)

You know, I think this is something that I've been asked similar question about and thought a little bit about. I think, yes, but I think it's more about just having been a technologist for, you know, the last 33 years. I don't know, you know, the full history of this position, the executive director position here at DIR all the way back. I can't say that there's Never been a technologist, you know, in this position, but it's, if, if there has, it's been, it's been a while. And so I think that alone will, you know, will have something to do, will play a role in, you know, definitely how I think about, you know, the state's IT challenges as, as we go forward and how technology can be used as an enabler, as a business enabler there. But yeah, I don't think it's, it's a stretch to, to, to think that, that there might be a little bit of a, of a direction adjustment in how we're going about things here at dir. Just with having, you know, a little bit of a different perspective and background on things. I think, I think AI is going to play, you know, where we're headed and what we're focused on going forward as a new technology that really there are a lot of expectations there right now in the area of AI and what IT maybe will be able to do for entities, for government entities, local government entities, state government entities, and how IT can help us better serve those that we are here to serve. So we'll be looking to implement and integrate those technologies where we can in a responsible way, safe and secure and responsible way. And it brings a new or at least or an elevated focus, I should say not new, but an elevated and increased focus in the area of data quality and data reliability, which we know is essential if we're going to get the most out of AI technologies. So I think there will be an ongoing increased focus in the area of data. You know, there's always, I think, been those of us in IT departments of an organization or the IT organization for state government. It's modernization and business enablement through digital transformation is always a focus. I think the term digital transformation is something that seems like a little bit of a newer term, but it's really what we've been doing in IT for the extent of my career and looking for ways to use technology to improve what we do in the business side of things. And we'll keep doing that here at DIR for the state.

A (8:40)

Right. You mentioned the need to step up on data for the purpose of AI and that's one of the things I wanted to ask you about later, but I'll ask IT now and your state IT strategic plan. IT notes that poor data quality is a challenge that the State faces and you're by no means alone on that. I've heard that from a lot of CIOs and, and I think state data chiefs have been complaining about it even longer. And now they're all saying, I told you so. But how, how do you plan to address that? Is that a, is that a long term thing you have to chip away at? How do you, how do you deal with that?

B (9:26)

Yes, I think it is a long term thing in that it's not a problem that will be solved overnight. And where we'll, where we'll do this and say, okay, that was, you know, job well done, you know, with data. But we will also chip away at it, right? And we'll chip away at it in a way that tackles, you know, chunks for given use cases, for given AI use cases that we need. Right. So we don't have to solve, you know, the data problem overnight. We need to solve the data problem or the problem with the data that we need for a specific use case, you know, sooner rather than later. So we'll be working as a state, you know, we just actually today, earlier today had our quarterly data management advisory committee, or what we call DMACC meeting, you know, where all of the data management officers from all the Texas state agencies, you know, get together and coordinate their efforts in their, in their individual agencies as we work to improve data quality. We are, we're active in NASIO or the national association of state CIOs and one of their communities of practice is the five that they focus on are those of the chief data officer from the states and our chief data officer, State Chief Data Officer Neil Cook, is one of the leads in that group for nasio. And because we are out front in that area, you know, I think as far as states go, we've got a long way to go. But I do think we're out in front. And Neil is, you know, does a lot to influence the programming there, you know, for all of the other states that participate in NSIO as well. So, yeah, we've got a lot of work to do with data. I do think we are on a good path there and I think there's a lot we can do there with data. You know, I mentioned the groups that we have, the group that we have with the DMACC and some guidance. You know, we regularly put out guidance. My hope in now being in this role is, you know, one of the things that I think, you know, I talked about some, some ways that my background in it might influence a little bit in how, how we do things at dir. First, I'll say, you know, at dir, we do what we're, you know, statutorily, you know, authorized and directed to do and we try to stay and do a good job of staying, you know, within those guardrails. But, but within that. And, and, and to the extent that we can show a need for more, you know, I do think there are some opportunities for us to really do more from a shared services standpoint. We've got, you know, a number of state agencies in Texas, the large, the larger of the group, the top tier from us from a size standpoint that have their, you know, the expertise and the personnel and the funding and you know, they can handle things, you know, on their own. But we've got another, you know, large group of agencies at the midpoint and lower, small, medium sized agencies that, you know, aren't in the same boat from a resource and personnel, staffing and expertise standpoint. And you know, we're not, you know, rather than try to do these things, you know, 50 times, you know, I think it makes a lot of sense to do, you know, some of these, some of these things that need to, need to happen out there with some of these agencies in a, you know, more of a shared services model where we at DIR are providing some data management services for agencies and that, you know, there are a number of services that I think that we can offer in addition to what we offer now on top of the traditional guidance, if you will, style services that we, that we have put out there, the recommendations and guidance and things like that that we've, that we've always done. I think we can do more to, to actively raise the bar in some of these areas, you know, by getting hands on with those smaller medium sized agencies.

