0:00:00.2 Junior: In the game of organizational effectiveness, LeaderFactor has pretty good seats. We work with some of the biggest, brightest organizations around the world. We do a lot of work domestic in the United States, but probably half, if not more of our work as of late has been international. And so we get to see trends, industry trends, market trends, organizational, like OD trends, we get to see trends in leadership. And all of those patterns inform the way that we advise our clients in their search for cultural vibrancy and market performance. Those are the two edges of the sword that we try to attack. You need healthy culture, but you also need to go and get things done. You need to execute, you need to innovate, and you need to create value. And one of the biggest disruptors that we have seen as of late is AI. So when I say disruptive, it's not just generally speaking. The world has AI now. I'm saying the organizations that we work with every day are trying to figure out how to deal with this. They're trying to grapple with it. How does it relate to leadership? L&D folks are wondering, how does this affect what I'm going to do? Is this a tool for me? Is this a threat to me? And what I find is that many organizations are asking the wrong question.

0:01:34.9 Junior: They're asking, what can AI do? It's the wrong question. The right question is, what can I do with AI?

0:01:43.6 Timothy Clark: I love that, Junior. So say that again, people. That's not going to sink in to our viewing and listening audience the first time. Say that again.

0:01:54.0 Junior: I'll say it several times throughout the episode. But yeah, they're asking this question. And by the way, we're like into the intro now, but. Welcome back, everyone, to the LeaderFactor. I'm Junior here with Tim. Welcome back.

0:02:05.6 Timothy Clark: Good to be with you.

0:02:06.5 Junior: But yeah, that's the question. Not what can AI do in a general sense, what's its capability? But rather, what can I do with AI? And that's the question that we hope that every listener asks by the end of the episode. And we're hopefully going to give some prompts, no pun intended, for you, what you can do as an individual, as a leader, as one of those who's leading leaders and helping develop leaders to help you give some semblance of organization to what's going on right now in artificial intelligence. We're not going to talk about this as technologists. We're going to talk about this from the perspective of leadership development training.

0:02:47.8 Timothy Clark: Right? So if you're an L&D or you're in talent management or one of these related fields. And our advice is very simple. Wait and see, and let's see how it plays out.

0:03:00.3 Junior: Right. Exactly.

0:03:00.9 Timothy Clark: Yep.

0:03:01.5 Junior: Goodbye, everyone.

0:03:02.2 Timothy Clark: I'm just kidding. That is not our advice. But a lot of people are doing that.

0:03:06.6 Junior: Yeah.

0:03:07.0 Timothy Clark: In this space.

0:03:07.9 Junior: Yep.

0:03:08.4 Timothy Clark: And that's why we are addressing this topic in this episode.

0:03:13.0 Junior: So while we won't dive into this as technologists, we will set the stage a little bit. AI in context, we've had industrial revolutions of the past, and that is probably how I would set up the stage to talk about AI. We've had mechanization, we've had electricity, we've had computing and digitization. Now, each of these, what do we call them? Probably revolution. I think that's the right word.

0:03:41.7 Timothy Clark: Yeah. They're eras.

0:03:43.7 Junior: These waves have required leaders to adapt every time. When we had mechanization, it required people to adapt. Massive change. Electricity, massive change. Internet, massive change. And obviously, there have been innumerable others, but there's some big ones. And if we're going to put four or five big ones on a list, we have to put AI on the list.

0:04:07.9 Timothy Clark: We do. So, Junior, I think what we're seeing is we interact with colleagues around the world in learning and development, in talent management, we're seeing more confusion than clarity. We're seeing more defense than offense as they respond to AI. What should we do? This is what we're seeing. This is the general... I'd say the general trend.

0:04:34.5 Junior: Yeah. And just at the outset here, it's important for people to understand that we're in this. So if you're like, in AI and you're like, these guys are going to have nothing substantive to say. Give us 30 minutes. Okay. I'm sure we're going to come up with something half decent. So this isn't just another tool. It's a paradigm shift like the others, which required change in leaders, not just technical ones. And that's an important point here that we'll make for AI as well. It requires change from everyone, regardless if you're in the technology or not. The Internet came and did that require the change from everyone? Yes, it did, and quite rapidly at that, so.

