AI, Trust, and the Human Shift: What Automotive Leaders Must Do Next

[Transcript]

[00:00:00] Jan Griffiths: Welcome to the Automotive Leaders Podcast, where we help you prepare for the future by sharing stories, insights, and skills from leading voices in the automotive world with a mission to transform this industry together. I'm your host, Jan Griffiths. That passionate, rebellious farmer's daughter from Wales with over 35 years of experience in our beloved auto industry and a commitment to empowering fellow leaders to be their best authentic selves.

Stay true to yourself, be you and lead with gravitas, the hallmark of authentic leadership. Let's dive in.

This episode is brought to you by Lockton. [00:01:00] Rising benefit costs aren't inevitable for you or your employees when you break through the status quo. Independence matters, it means Lockton can bring you creative, tailored solutions that truly serve your business and your people. At Lockton, clients, associates, and communities come first, not margins and not mediocrity. Meet the moment with Lockton.

AI still remains top of mind for everybody and for sure everybody in the automotive industry. And our last episode, we had the pleasure of interviewing Dr. Bryan Reimer who is an MIT research scientist and author of the brand new book, how to Make AI Useful, and that episode was so successful. I've received so much positive feedback that we had to bring him back onto the mic again.

But the first person that responded [00:02:00] to that episode was none other than Cheryl Thompson. We all know Cheryl in the auto industry, CEO of CADIA. So first of all, Bryan, welcome back to the mic.

[00:02:13] Bryan: Jan happy to be here.

[00:02:15] Jan Griffiths: And Cheryl, great to have you again,

[00:02:18] Cheryl Thompson: Thank you. It's good to be back.

[00:02:20] Jan Griffiths: Cheryl. It was just a matter of hours before the episode was released and I saw your email and you said that it was outstanding. So what was it about our last episode that really resonated with you? Tell us.

[00:02:35] Cheryl Thompson: Jan, I have gone down the AI rabbit hole. I have been in weekly classes, since April, and on top of those classes I have been building things. And so when I heard the podcast. And I listened to what Bryan said about trust and culture that resonated so much because we really do have to have trust when we think about using these tools. We have to have trust in the tools, we have to have trust in the people to use [00:03:00] them. And we have to have the culture for that. So that takes a certain type of leader and that takes that culture of psychological safety. But the one thing that really got me was the Wow Whoa Grow framework. And I'll just tell you how I relate to it. I see all these cool things I can do with ai. I use it in every element of my business. So that is the big wow. But what has happened to me is I have been creating like crazy all of that free time that I was supposed to free up. Yeah. I'm just creating more work. So I had to say, whoa. And now I do like a little meditation and center myself, so I'm leading AI and it's not leading me.

So I think I'm in the grow phase right now, really learning to use the tool.

[00:03:46] Jan Griffiths: Yes. And in this episode we are gonna talk about how people are using the tool because so many people say to me, well, you know, I've played around a little bit on chat GPT, and I'm summarizing my meeting notes, [00:04:00] but they don't know where to go with it. So, Bryan, what's happening out there? Tell us.

[00:04:06] Bryan: first and foremost, I think we need to remember that large language models embodied through chat, GPT, Gemini, copilot are just one attribute of ai. They're hot fad right now. They're incredibly useful tool. but they are just an element of the broader landscape of ai, a tool in the quiver per se. One of the things that I think is, intriguing about these tools is that they are incredibly useful for a lot of everyday activities. They are very much, if used correctly, a phenomenal copilot to work and collaborate with, to provide and refine product. They are not, however, an autopilot to do a whole bunch of stuff automatically for you.

And I think that's where that balance is critical and we find that. So when folks begin to embrace and use tools like this, it's all about starting small, scaling smart, and beginning to pilot AI practices into one's lives. [00:05:00] Otherwise, as Cheryl mentioned, all of a sudden at the time that you're creating. Disappears and too much of a morass. So treating this technology as a copilot, as a way of amplifying human expertise and upskilling each and every one of us, and filling in some of the gaps in our skill set is a great way of allowing and benefiting from AI today. again, remembering that what we are talking about here is just one facet of an ever evolving state of play in a state of technologies here that is gonna support us in new and unique ways that we can't even imagine yet.

