The impact of AI on the workforce: A state-level case study

Daniel sits down with Chelsea Linder, VP of Innovation and Entrepreneurship at TechPoint, to explore the what AI innovation and impact look like on the ground. They discuss Chelsea's journey from the VC world into economic development/ innovation, the growth of an AI innovation network in Indiana (funded by the SBA), lessons learned from fostering AI communities, and how businesses are actually adapting to AI. Chelsea also shares insights from Techpoints AI workforce impact study, which explored AI related job creation and levels of AI adoption among other things. Featuring: Chelsea Linder – LinkedIn https://www.linkedin.com/in/chelseaclinder/ Daniel Whitenack – Website https://www.datadan.io/, GitHub https://github.com/dwhitena, X https://x.com/dwhitenaLinks: Techpoint https://techpoint.org/Sponsors: Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U. S. eCommerce. Start your one-dollar trial at shopify.com/practicalai http://shopify.com/practicalaiFabi.ai http://fabi.ai/ - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.ai http://fabi.ai/Upcoming Events: Join us at the Midwest AI Summit https://midwestaisummit.com/ on November 13 in Indianapolis to hear world-class speakers share how they’ve scaled AI solutions. Don’t miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today! Register for upcoming webinars here https://practicalai.fm/webinars!

• 0:03Speaker 00

  Welcome to the Practical AI Podcast, where we break down the real-world applications of artificial intelligence and how it's shaping the way we live, work, and create. Our goal is to help make AI technology practical, productive, and accessible to everyone. Whether you're a developer, business leader, or just curious about the tech behind the buzz, you're in the right place. Be sure to connect with us on LinkedIn, X, or Blue Sky to stay up to date with episode drops, behind-the-scenes content, and AI insights. You can learn more at practicalai.fm. Now, onto the show.

• 0:49Speaker 01

  Welcome to another episode of Practical AI. This is Daniel Whitenack. I am CEO at Prediction Guard, and I'm really excited today to follow up on a number of topics that Chris and I have discussed over previous weeks related to wider AI innovation, what's working across various industry sectors, how that's actually happening, how that's impacting workforce. Because we have with us today Chelsea Linder, who is Vice President of Innovation and Entrepreneurship at Tech Point. How are you doing, Chelsea?

• 1:23Speaker 02

  I'm doing great. Excited to be with you today.

• 1:26Speaker 01

  Yeah, yeah. I know you and I met a little while back because you were kind of making your way into, I think, what is your current role and focus, part of which is this AI Innovation Network, which you've set up in Indiana specifically. And that's been very successful. But how does one get to that point? Describe a little bit about your background and kind of how you end up thinking about these kind of wider AI Innovation Network things and workforce things. I know we'll talk a little bit about that later.

• 2:02Speaker 02

  Yeah, for sure. So my original background is actually in user experience research. So I did that work for a while at a startup here in Indiana called An Toothless. And then I took a career detour to work in the venture capital space. So I was a partner at Generator, which is a startup accelerator and VC firm, where we invested across the country and I got exposure to all the most cutting-edge technology and innovation that was happening at the earliest stages through that impacting, investing activity.

• 2:42Speaker 02

  So then when I joined the Tech Point team, Tech Point is a nonprofit and our mission at Tech Point is to drive Indiana's digital economy through talent, innovation, and community. So when I joined about two years ago, we were talking a lot about what does that mean? And what, what do we need to drive, especially through that innovation lens, to ensure Indiana's economic success? At our core, you know, we're really an economic development-focused organization. And of course, staying up to date on the most cutting-edge use cases for AI was definitely one of those topics. And we had the opportunity through a federal program called the Growth Accelerator Fund

• 3:24Speaker 02

  Competition that's hosted by the SBA to apply, to do an assessment of our community and identify areas of need specifically around AI education. So I think that's when I met you, we're doing a needs assessment, mapping out the different stakeholders and resources we had across the state. And the thing we kept hearing over and over again was people across the state of Indiana wanted access to just know what other people in the state were doing, to share best practices with each other, really get in the weeds and learn from each other's mistakes and each other's opportunities, so that we can all, you know, rising tide lifts all boats, we

• 4:06Speaker 02

  can all support each other and making sure that Indiana can stay on the cutting edge of this new technology advancement. So we got the grant.