A (13:32)

Right. And I know Texas does a lot. I trying to remember when it was, I think it was maybe two years ago, might have been longer at this point. I guess maybe about two years ago I put in a records request to try and get a sort of inventory of all the AI projects in Texas. And I was surprised that how fast I got the information back, it was like in less than a week. Someone sent me a list of everything across the entire state to do with AI and it was a lot and so a lot of stuff people probably never even think of or have heard about. And so anyway, you recently mentioned that Texas, with regard to AI, Texas is now moving from the pilot phase to more toward the execution phase. So obviously you can't run down that entire list I just mentioned. But are there any use cases that you think are especially promising? What do you see coming up that you really like what's going on with AI?

B (14:32)

Yeah, I think I see A lot coming in this area. Colin and I talked a little bit about the expectations there that not just here at Texas state government but across governments and private sector everywhere. There's some really high expectations in the area of AI that are driving a lot of what we're all doing. There are some things that are already happening out there with you know, AI managing you know, traffic flow and predicting you know, accident patterns on highways, invoice processing. There are some agencies that are using developed internal, you know, chatbots for you know, internal use. A number of agencies have already rolled out or rolling out their own generative AI solutions here at dir. We just recently rolled out Microsoft Copilot and you know are looking at other gen AI tools to complement to do different things. Right before we started this conversation I ran down the hall because I was, I was talking to some folks that are using gen AI tools for co development and doing almost all of their code development that they, that they do using gen AI tools now to do it for them. So there will be a lot of you know, as we go using document heavy workloads, things like that. We're encouraging our folks to look for ways in their own departments. We are you know doing things like writing our performance goals such that there's something that has something to do with use of gen AI tools to help add efficiencies to what we're doing here at the state. But there are some things we're doing, you know as I mentioned out of our, out of our most recent legislative session House Bill 2818 created an AI division here at DIR that is up and running and focus of this AI division is really something that I talked a little bit about data and some other ways that we can hands on help other agencies out there, especially small and medium sized agencies. But House Bill 2818 created a division here at DIR that will, that will do that specifically in the area of AI and we'll have. We've got a lot of agencies out there that aren't going to have their own AI teams for the foreseeable future and so we'll have a central AI team that will, that will help out those, those smaller and medium sized agencies identifying use cases and implementing AI tools and technologies. House Bill 1964 from our, from our last session directed DIR to create an AI sandbox for state agencies and universities and local governments to use to test AI technologies. We're actually running our first, our pilot project through that sandbox environment and process right now and we'll be launching that and opening that up to other government entities here in Texas in the very near future. And we're doing a lot of other things. We've got an innovation lab where vendors can showcase some AI tools. We have an AI user group. Couple times a year we're doing AI days where we've got a day of focused AI education. And those things sell out. And our CTO that runs those, John Hoffman says they sell out like Taylor Swift concerts and that about two hours after the registration opens up for our AI days, registration is full. And so folks are tracking when those things are opening up and registering right away so they can get in. So we've got a lot going on all at one time right now here at the state in efforts to, you know, get down that path, down that road as, as quickly as we can in the area of AI and, and get to using more and more AI tools and technologies to, to do things better and more efficiently.