[00:05:35] Jan Griffiths: When we talk about ai, the first thing comes to mind is chat, GPT, of course. But then when we start to talk about more advanced AI systems and we start to talk about agent ai, can you help us understand that Bryan?

[00:05:46] Bryan: When we start to think about AI that is starting to make decisions for us, and, there's lots of different names and different approaches, but we're talking about. Robots or pieces of code that are going out and negotiating and doing [00:06:00] things automatically for us. And there are lots of really simple applications that that may work. the big picture question becomes, where do we need to be a collaborator with the automation and the ai? And where is the AI of handling simple tasks? By itself now hmm. Illustration of simple tasks by itself is not. So many years ago, we used to ha end up sing through our spam folders all the time, finding treasure troves of stuff that are missed. Now that still happens occasionally today, maybe, once a month or once every two or three months that I end up in my spa looking for things. years ago, it was once a week, if not once a day. is AI of a variety of different forms. Few solving problems for us. It can sort emails wonderfully. It can make decisions in the negotiation of advertisement for [00:07:00] us. Okay. at the end of the day, the real value proposition to AI for many of us is a role as a collaborator and it's assistant with us. And augmenting and supporting us and, and being better leaders, being better employees, being better contributors to society at large.

[00:07:18] Cheryl Thompson: I agree with that a hundred percent. I have found really good success in using it as an assistant. It will lie to you, right? It

[00:07:26] Jan Griffiths: Yes.

[00:07:28] Bryan: Yeah, I think that's important. Look, AI is an opinion, like you and I trained on a bunch of our opinions, so we hallucinate. Why wouldn't you expect it to hallucinate?

[00:07:39] Cheryl Thompson: Exactly.

[00:07:40] Bryan: It's regression to the mean at the best, so, as soon as we begin to treat AI as an opinion. Okay. It's an opinion that we need to weigh and say, okay, do I trust this electronic opinion? Well, may trust your and Jan's opinion a little more because I know you a little better. but the electronic opinion provides value. But at the end of the day, it's our ability to [00:08:00] synthesize that electronic opinion that's the amplifier.

[00:08:02] Cheryl Thompson: Yes, yes. I call that the human in the loop.

[00:08:06] Bryan: We call it the H factor in the book.

[00:08:06] Cheryl Thompson: Oh, okay. I love it. I love it. You know, I'll let it do maybe 80% and then I know I've gotta get in there and do the other 20%. As an example, I create a lot of workshops and content, and so I have a workshop assistant inside of Claude, and the backend is loaded with all of my past material, maybe some transcripts of things I've done before.

And in my custom instructions, I will say, do not fabricate. And it still will. And I'll have to say, you know, whenever it comes out with anything that has data, I'll say, where did you get that from? And try to validate it and it'll say, oh, you caught me.

[00:08:43] Jan Griffiths: Oh my gosh. Same thing. I will say, is that right? Where did you get that data from? And it said, oh, I just basically made it up and I said, do not ever. Make up data if you have a number, I need to always know the source of that information.

And the [00:09:00] other thing I noticed that it did the other day, so I've started creating my own GPTs for very specific projects and tasks and I was doing one for social media. And I said, okay, I want you to create some LinkedIn posts, right? And I gave it very specific criteria. 'cause it knows my voice now.

I mean, let's face it, there's enough transcripts out there, right?

[00:09:19] Cheryl Thompson: Mm-hmm.

[00:09:20] Jan Griffiths: Give it all my transcripts. Yeah. I could probably speak Welsh by the end of the day, but it knows my voice, it knows my tone. It's got me pretty good, but it's structure in the LinkedIn post.