• 4:14Speaker 01

  That's great. It was successful.

• 4:15Speaker 02

  AI Network. Yep. Yeah, it was successful. And so we launched the AI Innovation Network to try to help build that peer group and convene those folks to share those best practices and keep each other up to date.

• 4:27Speaker 01

  Yeah. And how long has that been going on now?

• 4:30Speaker 02

  So it's been going on for almost a year. We launched it in January.

• 4:34Speaker 01

  Congratulations. Yeah.

• 4:35Speaker 02

  Thank you. Yeah. And we have, as of today, 399 members of the AI Innovation Network.

• 4:42Speaker 01

  Surely, surely, as this goes out, because it's prerecorded, you will be at 400 already. So we'll just say, we'll just say 400. I'll, I'll, I'll find someone to, to register. So that's.

• 4:55Speaker 02

  That sounds great. Yeah. So, you know, it's, it's really cool to see that the market is interested in what we're doing and that we are providing the value to our community that we set out to provide. That is really cool.

• 5:08Speaker 01

  Yeah. Have you, as you are looking at this kind of need, of course, like in a specific geography, I mean, if, if you think about where we're at, we're surrounded by the industries that are sort of being transformed by, by AI. So whether that's like life sciences or manufacturing or logistics, or all of those things, of course, are, are kind of surrounding us. As you, as you did those needs assessment, as you pulled together, and we'll talk about specific things that maybe you're, you're doing that have, have worked well, or learnings that you've had that maybe you want to pass on to others trying to, to do this

• 5:48Speaker 01

  type of work. But as you evaluated that, were, were there examples out there across the country of other kinds of things like this? Or what, what kind of went into the inspiration, I guess, for the kind of mechanics of what this could or should be?

• 6:06Speaker 02

  Yeah. So we mostly drew inspiration from our other networks that we run at Tech Point, especially the Indiana Founders Network, which is a network that I launched the year prior to this one. And we have gotten a lot of great market success from that as well and designed this network to be similar to that one. But there are a couple of key differences. One of them being, we really did intentionally want to serve the entire state. And that can't happen at an only in-person convening. So we wanted this to be hybrid and we've been navigating what that means and how to do it well over the past year. But it has given us the opportunity to serve people in the middle of the cornfields, in the manufacturing floor, you know, all across

• 6:50Speaker 02

  our state. And that has been a really powerful impact from the network.

• 6:55Speaker 01

  Yeah. And for those out there, maybe kind of across the country that are maybe in an environment where, you know, certain people, maybe they are in SF or somewhere and they have a, they have an AI meetup every night. But there's certainly large parts of the country that are trying to figure out kind of how to navigate this. And of course, we'll talk about the workforce things later. But in just in terms of the community and what's needed around this, what, what have you found to be some of those, let's say, the core components of what people have responded to well and gotten value out of? So maybe that could inspire others, you know, in, in different areas that are trying to do some of this networking or maybe even spin up

• 7:40Speaker 01

  their own sorts of communities related to this technology?

• 7:45Speaker 02

  Absolutely. I think the number one benefit that we have here in Indiana is Pujor hospitality. But the way that that shows up for the AI network is that our members are extremely willing to share and be transparent about their work. And we very rarely come across instances where somebody says like, no, I need to protect my IP. I'm not willing to share. Or, you know, we, we just don't come across that kind of like ego-driven unwillingness to be open. And that is only to the benefit of the other members, especially at the beginning. I think people were so excited to have an outlet to talk about their projects that we just had so many people raise their hands and say,

• 8:27Speaker 02

  I want to share what I'm working on. I would love to get the feedback from other experts in my field. I would love to, you know, help a new person learn how to do this or replicate this type of work within their organization. And I think it's just, it's the power of having a strong community of helpers. And I, I don't know the secret to building a strong community of helpers. But I do think that that's really the foundation that we were able to build off of.