0:05:20.9 Timothy Clark: But even the Internet, Junior, was much slower.

0:05:24.3 Junior: Yeah.

0:05:24.8 Timothy Clark: Than the development of AI. That's one of the striking features of this revolution.

0:05:30.9 Junior: Yeah. Many argue that AI is way bigger than the Internet because the Internet is connecting people to information. That's what the Internet does. AI can take that information, it can decipher it, it can rearrange it, it can learn from it to then go and act on your behalf, on its own behalf, eventually, not in the distant future, it will be able to improve itself. So once AI achieves that point and can improve its own models now we'll be along for the ride.

0:06:01.7 Timothy Clark: That's right.

0:06:02.1 Junior: In a really interesting way. So the first big point that I want to make is that AI is not a tech issue. At least that's not how I want our audience to think about AI. Don't think about it as a technical issue. That's the easiest way for you to dismiss it. If it's an other people problem, if it's a technical people problem and not a me problem, I don't have to do anything about it. That's the sit, wait and see what happens approach which will end poorly.

0:06:27.4 Timothy Clark: Right.

0:06:28.2 Junior: So the early days of the Internet... Are you an appropriate resource to consult for the early days of the Internet?

0:06:36.4 Timothy Clark: Yes, I am actually. I'm a resident expert, thank you very much.

0:06:40.6 Junior: Right on. I want to use that example to help shed some light on what the transition was like for, and what it will be like for AI. So what happened?

0:06:51.3 Timothy Clark: Junior, just for the listening pleasure of our audience, let me say that when I was a freshman in college. I used a typewriter to type term papers. I am not kidding.

0:07:07.0 Junior: Yeah, well, a lot of our audience will commiserate, I think.

0:07:09.8 Timothy Clark: Yeah, it's pretty amazing.

0:07:11.6 Junior: And some of them will be like me. And remember hearing the dial up tone when you pick up the phone and someone's on the Internet.

0:07:18.6 Timothy Clark: And then by my senior year in college, this is how far we had advanced. I would go to a computer lab and I would rent a computer, right. A personal computer, a DOS based personal computer. And I would rent the computer for like an hour or two and I could type a paper and then I could print the paper. They had printers and you would pay for each page. So that was that... We leapt forward to that. By the end of my undergraduate experience. There you go.

0:07:57.0 Junior: So what were you thinking about the world when this was now on the stage, you had computers, you started word processing. How did you see that transition? Was it important to you? Did it suddenly make your life easier? Were you scared of it? Like, what was the general sentiment as you started using that?

0:08:16.9 Timothy Clark: I don't think it's... I think we could see how the useful parts of it and we were pretty excited about it. But it evolved, I think much, much slower than AI.

0:08:31.9 Junior: Yeah.

0:08:32.5 Timothy Clark: By the time, I mean the next thing was rudimentary email.

0:08:36.9 Junior: Right.

0:08:37.6 Timothy Clark: And then you could do an attachment. That was revolutionary. You could attach something.

0:08:43.0 Junior: Yeah.

0:08:43.5 Timothy Clark: But it was pretty slow paced back then.

0:08:46.7 Junior: It's one of the things I want to call out, which is why I think that this shift is so much different than that shift. The application of the, of computation at that point. Very straightforward. Like we have a few different things we can do. We can do Word processing. Right. Great.

0:09:03.9 Timothy Clark: Yeah.

0:09:04.8 Junior: There's not a whole bunch of other stuff that you could do in the beginning.

0:09:08.4 Timothy Clark: Right.

0:09:09.0 Junior: It evolved certainly over time. We're here now, but it's taken a little while. I think that many leaders, at least this is a pattern that I'm seeing, is I've heard this phrase. Yeah. Our technology teams are on it. What? Okay, so in the Internet era, people would say that too.

0:09:30.6 Timothy Clark: Right.

0:09:30.9 Junior: Our technical teams are on it. But if you said that for too long as a leader in that era, pretty soon there's another executive who's using email, uploading attachments, and he's eating your lunch. Meanwhile, you're still typing on a typewriter and sending letters and doing whatever it is you're doing. So my point here is that it's again, not another people issue. And if you didn't adopt the Internet, you got left behind. If you don't adopt this, you'll get left behind faster. So you've probably heard Jensen Huang, CEO of Nvidia, say this. If you're not engaging AI actively and aggressively, you're doing it wrong. You're not going to lose your job to AI, you're going to lose your job to someone using AI. Your company isn't going to go out of business because of AI, but because another company used AI. It's the same thing. It's a tool. AI isn't going to arbitrarily come and take your job.