So I said to it this is how I like it structured. I think I said 1300 characters maximum. 'cause I don't like long LinkedIn posts. Right. And. It came back and that was a change I had made to it. And then it came back with a ridiculously long post that was way longer than 1300.

And I said, why did you ignore the rule that I gave you? Right? And then I said, oh, sorry. Sorry, Jan. Yeah, you are right. I was focusing on those three other things you told [00:10:00] me. What do you mean you're focusing on, you're supposed to do what I tell you to do.

[00:10:04] Bryan: Jan, at least it's honest.

[00:10:07] Cheryl Thompson: That's true.

[00:10:08] Jan Griffiths: Why does it do that, Bryan? How does it do that? Why? I mean, if you give it a rule, isn't supposed to follow it.

[00:10:14] Bryan: This is why large language models are great assistance in many ways, but they're not gonna solve safety critical problems.

[00:10:20] Jan Griffiths: Ah.

[00:10:21] Bryan: And the value is. What they can produce, but nobody understands why they produce what they produce or what they're gonna produce next. So you have an artificial system that does some amazing things at times, but no one knows when it's gonna fail and why it's gonna fail. this is exactly why we need to understand where this can be an assistant to us and why it's not gonna be a replacement to us. And look, I think large language models are a fad. I think that much like deep neural networks, were gonna solve everything five years ago. Large language models are gonna roll on out to whatever's next. And if you can guess that, well, you probably shouldn't be hearing [00:11:00] the podcast. You should be doing a little betting with a retirement portfolio on Wall Street.

[00:11:04] Jan Griffiths: So Cheryl, there's so many people out there that want to go to the next level with ai. Rather than just play around with chat GPT, what are some logical next steps that they could take?

[00:11:14] Cheryl Thompson: I think learning. How you can use the tool as an assistant like we've been talking about, like what are the use cases and they have to be personal to what you do every day. The workshops that I do. I've powered them with ai, so I'll give them some prompts. So let's say I'm doing a workshop on self-care. give them a prompt and it'll say, you are Henry Cloud, the author of Boundaries. Right. And it is assisting them in setting those boundaries so it's something that they can relate to or I will teach them. How to summarize a transcript, which is pretty basic, but also taking like a large technical document and summarizing, it for a technical person. For a non-technical person. You know, I came from manufacturing engineering and I [00:12:00] wasn't extremely technical. I would've loved to have something like that so I

[00:12:04] Jan Griffiths: Yeah.

[00:12:04] Cheryl Thompson: and understand the information and then give me an analogy. So it's just real simple to understand and I'm thinking, if I was in corporate now I can remember I had a boss and he would ask the same questions and I would always think, why don't people pick up on his questions?

Why aren't they preparing that presentation? With that in mind already, I would be running that filter, like before I presented anything to him, I would have his voice in there and

[00:12:29] Jan Griffiths: Yes,

[00:12:30] Cheryl Thompson: Right?

[00:12:30] Jan Griffiths: yes.

[00:12:31] Cheryl Thompson: if I was a project manager, I would put my project plan in there and say, identify the risk. You know, so I just, I try to get real close to who's using it and what the use cases are, and come up with some ideas so that they can start to see how applicable it is. Or I will help them use things at home. Like meal planning, like for, Thanksgiving,

[00:12:52] Jan Griffiths: Yeah.

[00:12:53] Cheryl Thompson: I had my chat GPT right there with me. The Lions game was on. The guys were watching the game. I wasn't sure when it was [00:13:00] gonna end and I had said something like, yeah, these jokers are watching the Lions game. I've gotta figure out all the timing and chat. GPT came back and said, okay, this is what we're gonna do when the game's done and those jokers talk to me.