• 8:52Speaker 01

  What do you think that, that eagerness, I mean, I've even seen it on the podcast here with people that we've had on that are really wanting to, I guess, um, they've felt pain maybe through some of their AI journey and maybe that's part of why they want to share things. What, what is your sense of, uh, yeah, why, why is, why is part of that eagerness there? And what are they hoping, what are they hoping to provide? Like in the AI automation network that you run, when people are sharing their stories about what's working, what's not working? Yeah. What are, what are their motivations? What are they hoping to see?

• 9:27Speaker 02

  I think that, like I said, a big part of it is being able to learn or identify opportunities to get better at what you're doing professionally. I think that's a big piece of it. I also think that we, as a community, are, we're focused on education. Indiana has like the most universities per capita, um, I think, except for Massachusetts. And so for us, like being a lifelong learner, being in an environment of people who just want to learn a lot is a big piece of it. And then thirdly, I would say one of the key topics that our advisory council, who we have, um, helping us with the content for the network.

• 10:08Speaker 02

  What we talked about at the beginning was a feeling of imposter syndrome of, I think I'm doing a good job, but am I actually? And I don't have a lot of peers in this work that I can verify with. So a little bit of willingness to be an open book or like show your work just to, uh, combat those feelings of imposter syndrome. And we've started to try to kind of democratize the opportunities within the network. Doing more live prompting or live coding activities. Again, just to help with that feeling of imposter syndrome and, and make everyone see, you know, they're not the worst person in the room at whatever they're doing.

• 10:47Speaker 01

  Yeah, it helps to be in a room with what you might perceive as very smart people, but in reality are other practitioners. And certainly, I've noticed that over time, where I have a very small sphere of knowledge, but others have different spheres of knowledge. And when you, I think, start to realize that, that we have a lot to learn from one another. And I may be able to talk about whatever security-related concerns with AI agents. I certainly can't talk about other things at the core of pharma manufacturing

• 11:28Speaker 01

  and how AI fits into that always. So that cross-pollination is really exciting. Does that happen? Describe for us an AI innovation network event. What would that typically look like? What could people expect? Yeah, how do people show up there and what happens?

• 11:50Speaker 02

  Yeah, so we have three different buckets, I would say, of events. So the first one is just purely networking, just make friends, get to know people in your field. And so we facilitate that through different activities or different types of icebreakers to just help folks feel more comfortable in the room. Secondly, we do, on a quarterly basis, a case study, where we'll have a partner come in and present about a project that they've done, either within their own organization or for a client. And then we take it similarly to how you would structure a PhD course, where we'll have the beginning half be about describing the case, describing the problem,

• 12:33Speaker 02

  break into small groups, and have a discussion about how would you approach that problem and what tactics would you use, and then wrap it up with what they actually did on the outcome side. And then we follow up with a written documentation of that case study. Uh, so we're trying again to just give that more in the weeds knowledge to the practitioners that are in the group. And then the third one, I would say is more of that kind of open book sharing about projects or processes that folks are working on to be able to get more real time feedback or just show how an application may work in an inside of a different organization. For example, recently we had a fantastic presenter from Baker Hill come in to talk

• 13:14Speaker 02

  about how they encouraged adoption across their team, uh, which is of course a really major issue that we're all trying to talk about right now, not only adoption, but upskilling and rescaling of the workforce, um, and being able to share a shining star example of how it went well and what they learned, uh, that's just incredibly applicable to another organizations that are in the room.