0:10:29.6 Timothy Clark: Right.

0:10:29.9 Junior: Right. It's not going to be some sentient thing tomorrow that's going to come and displace you, but someone who understands the tool and understands its application absolutely will come and replace you.

0:10:38.9 Timothy Clark: That's right. I love what he said. You're going to lose your job to someone using AI.

0:10:43.8 Junior: Yeah. Now, he's incentivized to say this as CEO of Nvidia, but I think it's...

0:10:48.3 Timothy Clark: I think there's a lot of truth to it, though.

0:10:50.8 Junior: Of course, there is.

0:10:51.5 Timothy Clark: It's not going to just automate you, but it will help your productivity.

0:10:58.7 Junior: Yeah.

0:11:00.1 Timothy Clark: If you can use it.

0:11:00.4 Junior: And we probably all heard Zuckerberg... Well, it was it last week, two weeks ago, he said the AI is going to start replacing his mid level engineers. That's interesting. The Internet's been having a lot of fun with that. But the point is that that's the inevitable end. We're in this era of agentic AI. AI can do complicated jobs. Just recently we watched the launch of the Operator of ChatGPT. Yeah, that is really interesting. If you haven't watched that, do that.

0:11:31.5 Timothy Clark: Do your shopping, make your reservations.

0:11:34.0 Junior: And we're already dating this episode by saying that. Right. And who knows what's out when this comes out, which is not that far in the future.

0:11:41.4 Timothy Clark: That's right. But that just shows you this, the speed of this.

0:11:43.8 Junior: Yeah. So if AI is taken over and there are no humans left on the earth, then I guess to the AI, you won. But if you're a human watching this, then we still have time. Okay. Adoption. Personal adoption will be fast. This is where I think things start getting interesting in this conversation. ChatGPT had 100 million users in two months. 100 million. So to put that in context, if you look at the adoption of like the television set, the personal computer, the Internet, Angry Birds, right. Those inflection points that people talk about, this is like so far ahead of anything that we've ever seen.

0:12:19.4 Timothy Clark: That's incredible.

0:12:20.9 Junior: But here's the irony. Despite that growth curve, enterprise adoption will likely be slow. And this is where we start talking to the L&D folks and this becomes interesting...

0:12:30.6 Timothy Clark: This is where it gets interesting.

0:12:30.8 Junior: For the leadership application. So there's a book called Crossing the Chasm. You have it here?

0:12:36.5 Timothy Clark: Well, actually it's funny, Junior, because you asked me this week, you said, hey, have you ever heard of Crossing the Chasm? You know, I think I read that book and I pulled it off my shelf.

0:12:47.6 Junior: Yeah, you did say that.

0:12:48.3 Timothy Clark: And. And I went through all my highlights because, see, I got hard copy and I used to use... Well, I still do. I use highlighter. Yeah, here it is.

0:12:58.0 Junior: All your notes.

0:13:00.1 Timothy Clark: All my notes.

0:13:00.7 Junior: That would be a valuable thing to the world is all of your highlights. If we could put those on SparkNotes, we would do really well. But Crossing the Chasm is interesting. I read that book years ago. What I didn't realize was the publication date. Obviously, you knew it came from a certain era, but the publication date on that book is early '90s. I think it might be '91.

0:13:21.2 Timothy Clark: It's '91.

0:13:21.8 Junior: Is it '91?

0:13:22.5 Timothy Clark: Yeah.

0:13:23.3 Junior: So if it's '91, this makes it all the more cool. So Crossing the Chasm explores market dynamics and technological adoption into vertical markets. And his argument is that the adoption curve is a little bit different than what we might have originally thought, which we'll talk about later, but that enterprise adoption is slow, that it takes, there's a big lag between adoption, the early adopters that are individual users, and then into mainstream markets. I think, and many think it seems obvious that the adoption curve will look similar for AI. Anything stand out to you about that book or that concept?