It's like when those jokers come in and wash their hands, that's when you put the biscuits in, right? So it's just like, how do you use it day to day? How do you use it to plan a travel itinerary? It can be so useful. So trying to get people to see the use cases. it's personal for them. And when I go into companies, I think that the co-pilot enterprise just got released in the beginning of the year. And so I'm seeing it departments start to put their policies together, put those guardrails in place. And so I'm encouraged because I am seeing them come to the table and say, okay, here's what you can do. You know, here, here are the, the guardrails, the guidelines, and all of that. So they're giving them some structure. But I think people still need a little help for the use cases.

[00:13:56] Jan Griffiths: Yeah. It's not an it thing. I think that's [00:14:00] often a misconception with technology. When we talk about technology like this, we go, okay, it, figure out how to use ai. Okay, you got that? Come back and give us a proposal. You've gotta look at it from a holistic business sense.

You've gotta agree in my mind as a leadership team, all right, what makes sense for our first use case for the implementation of ai. Where are we seeing maybe a lot of transactions, a lot of humans doing a lot of mundane work. Maybe there's a lot of errors to start to identify criteria and start to identify our project and then work together on that project.

There's an article that McKinsey wrote, and I will link it in the show notes and they talk about, leaders today must have what they call a second muscle, and that is they must be tech savvy. And it doesn't mean that you need to know everything about ai, but what it does mean is that you can't [00:15:00] throw it over the wall to the IT department.

[00:15:01] Bryan: More importantly, Jan, I think leaders need to be open to learning from individuals in the organization and how this can help the organization. How this can be build. It's not about leading and telling everybody and dictating this is the way it's gotta happen. No, we're dealing hmm. Technologies that, you know, whether it's AI automation or a bunch of other technical trends that nobody is a technical expert. well, team, what can we use this for? What should we be losing for? Can you enlighten me? okay. If I was to do a, what would that do? If we were to do B, what would that do? You know, talking through the scenario, planning and moving, and, Cheryl, you appreciate this in the book, how to make AI useful from the tactical aspect of just. Trying to play whack-a-mole with the potholes to a more strategic application of how does this threaten Our organization? leaders have to be willing [00:16:00] to listen, unlearn as much as they relearn in many senses. The ways that they've been dictating and ways that they've been charging business are not necessarily the paths forward.

There's a great article out In Business Insider with a history professor saying AI didn't break college. It expressed how broken it already was talking about how AI's application and learning process are filling holes that weren't there. And I think it's a really interesting written piece on why and how the education system needs to really think about changing bail because of the advent of AI over the last few years.

[00:16:33] Cheryl Thompson: Yeah, I think it's just changing the way we're all thinking. And I agree with you, Bryan, on what you said about leaders, but I also think leaders need to go first sometimes as well, and signal it's okay and talk about how they're using it so they create that safe environment. And I love what you said about talking to the team.

How can we use this? Like what are the things that are just a pain we would like to automate or make easier and really go after those things [00:17:00] first, you know, not going after the things that people love to do, but what are the things that people dread doing? Let's see what we can do with AI to help us there. And you know, I am 59 and so I am not a tech person, and so I think if I can do it, anybody can do it. for me, just thinking about all the things I dreamt about doing in my business two, three years ago, I'm able to do now because I have this copilot I'll tell chat, GPT or Claude, I'll say, talk to me like I'm 10 years old and walk through this with me step by step.

And now AI is built into all of these tools. So notion, I love using notion to organize everything. AI is built in there. Zapier, a tool to automate things. Ai, you can use copilot within ai. So now I don't have to worry about downloading my recording from Zoom and uploading it to Vimeo. It just happens, and I get an email, right? I would've never been able to do that six months ago.

[00:17:53] Jan Griffiths: This episode is sponsored by UHY. Join us January the 14th at the Detroit Athletic [00:18:00] Club for their Automotive Supplier Outlook. Real talk on AI, margins, and the culture shift suppliers need to rise.

Sign up the link is in the show notes and I'll see you there.