• 13:50Speaker 03

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• 16:00Speaker 01

  Well, Chelsea, it's really great to see, of course, this happening in my backyard and see some of this innovation network being formed. What lessons do you feel for maybe, again, others out there that are thinking about kind of forming communities around this topic, around AI, whether that be on Discord or hybrid or via in-person events? What have been some of the lessons you've learned that are maybe like mines to not step on or just like challenges that are part of it that you haven't totally figured out yet?

• 16:41Speaker 02

  I think the number one would be not assuming that what works for our community will work for your community. And that's why we have the Advisory Council. I am not an in the weeds AI practitioner. That's not my day job. And so I never would want to pretend that I was or lead the content of the network in that way. So we built an Advisory Council and they've been instrumental in helping us identify. Where the knowledge gaps are, how we can help build those and championing the network in general as well. Um. So I would say step one, start by talking to your community and figuring out what they actually need. And then I think you have to kind of capture and hold on to the momentum as tightly as you can. So

• 17:25Speaker 02

  certainly at the beginning, we had a lot of excitement, enthusiasm, momentum for the network. And um with some things, we did a great job capturing that and pulling it forward. And with other things, we didn't. Um. So some of those initiatives have kind of slowed down or aren't happening anymore. Um. So you kind of have to pick and choose, you know, what are the things that are really providing the value you want to provide that you can double down on? And then are there things that maybe aren't working out that you don't need to continue doing moving forward?

• 17:53Speaker 01

  From your perspective, because you have, you know, you have been working on this over this past year. Have you seen just kind of general trends or shifts in people's view towards AI within companies or people's education around the the topic or the types of things that they want to talk about? Um. Because that's, you know, something maybe for some of us that are in the industry or like building AI things, we we have our own view of maybe what people, what's on people's mind and that sort of thing, where they're at in terms of what they're thinking about. Um. And that doesn't always map to actual

• 18:36Speaker 01

  actual discussions in companies, where people are at on their kind of educational journey, what they want to talk about. Like, are they just trying to get their first chat interface up? And like have that be a when? Are they? Are they thinking about, you know, tying in AI functionality to existing products or building custom tools? Are they? Are they thinking mostly about, like you said, the adoption uh side of things? Have you seen that shift uh over this past year and any anything to kind of highlight there?

• 19:14Speaker 02

  Yes, absolutely. I think we're really uniquely positioned as Tech Point because we have working relationships with everyone from Eli Lilly, which was recently named the number one most AI-ready company in the world.

• 19:29Speaker 01

  Oh, I didn't know that. That's awesome. Congrats to them.

• 19:32Speaker 02

  Really cool, right? All the way down to like little baby startups or more mainstream lifestyle type of businesses that have perhaps been operating for many, many years and have basically zero technology adoption, right? So we have the viewpoint of that entire spectrum. And what I've witnessed over the past year, or maybe even more than that, is a democratization of access, which has been really cool to see, where, you know, Lilly has all the resources and all the capabilities and incredibly talented and smart people to help get them to that place. And, um, you know, uh, automotive shop down the road doesn't.

• 20:16Speaker 02

  But thanks to a lot of the initiatives that have happened both within Indiana and just in general with more education and awareness of AI, that small business has the same access and opportunity. Um, and that's really cool to see because now we can see how a small business may be able to grow exponentially more quickly, increase their productivity, et cetera, in a way that they really never would have been able to before. With that in mind, I think what's happening is these businesses are realizing that this is a must-do. And so now I'm getting more and more inbound questioning from businesses that

• 20:57Speaker 02

  probably don't even have a tech team at all, have never really thought about this before, saying, "I know I need to do this." How do I get started? And that's a really great position to be in to say, okay, well, come to the AI Innovation Network and then we'll introduce you to some of the people who are already leading the way here and they can share with you what works and what doesn't work and we can go from there. So that's been, that's been a fantastic thing to see. On the flip side of that, I think a big challenge that every business is facing right now is with the workforce and the upskilling, reskilling, job security questions, all of that. So Tech Point just recently published a report about AI-driven skills and the changes in workforce

• 21:41Speaker 02

  demands due to AI. And it's, it's just some really fascinating data, right? Like job postings for generative AI engineers are up by seven times year over year. Fascinating data to, to think about. But at the same time, we're seeing higher levels of unemployment, higher levels of reduction in forces, all kind of also attributed to AI. So, you know, there's a lot of contrarian data, but at the end of the day, I think we all can agree that we need to focus on the upskilling and reskilling and that we need to do it in a way that can preserve the workforce as much as possible. And we, we're so lucky to have companies like Lilly in our backyard that are leading the way on that.