A (18:31)

What happens at an AI day, we,

B (18:33)

we do some training. We do some training, we do some. We have some speakers come in. And so usually at an AI day, we'll have. The first half of the day will be some general sessions on some use cases we've gotten to where now I think our next AI day is AI Day seven, I believe. And we now have AI Day one was a lot about what is AI and if and how we might use this in state government. And now with our, with our last couple of AI days, we have folks from, from state agencies that are coming and sharing how they're using AI technologies in their state agencies. So we've come a long way there. And so we'll have some general sessions in the first half of the day and usually after lunch we'll do the afternoon with a lot of breakout sessions where we'll invite some vendors in that, with some, with some technologies to showcase. And I believe in the last one we had, we had four at a time for, you know, right after lunch and then another four that folks can choose from. So a lot, a lot of good, a lot of good stuff, A lot of good information and interaction and networking happening at our AI days.

A (19:43)

Yeah, you mentioned the high level of interest. How much of it is positive versus negative. The main negative thing I'm thinking of is concerns about is, is AI going to take my job and things like that.

B (19:58)

Yeah, you know, we don't, we don't see, we don't get to a lot of that. You know, that's something that, that is, I hear maybe in, you know, conversations like this most often. Honestly, you Know, I think folks understand that in our environment anyway, you know, being in our environment, you know, folks understand that we have a lot of work to do. We have a lot, we have more work to do than we have folks to do it already. Just needing the help to get caught up and get everything done that we need to do and do well is sort of step one. And if AI technologies can help us do that, then that'll be great. And we're also looking at a couple of conditions I think where just from an age standpoint, we have a larger number of folks that are near retirement than we have coming into state government. There might be a need, right, for some AI technologies to, to do some jobs, but it'll be from, it'll be from a, from a needs based position, you know, because we need to look for the, for ways to fill some positions because we're losing more folks and then, and then just the idea that, you know, it's not, we just don't see, you know, a large number of folks coming out of, coming out of school that are looking to go into government work and not as in past eras, if you will. And so we're looking for ways to have AI do some work, but I think it'll be because we're looking to fill some gaps, not because we're looking to replace any employees that we have on staff. I just don't see that being the case.

A (21:39)

All right. One other challenge that was mentioned in the IT strategic plan that I wanted to ask about was to do with the rapid change in the domain of technology. Everyone's heard of that at this point, but with regard to government, how it's outpacing the procurement cycle. And if I remember right, Texas has a two year budget cycle. So I don't know if that makes it especially challenging. But do you have any strategy for handling that? Is there any, is there any hope there? That's something we hear across a lot of states.

B (22:16)

Yeah, I've got maybe a little bit of a different perspective there. And just being 33 years in tech and we've seen changes all through my 33 year career with technology and I think technology change, while other sectors might have, know shorter funding and procurement cycles than, than what we have in a, in a Texas where it's biennial, that doesn't mean they have a desire to purchase things more rapidly. Right. Or replace things more rapidly. There's still always been the, you know, we, we live with the tech that we have for an expected period of time. Changes are happening, new technology is is happening. And when the time is right from a, from a budget standpoint and a fund, then. Then at a need standpoint, right, then we look to, to make upgrades. And that's always been the case, you know, and I think, I think seeing that it's happening a little faster today, you know, is a little bit of a shiny object. It's a little bit of a distraction, you know, still going to need to plan to spend a certain amount of time, you know, using the tools that we made an investment on. Right? We're spending, we're spending taxpayer dollars on, on the tools that we're buying. And so there's an expectation that we, that we, you know, get a certain amount of use out of those things. And, and unless the case can be made that, you know, we're, we're losing money by continuing to use something and, and I don't think we're there. I don't think, I don't think technology is. I don't think technology has outpaced our, our, our funding and procurement cycles to the point where we're losing by not being able to procure faster. I just think again, it's something that's been out, it's been out there for a long time, you know, with, with it. And I think we'll just continue to, you know, make sure we're planning on, you know, we know being in state government that, you know, we're used to our budget procurement cycles being what they are, and we understand that when we do make an investment in tools and technology that there's an expectation that we use it.

A (24:29)

That was Tony Sauerhoff, CIO of Texas. That's it for this episode. State Scoops Priorities Podcast is a production of Scoop News group in Washington, D.C. production work is done by Adam Butler and Carlin Fisher. I'm Colin Wood. Thanks for listening.