[00:18:13] Bryan: Look, I think it's all about normalizing AI as a partner. Encouraging the curiosity, the fear aligning our culture for change. Focused around the usefulness, not the hype, here's how this can be used to help me, my team, my organization. And I think that the fear side prevents a lot of us in certain roles from touching and leveraging this ways. And I think the folks who are embracing AI tools today on the leading edge are going to be hard to catch up with. Many of those are the leaders that we've seen before, the bright folks that have always been forward thinkers saying, okay, this is gonna allow me to do more faster.

And I think that, same employees that we wanted to hire before, but they're, empowered by new technology. [00:19:00] And so I think Cheryl, folks like you who are saying, okay, I need to change, to leverage these tools to create more, faster, better material. You know, where it's going.

I mean, Look, I, went. a presentation the other day and said, how would an audience of X, y, Z interpret this presentation? And had some great suggestions in there.

[00:19:19] Cheryl Thompson: Yeah.

[00:19:20] Bryan: Me listening to the electronics assistant and saying, Hmm, that's a good idea. I'm not agreeing with that one. Hmm, a great idea.

[00:19:28] Cheryl Thompson: Yeah,

[00:19:29] Jan Griffiths: Yeah.

[00:19:29] Cheryl Thompson: discernment and I agree there is still a lot of fear out there. There are still companies that have it locked down. People have to sign something saying they're not going to use it. And I think you're right Bryan, they are gonna fall behind. You know me coming from a very large organization.

You know, an OEM where it's just, bureaucratics and red tape galore. And now being a very small business owner and now meeting other business owners and seeing how fast they're able to move with ai, these small businesses and startups, they're gonna lap the bigger businesses, [00:20:00] right?

[00:20:00] Bryan: Absolutely. And then I think that the newer startups even have, an advantage over folks who've been around for a year or two because these tools are just so quick and can create such an inertia. But we have to be mindful. This is just one tool in the quiver.

And we, have remember that this is a copilot, not an autopilot.

And. other things are gonna change in ways that we can't predict. I mean, open AI is changing the foundations of chat GPT many times a year at this point. That means even, if chat p version X, y, Z provided a response, it couldn't replicate it, nor would you expect the next version to replicate it. all it is is just great suggestive evidence and direction.

[00:20:45] Jan Griffiths: Tell me. The generational response, if you will, to ai. What are you seeing, Cheryl?

[00:20:52] Cheryl Thompson: Well, it's interesting. I just attended a talk. It was the Women in Manufacturing Conference, and there was a person that spoke on generations [00:21:00] in the workplace. Right? We've got some traditionalists left. Still, we've got the boomers, we've got the Xers, we've got millennials, and then we've got the Zs.

And she had a slide up there. How much does each generation trust ai? And I thought it was going to be Gen Z, you know, out of the

[00:21:15] Jan Griffiths: Yeah.

[00:21:16] Cheryl Thompson: was not Gen X trusts it the most. And I think about that. You know, I'm on the generation that has seen the most change. I was just talking to somebody the other day about running around with a tape recorder in my car.

Right.

[00:21:27] Jan Griffiths: Yeah.

[00:21:28] Cheryl Thompson: Listening to the radio, trying to hit record when my song came on so I could make my own little playlist. And so I find this stuff so fascinating. And then I think my personality is wired a little bit for this as well, but the Gen Zs, they have come into a world where social media and everything that's out there, there's so much misinformation and so there's already a little bit of that mistrust. And so that's what the expert was saying. And then the boomers trusted it the least.

[00:21:54] Bryan: I look at my parents for one and they're using Claude left and right now. I [00:22:00] think the boomers will embrace this as they learn, and older adults may take time to embrace new technology, but when they do and see the value proposition, they learn very quickly. It's all about opening one's eyes to the value proposition.

[00:22:12] Cheryl Thompson: A friend of mine her mom is 84 and she just hooked her mom up with a chat GPT account, and she said, mom, if you hear that noise in the furnace, talk to Chad about it. And then her mom sent her an image that she created out of nano banana. I mean, look at her. Go 84.