0:14:07.9 Timothy Clark: It did, Junior. I was going back through my highlights. Let me just read this part here. He says...

0:14:15.7 Junior: Jeffrey Moore.

0:14:16.0 Timothy Clark: Jeffrey Moore. To maintain leadership in a mainstream market. Right. Mainstream market, you must at least keep pace with the competition. It is no longer necessary to be the technology leader, nor is it necessary to have the very best product. But the product must be good enough. And should a competitor make a major breakthrough, you have to make at least a catch up response. So I thought that was really interesting. But then he says, as he says later on, he says the basic flaw in the model, as we have said, is that it implies a smooth and continuous progression. I, that's, I think that's where we're going to have some challenges because I don't think it's going to be as smooth as we think it might be.

0:15:12.0 Junior: No. And the reason that he argues for kind of a S curve adoption is enterprises are built for stability, not agility.

0:15:22.0 Timothy Clark: Right.

0:15:22.6 Junior: And so...

0:15:23.1 Timothy Clark: Very good point.

0:15:23.8 Junior: They're interested in maintaining whatever competitive advantage they've built, been able to gain.

0:15:31.2 Timothy Clark: They've invested in that.

0:15:32.9 Junior: Oh, yeah. And it's difficult to turn a big ship.

0:15:35.8 Timothy Clark: Right.

0:15:36.0 Junior: We've talked about this principle a lot. But you pitch that rudder, it's going to take a while for you to make a significant turn.

0:15:43.1 Timothy Clark: What do you call that strategy, Junior? You've got a term for that.

0:15:46.7 Junior: A long jump?

0:15:48.3 Timothy Clark: Well, not just a long jump, but based on...

0:15:51.2 Junior: Path dependence?

0:15:51.9 Timothy Clark: Path dependence. Can you explain that?

0:15:53.8 Junior: Yeah, yeah. So two, which are really interesting. So for any fellow strategists out there, this is Leventhal and then Sydney Winter. There's a whole bunch of cool stuff here on path dependence and the long jump, which are, comes from rugged landscapes. But anyway, path dependence is the idea that where you are now is a function of where you've been. And the opportunities for movement today are based on all of your historical behavior. And so you don't have an opportunity to fundamentally shift your position on the competitive landscape overnight because you are constrained by your previous choices. So I can't go and compete in the NBA. Right. Why? Well, I'm not tall enough, but also that's not what I've dedicated my life to. That's fundamentally different. Right? There are a whole bunch of things that I just can't do because of my current position.

0:16:48.2 Timothy Clark: Right.

0:16:48.8 Junior: Which is both a liability and an asset. Long jump comes from the theory of rugged landscapes, which means that every peak in the market is an opportunity to go and compete. So if I'm choosing to compete, let's say in fast, local, fast food, I'm not going to be able to tomorrow go and compete in automotive. It's a different set of skills.

0:17:13.0 Timothy Clark: Can't deal.

0:17:13.4 Junior: It's a different revenue model. It's a different, it's everything is different.

0:17:16.5 Timothy Clark: You walked through some one way doors, Junior, you made some decisions and you can't go back.

0:17:20.7 Junior: Yep.

0:17:21.0 Timothy Clark: In terms of allocating resources.

0:17:23.0 Junior: Yep. You've made some choices. And so a long jump would be able to go peak to peak and just suddenly on a dime say we're going to go compete in a completely different market. Sometimes that's the play. Most of the time it's not the play. Certainly not the play if you're a big institution.

0:17:37.0 Timothy Clark: That's right.

0:17:38.0 Junior: Most on average of the people watching this are going to be working for a larger organization. Right. And that organization is likely going to move slowly. Here's the point. If enterprise adoption is slow and you wait for the enterprise to tell you what to do about this innovation, you will be slower than the enterprise.

0:18:00.9 Timothy Clark: That's right.

0:18:01.0 Junior: Which means that you are going to be absolutely left behind as it relates to this new technology. You cannot wait for the organization to push you along and come next year, say, hey, this is what you need to know about AI, that is very, very, very unlikely to happen. And even if they do come to you and say this is what you need to think about it, it's probably going to be wrong in two weeks.