• 22:24Speaker 01

  Yeah, this, uh, this report is really fascinating. I, I encourage people and we'll link this in our show notes, uh, but this is a report, AI-driven skills, uh, for Indiana's economy, insights from employers and industry trends. Certainly something like at the heart of our country that is the reality, kind of on the ground of, of what's happening, which is why I think this is, is, is a really great, a great way to present this. And, um, so gi- give us a little bit of a background on this particular report, kind of how, how it came about and, and the, and the data behind it.

• 23:01Speaker 02

  Yeah. So if you recall, I mentioned that Tech Point achieves our mission through three pillars. So innovation, community and talent. And the talent pillar has historically been about solving the brain drain problem we had in Indiana, helping retain and recruit workforce, especially tech workforce to come to our state or stay in our state once they graduate from one of our amazing higher ed institutions. And over the past couple of years, we've been seeing that problem not be the biggest problem for employers anymore. So it drove Tech Point to go back and talk to our stakeholders and employers across the state and say, okay, we sense that retention and recruiting of

• 23:42Speaker 02

  tech talent is not your biggest problem anymore. What is? And we kind of already knew what they were going to say, but they absolutely validated our assumption that aligning the workforce with these new in-demand skills is their number one talent problem right now. And so with that in mind, we started doing a lot more of this research and ultimately came up with the contents of this report. And what we found out is that right now, we needed to focus on three things. We need to focus on integrating AI into the workforce training programs, so including higher ed, as well as within an organization upskilling.

• 24:22Speaker 02

  We need to focus on doing that in an industry-specific way, because the AI skills in every industry, as you mentioned, like manufacturing, AI in a manufacturing floor looks very different than AI in pharmaceuticals, right? So we need to align that in industry-specific ways. And then we need to expand adoption past our early adopter sectors. So we really need to push into some of those more lagging sectors like agriculture, et cetera. And then thirdly, we need to create cross-sector AI knowledge as well. So we need to share best practices across all of our strongest industries, and the AI network is one of the ways that we can do that. But if we can do these three things, then we think we will be able to maintain a competitive workforce here in Indiana.

• 25:06Speaker 01

  Yeah, some of these things, I encourage people to look at the, look at the report. I mean, there's some things just generally that are interesting, kind of nationwide, and some things that are kind of a case study of where we live specifically. But yeah, job postings for generative AI engineers up 7X is really interesting. Another thing, though, that you mentioned is job postings requiring generative AI. Generative AI skills in other IT roles are up thirty five percent. And I think you have some some graphs around this. So it's there is this kind of generative AI engineers or AI engineers specifically that is a in demand thing.

• 25:51Speaker 01

  It kind of reminds me back when everybody was looking for data scientists and we were trying to figure out how to get data science into workforce education and or all of those things. But that that is up, but even more so or at a higher rate are these other technology positions that are requiring skills in in AI. From your sense, is that due to just the I know you also talk about or show kind of a graph in the report of companies adoption of of AI, kind of official, I guess official adoption of of AI, maybe not shadow usage of AI, but official adoption of AI kind of

• 26:35Speaker 01

  rising up to ten percent or or beyond. Do you think that's just a matter of them figuring out that, yes, this is here to stay? And we need to not just have a sys admin, we need to have a sys admin that also knows how to use these AI tools. Like, what do you think is is behind that?