[00:22:28] Jan Griffiths: That's awesome. Well, I've got a, very personal example to validate your point about Gen Z Cheryl and my daughter scolds me for using ai.

[00:22:40] Cheryl Thompson: Oh no.

[00:22:40] Jan Griffiths: She believes that AI is gonna make people stupid because you're not gonna be exercising your brain. And she doesn't use it. She won't use it. She's in college and she does not use it, is she's not afraid of it.

I mean, she'll play with it, but no, she says you're not using your brain to think. [00:23:00] So MIT research scientist, what you gotta say about that?

[00:23:03] Bryan: There is a few studies out, that show that neural activity is lower. And I think that the neural activity is always gonna be lower if you ask automation to solve a problem for you. the question is, are we delegating to the machine? Or are we collaborating with the machine? We have not really asked that question yet, I think the studies that are out there that show in the lower neural levels are really about delegating to the machine. want to know when we play ping pong with the AI agent and we are thinking through the content and using the feedback and collaborating with it as a copilot, you know, I'm spending a lot of energy strategically. I was not spending I'm spending less energy tactically because quite frankly, it phrases things quite reasonably well without thinking about it. in one sense, I am probably losing skills in my ability [00:24:00] to craft tactically strong sentences and strong structure. the other hand, I'm exercising my ability and capabilities to think more strategically. it is a balancing game. Skill atrophy with any form of automation is going to exist.

The question is, where do we want that atrophy to be and what do we want to use the accelerated capabilities for? So I think this is a good societal question, and I think your daughter's saying, Hmm, I wanna learn everything the old fashioned way. You know, you can, but you're gonna miss many opportunities that you would've been able to learn if you had embraced, support tools in some aspects of what you're doing. Quite frankly, grammar Check and Spell Check has been around for, since the dawn days of word processing. We are talking about grammar check and spell check on steroids, and that alone is a huge augmenter of time and the output written work.

[00:24:57] Cheryl Thompson: I agree a thousand percent. I think when [00:25:00] I first started using it, I was in the delegation mode and I could definitely feel a drop in in my ability To think. But then when I started using it more strategically, I'm just thinking so much bigger, I created like a business and leadership coach for myself and my team inside of Claude.

So today I had to have a conversation and I had our enneagrams, our kolby types, you know, all our personality types in the backend. And so it was able to coach me on how to have this discussion. And it was so helpful because, my Gallup. My strengths finder. I am an achiever, but I'm also a harmonizer, and she is an Enneagram eight, which is like very straightforward, say it like it is, but she also likes her freedom.

So this conversation we were having, it was like, okay, you're an achiever, but you don't like conflict. So that is why you're so frustrated, she wants her free. So it was just so helpful in guiding me in the conversation, things I would've never really thought of before. So for me it's a [00:26:00] big collaborator and a partner.

[00:26:01] Jan Griffiths: We talk about Bryan, I like what you said. We have to decide are we gonna delegate or are we gonna collaborate? Now, agentic ai isn't that delegating it.

[00:26:11] Bryan: In its current form, agentic AI is more delegation. The question is, is it all delegation? Is it is a whole piece. We need to get to the point of deciding how much machine intelligence we want to fuse with human expertise and where, so it is not about a one size fits all answer. It is, you know, what is. the intended application, balance of human expertise and machine intelligence. So in some aspects, yeah, a hundred percent. Machine intelligence can change traffic lights. When a car pulls up to a light. Humans don't have to have a role there anymore. We haven't for quite some time. On the other when it comes to making strategic business decisions, [00:27:00] I'm not so sure I'm willing to ask chat. GPT, how should I invest a billion dollars today? Although is probably going to provide you with a better answer than the average advisor. Now

[00:27:14] Jan Griffiths: Hmm.

[00:27:14] Bryan: We all hope we are working with a better than average advisor or have an advisor team that together collectively performs better than ChatGPT.

[00:27:23] Jan Griffiths: Hmm. That's interesting.