0:18:24.0 Timothy Clark: So Junior, we need to underscore this point because what we're saying is that if you move with your organization and if you think that's okay, there's a false sense of security that that's giving you and you look around and you think, oh, it's fine. Look, our technology team's doing this, this team's doing this. We're adopting AI. What we're saying is that, that that's not good enough. Right?

0:18:51.1 Junior: Yeah. Well, and it's never been good enough across any skillset. If you wait for the organization to come do all of your leadership training, is that going to be enough? Are you going to go. Just wait till they say, hey, Agile is important. We're going to put you through some courses.

0:19:04.4 Timothy Clark: No, you're on education welfare.

0:19:06.2 Junior: Best case scenario, your organization cares a little bit and gives you a little bit of resource. That's like best case scenario.

0:19:11.7 Timothy Clark: You're a laggard.

0:19:12.9 Junior: Yeah. And you're not...

0:19:14.3 Timothy Clark: I think that's what we're trying to say.

0:19:15.5 Junior: You're going to develop some skill gaps and if this is making you feel uncomfortable, great.

0:19:21.5 Timothy Clark: Great. That's the intent.

0:19:22.5 Junior: Because we are saying, hey, there are probably some gaps here that we need to close. And that's true for all of us.

0:19:28.3 Timothy Clark: That's exactly right. That's right.

0:19:28.7 Junior: We are not the experts, but we're here maybe canary in the coal mine style saying, hey, this is something to pay attention to because as we said in the beginning, we have some interesting seats in the landscape of leadership.

0:19:44.0 Timothy Clark: Especially as we look across industry, Junior.

0:19:46.0 Junior: Yeah. So if we go to the slide, what are we saying? AI is disruptive, but enterprise adoption will be slow. Why is it slow? The fear factor. There's a huge element of fear in adoption for any new technology. And that happens at the level of the organization and also at the level of the individual. The organization, especially with AI, is going to tread lightly, they're going to tread carefully and they're going to be probably very deliberate and slow as consequence. Individuals will often behave the same way. Oh, the organization's a little spooked by it. People are a little spooked by it generally. Maybe I should be spooked by it. Maybe I should just hang back and hope that nothing adverse happens as consequence of this technology. So the response from fear is freeze. It's in action and a lot of people just do that and call it a day. They wait until it's too late.

0:20:43.3 Timothy Clark: I think we have to go beyond the fear factor though, Junior. I think we have to think about as, as you just talked about, the allocation of resources. If you've been allocating resources a certain way for a long time, you're really dug in.

0:20:55.9 Junior: Yeah.

0:20:56.6 Timothy Clark: Right. So you have a sunk cost.

0:21:00.5 Junior: Yeah.

0:21:01.6 Timothy Clark: Or sunk costs all over the place. And then in addition to that, you have loss aversion to let that go.

0:21:09.3 Junior: Yep.

0:21:11.1 Timothy Clark: Right. Based on the way that you've been allocating resources for a long, long time. So switching costs are enormous. Enormous. And so this is very difficult for a large enterprise. Large enterprises don't pivot. That's not a thing. They move slowly. They can move to a different course of action, but it takes time. It takes a long time. So I think we need to acknowledge that.

0:21:41.5 Junior: Well, and most organizations will go until they hit an iceberg and then they move into obsolescence.

0:21:48.6 Timothy Clark: Yeah.

0:21:49.2 Junior: And so you have to figure out, okay, if this organization's unlikely to adopt this technology as fast as it will need to to stay competitive. Well, you got to learn yourself.

0:21:58.6 Timothy Clark: Yeah.

0:22:00.0 Junior: You got to go out there, and that's where the leadership element of this comes in. And for those of you who are leading leaders and helping develop leaders, you have to pay attention. Practically speaking, that's something that we try to do. Are we going to become an AI company tomorrow? No, we're not. Is AI going to change the landscape in the market that we compete in? Of course, it is. So at the very, very least, we've got to keep tabs. We've got to see what's going on, to see, okay, there's a threat, there's an opportunity, there's an emergency. We have to know what's going on. If we don't, we'll pay for it.

0:22:32.6 Timothy Clark: That's right.

0:22:33.4 Junior: So what do we do? Here's the point. Enterprise application will be slow, but personal application can be fast. So you do not have to keep pace with the organization, which will likely be slow. You shouldn't. You should detach from the pace of the organization...