• 27:00Speaker 02

  Yeah, I think it's partially because it's becoming clear that it's a competitive advantage. And so companies are doubling down on requiring those skills. You know, it's hard to ignore when you hear somebody like the CEO of Atlassian being like, everyone has to do this, right? So I think that's that's a big part of it. And then I also think that, especially with Gen AI, as you know, I don't need to tell you this, this is really just the tip of the iceberg when it comes to truly implementing AI, not just Gen AI within your business. And that what businesses are really going to see success from is not using a chatbot, right? It's a many layers deeper application.

• 27:44Speaker 02

  And so I think. Having these roles is kind of the preemptive steps towards moving into those deeper applications where we're truly talking about process automation, et cetera. So I think, I think it's the tip of the iceberg and I feel like those roles are going to continue to require some level of skills, similarly to now how a product owner would normally be required to have some level of coding skills, right? So I think we'll continue to see that proliferate across organizations. I recently was able to present to a group of CFOs of companies that had 50 million annual revenue or more. And it was really interesting to see the spectrum of, I absolutely will never trust

• 28:29Speaker 02

  AI to do my finance work, to like, I love it. It does so much of the things that I used to hate doing. And I think we're just, again, we're going to see that proliferate across every business unit or every department within an organization.

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• 30:22Speaker 01

  Chelsea, just another interesting thing that I see in this report, which kind of stood out to me is you talk about kind of the skills gap, which some of those like highest skills gap around AI and machine learning, data analytics, big data, cybersecurity. But there's kind of chart of most in-demand roles now, and it kind of stood out to me that software developer or engineer is still up there as the highest in-demand skill, even higher than the AI machine learning engineer. And so I think there is this narrative that we hear, right? And you know, there, everything is a kind of mixed bag.

• 31:07Speaker 01

  It's a messy situation, but the narrative on the one side of the spectrum is that, well, AI is kind of doing all of these software engineering things now, and we don't need as many software engineers to do the same amount of of work, which means like maybe, you know, maybe I need to be an AI engineer. I don't, it's not enough to be a software engineer. And maybe this is a, maybe this is a timing thing, but I don't know if you have any thoughts on that. That one stood out to me as kind of, even in light of all the vibe coding things that are going on, software development is still, and being a software engineer is still a good gig to have, at least, at least here.

• 31:51Speaker 02

  Yeah, so um this data is trailing data. So I do expect that that number will change in the future um as we, you know, we're scraping job descriptions and things that have already happened, right? So I do anticipate that those AI focused engineering roles will take over um as the number one most in demand. But I uh also have been doing a lot more research on this recently and as an example, I spoke with an organization who had laid off all of their junior devs and they had their mid levels working with AI to do the work that the juniors were doing. And at first, the mid levels loved it. They were like, this

• 32:35Speaker 02

  is great. I'm getting basically the same quality work as a junior dev would give me. And I don't have to manage a human being. I don't have to deal with the emotional side of it. I can be as blunt as I want to, like, they're never gonna get upset with me, right? And they loved it. Well, six months down the road, those same mid levels are saying, can we please hire some junior devs? Because I am so annoyed at my AI and I don't want to have to be the one managing that, right? I don't want to have to be the one doing the prompting, getting it to fix all of its dumb mistakes, hallucinations, whatever. So I think that just speaks to this is a transition in what those jobs look like, not a complete removal of those jobs from our workforce.

• 33:20Speaker 01

  Yeah, that's that's really interesting. It reminds me of a discussion, I forget what episode it was on, but we were talking about this kind of vibe coding work and the actual mental burden of that work for an engineer is very different from the from the kind of normal, oh, I'm typing things in my editor, even with autocomplete or something like that, where you have like multiple things going on at once, you're constantly context switching between different agents doing different things. And to your point, you kind of get into this like master orchestrator. Mode and it maybe, maybe to your point, like there are engineers who like doing engineering

• 34:04Speaker 01

  and they don't want to be just those orchestrator type people. So it's like almost like a different, it is a different cognitive load. It's a different day to day workflow and, and we haven't, certainly haven't fully navigated that yet and understand, you know, what, what, what will happen, right?