[00:27:25] Bryan: you recruited a random financial advisor off the street, there's a 50 50 chance that chat. GPT is gonna give you a better direction at this point, I would guess.

[00:27:34] Jan Griffiths: Well, making business decisions. My background is a lot in purchasing and supply chain, and I was at a conference a few weeks ago and we were talking about the evolution of procurement function and the integration of ai. And it starts with augmenting basic tasks, transactional things, taking care of those, okay, we got that.

But then it moves to a point [00:28:00] where the leader of a procurement function has an army of agents, basically of commodity experts that are programmed to make decisions, sourcing selection. Decisions. So at that point we're really in the delegation stage. Although they did say though that, obviously there's gonna be a human, A human will have to look at that output. You can't just automatically just trust it. I wouldn't trust it right now to make a source decision just based on my little LinkedIn example.

[00:28:31] Bryan: And look, you're talking about where the hope is. Agent AI and I think there's a real possibility that's the case, but. Over automation is ripe with failure at times, and, so I think we will see more and more a balance of, agents may go out there and negotiate but at the end of the day the human process may actually produce better negotiations 'cause it's emotional. And the stronger negotiator is not [00:29:00] necessarily the stronger AI system, it's the emotional component that's in there. And we find some hybrid of the two.

We work with folks that we begin to build trust in over time and. the bots negotiating for us don't have that critical element. Larry, who I've been talking to and working with for 20 years, has always come through today. I need to make sure I negotiate for a shipment. I pay well, I procure well, but I'm guaranteed a delivery 'cause I gotta have something in the just in time system tomorrow. different than I'm trying to book something six months out, seven months out, Okay. You know that stuff's gonna be hard to codify.

And codify successfully producing the outcomes that we want. And we expect, remember, we can create outcomes. They just may not meet the expectations of us.

So, we are the failure aligned, we're the failure aligned in delegation, and we're the failure line in receiving. So just automate it all away, it'd work, but not necessarily the effective solution we're looking for.

[00:29:49] Jan Griffiths: Yeah. And you can't codify a bad culture, can you? That's what you said in the last episode. So like Cheryl, I know you got a lot of thoughts around that.

[00:29:57] Cheryl Thompson: Well, I was just thinking about Tesla. [00:30:00] I think, you know, I've read about Tesla and how they're using ai, you know, and from what I've read, they have built AI into how work gets done. Right. And they don't have all the legacy, like the traditional OEMs do. They've got flatter structures. They've got where the AI people are sitting with the engineers. So I think that would be really interesting to see, you know, there's some things maybe about the culture we would not want to Right. You know, I've also heard there's a lack of psychological safety and just this always on culture. So, I think we need to be learning and taking the good and leaving the bad. I, think we do need to be talking about it more. I think we need to work on our culture because, I see two extremes right now. I see some managers lock everything down, don't use it. I mean, some sites are completely blocked and then some just open it up and they're that laissez fair approach and people are left wondering what's safe, how do I use these tools? So I think we've got a ways to go and there's a and. Opportunity.

[00:30:58] Bryan: Leadership today [00:31:00] means observing what's going on and rounding us and beginning to adapt faster. We can't be standing still waiting to figure things out the old fashioned way. The Titanic needs to change we need to become much more nimble, much more fluid organizations if traditional Detroit based or OEMs and suppliers are going to compete any a very fastly accelerating marketplace.

[00:31:22] Cheryl Thompson: A hundred percent agree

[00:31:24] Jan Griffiths: and to quote my friend from McKinsey, Samir Kushalani standing still is both prohibitive and existential

[00:31:32] Bryan: Yeah, I

[00:31:33] Jan Griffiths: is, yeah,

[00:31:35] Bryan: Not only is Tesla using these tools, our, our competitors in China are as well, we are looking at cultures that are embracing and accelerating with tools. Now, I'm not gonna say they solve time and provide efficiencies at all points. We need to understand where they help. Where they don't, where they can be, the collaboration can produce a better product, and we need to begin to think about how do we invest strategically and then [00:32:00] accelerate smartly.