0:22:49.5 Timothy Clark: Use it in your job.

0:22:51.2 Junior: And say, go for it.

0:22:52.0 Timothy Clark: And that... So this becomes a matter of discovery, a matter of exploration, a matter of experimentation for you within the scope of your job. Regardless of what's going on around you, you've got to learn how to use AI in the context of your job.

0:23:07.8 Junior: That's right. And some of us work in highly regulated industries. Maybe you're in defense, maybe you're in healthcare. Maybe there's not an opportunity for you to use this in as straightforward a way as you might. If you were in some startup trying to do something, you may be prohibited to even have that on your device. Right? That doesn't mean that you can't go explore on a personal level.

0:23:32.9 Timothy Clark: That's right.

0:23:33.5 Junior: You want to look for every avenue possible to try and test out some of these things. It's your responsibility. So let's talk about application for a second. This is another piece of value that I think we can add. We have to assume that the computational angle of AI will be commoditized.

0:23:51.7 Timothy Clark: Certainly, it will.

0:23:52.6 Junior: Right?

0:23:53.1 Timothy Clark: Yes.

0:23:53.8 Junior: So when the first people had the Internet, massive advantage, how quickly did everyone else get the Internet? Pretty quickly, relatively speaking. Right. So we get back to competitive parity in access to resource really fast. So if you look today, a frontline employee has pretty close to the same computing power as most developers.

0:24:21.7 Timothy Clark: That's right.

0:24:22.8 Junior: Not a massive difference. The way they use that hardware and software, vastly different. And I think that this will be the same. So if you look purely at computation, you look purely at the ability of the tool that will be commoditized. Its application is where the advantage can live.

0:24:42.6 Timothy Clark: That's where it is.

0:24:43.0 Junior: So think about it that way. You don't need to have the best tool. You can be at competitive parity as far as access to resource, but how you use it varies widely. That's why two people can have a computer. One person can make a billion dollars, something, and the other person can send an email to their mother.

0:25:07.2 Timothy Clark: Same machine technology.

0:25:08.7 Junior: Same machine. What do you think about that? Have you seen that as access to tools has changed over your career?

0:25:16.9 Timothy Clark: Oh, absolutely, yeah. The forces of commoditization are chasing all of these things. So we begin with computing, but going back to what you said, how can you use the tool? And Junior, I want, I want to point out a way to use the tool, a way to use AI.

0:25:34.5 Junior: Sure.

0:25:34.9 Timothy Clark: That I think is most, has been most beneficial for me. And I'm not in your generation. And so I have some disadvantages maybe going in, I don't know, maybe there's a little bit more trepidation, I'm not sure. But the single biggest thing that I've learned and, I think this might be helpful to some of our viewer, viewers and listeners, and that is use AI to use AI.

0:26:00.0 Junior: There you go. Love it.

0:26:01.7 Timothy Clark: This is the single most helpful thing that, or helpful way that I've been able to incorporate AI into what I do. Use AI to help you use AI. Let me give you an example. So I did, I just, I did this one. I said, I asked AI.

0:26:22.3 Junior: So you're interacting with ChatGPT, right? So chat interface, just to be clear.

0:26:27.2 Timothy Clark: I am. And I'm asking AI. So this is a query. And by the way, you know, I didn't take a, I didn't go to a class in, in script engineering, by the way. I'm just learning how to do that myself. But I said here, here's the prompt: Give me a practical list of ways that the average employee can use artificial intelligence in their work. Whoa!

0:27:00.2 Junior: Beautiful prompt, an awesome prompt.

0:27:03.1 Timothy Clark: And we go through specific recommendations for boosting productivity and I'm not even getting into the details. Enhancing decision making. Improving writing and communication. Driving creativity and innovation, personal and team learning, collaboration and teamwork, improving customer interaction, optimizing workflow, enhancing problem solving. And then they give very specific recommendations about how to use, how to do each of those things. That's what I'm talking about.

0:27:40.8 Junior: Yeah.

0:27:41.5 Timothy Clark: Use AI to learn how to use AI.

0:27:45.1 Junior: Yep. If you just go...

0:27:46.5 Timothy Clark: It works.