• 34:24Speaker 02

  Yeah.

• 34:24Speaker 01

  When, when that comes about, but I think at least Chris and I's view on the podcast here, I think we've said a few times, I don't think software engineers are going anywhere. The, the dynamics and kind of the roles may shift, like you said, but there's still going to be a need for those resources. There may additionally be a need for these, you know, in increasing need for these resources around AI engineers and, and that sort of thing.

• 34:51Speaker 02

  Yeah, I will hold fast forever that the number one skill you need to vibe code well is to already know how to code.

• 34:58Speaker 01

  How to, how to code. Yeah. Hey, good, good point. That's a, that's a great quote. Yeah. I, I love that. Yeah. And I think, I mean, even back when people were first starting, like, like in the seventies and eighties, when, you know, people were programming, I think they were already talking about, well, computer programs are eventually going to be able to program and we're not going to have jobs. And, and that was, you know, quite a while ago. Now things are moving a little bit quicker. Now I think you could argue and maybe there's some differences, but I, I think we're at least safe for the moment.

• 35:32Speaker 02

  Absolutely.

• 35:33Speaker 01

  Yeah. I am interested in this graph you, you show about the, the share of businesses that are using AI. Could you talk about like the kind of range of industries that that represents? And just to give people, because you're listening on audio, a visual of this, it's essentially an increasing, you know, trend to more and more, right? But this goes from September of 23 up to July of 25 and September of 23 was less than 4% in the, in the US, slightly less in, in Indiana, and then kind of both converge up to around 10% in July of, of 2025. So around 10% of businesses using.

• 36:20Speaker 01

  Kind of using AI. So could you help us understand like, what does that mean using AI? What industries, et cetera?

• 36:26Speaker 02

  Yes, yeah. So that data is from the US Census Bureau and it's a survey. It's the BTOF survey and forgive me for not remembering what that acronym stands for. But it is a survey they do every two weeks. So that's why we see this data. If you look at the chart, it's pretty lumpy. Because they're getting different numbers of responses, et cetera, from different industries, different stratification every two weeks. But what the questions are, there's two different questions that they asked to pull that data. They're very specific questions. So one of them is, are you using AI to build your product at your organization? And then the second one is, are you using AI to do business within your organization?

• 37:09Speaker 02

  So it kind of touches on your question, which is, what exactly are they using it for? Right? And so I didn't have access to the data for those two separate questions. And I think that would be really interesting to see. My assumption is that very few are using it within their products and very many more are using it within their business operations. But that's where the data comes from and it definitely makes me feel positive about Indiana's trajectory to see us kind of catching up with the rest of the nation. But then we can compare that to the data recently, yesterday or a couple of days ago, coming out of MIT, talking about how 99% of AI projects fail or pilots fail. So I think it's one thing to say, yes, I'm doing it.

• 37:52Speaker 02

  And it's a completely different thing to say, we're doing it successfully. And I think that's the data that we're going to have to dig in more to find out more about and how we can, you know, leverage programs like the AI Network or otherwise across the country to ensure the success of our adoption program.

• 38:10Speaker 01

  Yeah, yeah. And it is interesting, like the perception around these sorts of use numbers. My friend Scott at Chip AI, I think he says something like, like 90% of people are using AI or some high figure, 80% or whatever it is, 80% of people are using AI, but 10% of businesses are using AI, which if the 80% of the people in the businesses are using AI, it probably just means like, a lot of companies don't know that their employees are using AI. Do you find that to be like?

• 38:50Speaker 01

  A common theme amongst these discussions of even just figuring out what people are doing, because people, it seems like, are just getting access to whatever tools they think will make them productive, because they actually probably do want to be productive in their jobs, or make their jobs easier, or whatever that is.