[00:32:00] Cheryl Thompson: I agree. You know, we've got a workforce shortage. I keep hearing this number of 400,000, and so we think about all the knowledge that is about to walk out the door. I think so much of that knowledge can be captured with ai. You know, you can c create custom GPT with somebody's brain.

[00:32:18] Bryan: You can go through 50 years of documentation and potential find something with search that

[00:32:22] Cheryl Thompson: Yes. Oh my gosh.

[00:32:25] Bryan: I can't find using any traditional method

[00:32:26] Cheryl Thompson: Absolutely. Absolutely. And you can help people learn faster, you know? And Kaia, we're right now all about helping organizations learn faster than the pace of change because we've got a lot of change coming at us, and I think we're gonna need to leverage these tools. And I think right now most people are only using 1% of their potential.

[00:32:46] Jan Griffiths: Yeah, I like what you said, learn faster than the pace of change. And that lines perfectly, Bryan, with your thought process about it's the human that will actually slow down the rate [00:33:00] of advancement of ai.

[00:33:01] Cheryl Thompson: Yes.

[00:33:02] Bryan: Will we let AI change us effectively is a, is important question. Centerpiece, my recent book. Look, we're sitting here talking and I'm laughing in some sense 'cause you know, I'm sitting here, I have Outlook on my computer but MIT has not allowed us to adopt co-pilot into our email boxes yet. And I can't find anything. I would. Be blessed to have copilot searching my inval. The amount of time that would free in searching for information. I know it's there. Just traditional search approaches don't index it well.

[00:33:30] Cheryl Thompson: Oh my gosh, that's so funny because you know, I just upgraded to the 365 copilot and at the end of the week I always run a prompt and I'll tell it to look back at my last week, all my emails. Send emails, look ahead at my calendar, 14 days and tell me where, I need to prepare, where I have conflicts, and it's so helpful.

And then I learned that I can automate that. So now I set up a workflow every Friday at five, it'll run by itself. So

[00:33:57] Bryan: would, I love to have access to

[00:33:58] Jan Griffiths: Oh.

[00:33:59] Bryan: [00:34:00] folks around me, whether they're an it or others that have fear of it, but I just want to find the email. I know I got last week from someone who was talking about some topic area I'm interested in and, I know it's there.

[00:34:10] Jan Griffiths: All right. In closing today, I wanna hear one piece of advice from both of you to leaders out there in the auto industry that are perhaps, I would say at the stage where they're comfortable playing around with chat GPT, but they wanna take it further with their team. What do they do? Bryan? Let's start with you.

[00:34:29] Bryan: The future doesn't belong to those who sit idly by, it belongs to those who really begin to think about how does it become useful for them, their organization and society at large. So these tools have value. How does it really manifest itself in my organization and how do I put that to practice and how do I question day by day whether I'm using it too much or too little.

[00:34:51] Jan Griffiths: There it is, Cheryl.

[00:34:52] Cheryl Thompson: I would. Start playing around with it in your personal life. It just gets you thinking differently. It can make you be a better human. [00:35:00] Just have it coach you, talk to it about the challenges, the frustrations that you're having and, and just start there. And then your brain starts rewiring a little bit and then you start thinking about, oh, okay, how can I solve this problem at work or in the business?

[00:35:15] Jan Griffiths: There it is. Perfect. Bryan, Cheryl, thank you so much for joining me today.

[00:35:20] Cheryl Thompson: Thank you for having me. Happy to here.

[00:35:22] Jan Griffiths: Thank you for listening to the Automotive Leaders Podcast. Click the listen link in the show notes to subscribe for free on your platform of choice, and don't forget to download the 21 Traits of Authentic Leadership PDF by clicking on the link below and remember. Stay true to yourself, be you, and lead with gravitas, the hallmark of authentic [00:36:00] leadership.