0:27:47.1 Junior: It works. If you just go into any chat interface and really any model and you ask it help me do my job, you don't have to tell it what you do. And it'll start to ask you the things that it needs to know in order to be useful. Now, granted, not all prompts are created equal. As you said, you're not a prompt engineer.

0:28:03.7 Timothy Clark: No.

0:28:04.1 Junior: But a prompt as simple as that allows you to...

0:28:06.5 Timothy Clark: You can get better.

0:28:07.7 Junior: Get your feet wet and start working on it.

0:28:09.5 Timothy Clark: And you can drill down into any, any of these where you think there's some promise, something looks like it has potential. Okay, let's explore that. Let's get into it.

0:28:19.5 Junior: Yeah.

0:28:19.8 Timothy Clark: And you keep going.

0:28:20.6 Junior: Yep, that's right. So start small. You don't need to start by tuning models, testing every mainstream LLM. You don't have to create your own GPTs. You can just start in a basic chat interface in any platform and just start. One of the generational differences, and this is research based, okay, so don't come after me, but one of the differences between your generation and subsequent is that your generation on average, has a fear of clicking buttons.

0:28:51.0 Timothy Clark: That is true. I'm trying to overcome that.

0:28:52.8 Junior: Right? So in any digital interface, on average, a Boomer has some trepidation around, like clicking the thing, like, I don't know what it's going to do. Like there's this hesitation, right? Millennials, anyone past that, it's like click all the buttons. Like, just click them. Right. And so in this case, everyone who has not yet used AI needs to just go and click the buttons, right? You need to go, just open it up. You can use OpenAI. You have a free... Don't even need an account. Like, just go and try it. You can use Grok, if you're on X, you can use Gemini, you can use whatever you want to use there. Every big tech's going to have their generalized AI assistant. Just go play around. So if you think of the traditional adoption curve, it looks like a normal distribution, right? And you have categories. Every standard deviation has a different descriptor or label. So the first standard deviation to the left of the mean is early majority. The second standard deviation, and that's 34% of the population. The late majority is 34%. Right. So one standard deviation from the mean is 68% of the population.

0:30:12.1 Junior: So just with those two, we account for two thirds of people. Early adopters is the next standard deviation out, which is 13 and a half percent. And then the final 2 and a half percent is the innovators. You don't have to be an innovator. And my suggestion would to be even earlier than an early adopter or early majority. Be an early adopter, which is that second standard deviation, 13.5%. So if you can be faster than 15 than, or in the first 15%, faster than 85% of people, I think that you're going to be okay. If you are even in the early majority, I think things are moving fast enough that you will be left behind and in a practical sense you will be a laggard. So it's somewhat trivial to think about the actual numbers and statistics here. My point is, be earlier than you think you have to be.

0:31:12.6 Timothy Clark: Right.

0:31:13.0 Junior: So if you think that you were going to get into it next year, get into it now, start playing around with it and you can just keep tabs. Even if you're not using this day in and day out, which I would recommend, you can still stay apprised of the direction that things are moving and how it's affecting the market broadly, because regardless of what you're doing right now, if you're in L&D, absolutely, this is going to affect you, for sure. 100%.

0:31:41.1 Timothy Clark: Junior, I got to tell you a little bit about my own personal journey. When ChatGPT came out, I didn't know much about it as most of us didn't, but I played around with it, as a lot of people did.

0:31:55.7 Junior: Yeah.

0:31:56.2 Timothy Clark: And I treated it as a novelty.

0:32:00.1 Junior: Right. Yeah.

0:32:00.6 Timothy Clark: And that first version wasn't great and it hallucinated a lot. It gave some bad answers and we all know that. The current version is, is, is incredible. But I, here's what I did. I kind of, I used it every once in a while and treated it as a novelty. But then I advanced to starting to use it more often and for me, I discovered one application of the technology that blew my mind and that was I started to use it as a research assistant and I lost all fear of pressing buttons. Like I overcame that.

0:32:48.3 Junior: That's awesome.

0:32:48.7 Timothy Clark: Because early in my life, I remember, and I've shared this with you before, but spending hours and hours and hours upon hours in the Bodleian Library at Oxford University, finding stuff, gathering research, go just pouring through the Stacks. I spent hours doing this, and this has blown my mind to be able to use AI as a research assistant, I am just astonished at what it can do. That's one application. There are many, many, many others. But that's what we have to do. We have to use AI to learn how to use AI. And it is absolutely astonishing.