• 39:06Speaker 02

  Yes, absolutely. And I think that's true about individuals as well. I would say probably almost 100%, at least in the United States, are using AI. They probably just don't know.

• 39:15Speaker 01

  They probably don't, yeah, fair enough.

• 39:17Speaker 02

  Probably don't know. And I think that's the same with businesses. As an example, I, my daycare, one of my daycare teachers started using Gen AI to write her daily status updates about my daughter at daycare. And I was not cool with that.

• 39:37Speaker 01

  For various reasons, yes.

• 39:40Speaker 02

  And when I went to go and talk to that administrator of that daycare, she had no clue that her staff was doing that. And certainly, a daycare doesn't have an acceptable use policy of AI, right? So I think there's a lot of those types of circumstances. And the best thing that a business owner can do is, regardless of whether you think people are using it or not, you need to have a policy, you need to set up the appropriate guidelines so people can do it safely. And I think that starts with giving approved access to everyone.

• 40:11Speaker 01

  Yeah, yeah, I think certainly there's companies that try to lock down from the beginning, but it doesn't really stop it. It just sort of stops the maybe egregious use. I don't know. But, but yeah.

• 40:28Speaker 02

  It stops them from doing it on their work computer.

• 40:31Speaker 01

  Yeah, maybe so. That's a good way, that's a good way to put it. That's a good way to put it. But yeah, I very much encourage people, please, please go and look at this report. It's very nice. You can, we'll link it in the show notes and you can find it at the Tech Point website. There's a lot of cool stuff coming up that if you are in the Midwest or in Indiana, Tech Point's doing, they have this great Mirror Awards, which I've been to, which Celebrates a lot of innovation that's happening and people can find out about that and nominate people. There's, there's events coming up. What are you kind of, as you look at all the ecosystem, Chelsea, of things that of course have spun up this past year?

• 41:17Speaker 01

  But maybe kind of wider, just what's happening and the shifts that you're seeing in terms of adoption of AI and case studies around AI, what, what's most exciting for you as you're looking forward to the next year of the AI Innovation Network, maybe related to the network, but also just related to your own view of like how the technology is developing?

• 41:38Speaker 02

  I'm really excited about how AI is pushing people to be even more innovative and think about things in even more uncomfortable ways than they did before. And especially right now in Indiana, the conversation around data centers, I think is driving a lot of forced innovation where we have some of the best scientists in the world here in Indiana. And they're trying to figure out how we can make data centers more efficient and more ethical and sustainable and all of those things that there wasn't a pressure cooker to figure out until relatively recently. So I'm really excited to see that because, you know, if we can find a copper alternative that can stay cool more efficiently,

• 42:21Speaker 02

  that's going to have impacts across so many industries. AI is just, you know, data centers are just one use case for that, right? So that gives me, I always, you know, challenges drive innovation. And so the more of these kind of hard conversations that we have to have, the more innovation will stem out of it. So I'm looking forward to seeing what, you know, the next crap of amazing innovations are that come out of this really pressure full time that we're in.

• 42:47Speaker 01

  Yeah, that's awesome. Well, I'm sure that Tech Point and the AI Innovation Network will continue to produce great, great reports around this, but also engage the community as all of that's going on. So really, really appreciate you joining us, Chelsea. It's been, it's been an amazing conversation and of course, look, look forward to interacting with you in my own community around things that, that are going on. And yeah, thank you so much for joining us. Look forward to having you back again sometime.

• 43:17Speaker 02

  Thank you. It was great catching up.

• 43:26Speaker 00

  All right, that's our show for this week. If you haven't checked out our website, head to practicalai.fm and be sure to connect with us on LinkedIn, X, or Blue Sky. You'll see us posting insights related to the latest AI developments, and we would love for you to join the conversation. Thanks to our partner Prediction Guard for providing operational support for the show. Check them out at predictionguard.com. Also, thanks to BrakeMaster Cylinder for the beats and to you for listening. That's all for now, but you'll hear from us again next week.