0:33:35.6 Junior: Yeah.

0:33:36.3 Timothy Clark: And we've been using it at LeaderFactor in a number of ways. So now I look at my usage pattern. Guess what? I use it every day now. I use it every day. It's an integral part of what I do. Isn't that interesting?

0:33:53.6 Junior: This is a baby Boomer Oxford PhD telling you that he's using AI every single day.

0:33:58.4 Timothy Clark: That's crazy.

0:34:00.0 Junior: As CEO of a training company, so if you can do it, man, everyone can do it.

0:34:06.0 Timothy Clark: The productivity enhancement is off the charts.

0:34:09.6 Junior: And that's not to demean your technical skill, by the way. I think you're leaps and bounds ahead of most people, which is why I point to you as an example I think is super interesting. For me, I could argue very easily that my productivity has gone up 100% in the last six months.

0:34:26.1 Timothy Clark: Really?

0:34:26.6 Junior: Yeah. I think I'm twice as productive, at least. I have gained back so much time using these tools and integrating them into my work that I feel very confident that today me could take on, like, three clones of me a little while ago. It has amplified my ability to get things done tremendously. And I think that it's going to be exponential. And a lot of what that curve has looked like in terms of impact has been my own skill in applying the technology.

0:35:00.6 Timothy Clark: Right.

0:35:01.1 Junior: And so I know for our team, I started looking into this deeper and keeping tabs. But as I started using it, I'm like, hey, everyone, like, we need to be doing this, because I saw what it was doing for me. And so now almost everyone on the team has paid accounts across a variety of platforms. We're using Gemini, we're using ChatGPT, we're using Llama, we run local AI. We're integrating it into our products. It's everywhere.

0:35:27.6 Timothy Clark: Look at what it's done for us with translation.

0:35:31.0 Junior: Yeah. We built our own translator months and months ago. And, yeah, fun fact. You know how much we used to spend on translation for all of our materials?

0:35:41.1 Timothy Clark: Unbelievable.

0:35:41.8 Junior: We do work around the globe constantly translating material. Anytime we would have to make any change to a piece of content, it's got to go through a professional translator. We're back and forth. If we use a different service, we've got to give them all of the context. We've got to send over vocabulary lists. Absolute nightmare.

0:36:03.2 Timothy Clark: Right.

0:36:04.1 Junior: We have built the native application to our platform that runs translations and we have them checked by professional translators. But we're, I don't know, 10 times more fast, probably a lot more than that, and certainly 10 times more efficient on cost. And like, is that what we do as a company? No.

0:36:23.0 Timothy Clark: It's just an application.

0:36:25.2 Junior: It's just one application of what we do. And I'm sure that there will be other applications that will be more and more obvious for us over time, but when I say that the majority of our team is using this every day, they are. I can see that. So I just, I can't harp on this enough. It's something that I feel passionately about. Not because I'm, like, super into the technology even. Right. Like, our CTO and our developers are way farther down the rabbit hole in the technicalities of AI than I am. Like, I'm a total amateur when it comes to a lot of that, but I try to stay apprised enough to be dangerous. And that will be my final point is that you do not need to be on the bleeding edge, but you need to be pretty close to the edge. So you don't need to know the latest release that was five hours ago, but you probably need to know what happened in the last week. And what's really cool about that is you can even use AI. Hey, what happened this week in AI that I need to know about?

0:37:26.4 Timothy Clark: That's what I mean. That's right.

0:37:26.8 Junior: And it's like, well, here's what happened.

0:37:28.1 Timothy Clark: Just let AI give you the update.

0:37:31.7 Junior: Yeah, well, and what you brought up earlier is absolutely brilliant. Like, using AI to use AI is a wonderful application. It's a great place to start. What happened in the last week that I should know about and how can I integrate it into my work? Right. You can go from there. What final words or thoughts would you have?

0:37:49.2 Timothy Clark: Junior, I would just emphasize what you said, and that is that at the enterprise, large enterprises around the world, they're going to lag in adoption. But for you as an individual, you need to get going. Don't lag yourself. Get going. Jump into AI. Learn how to use it. Think about applications, think about how you can use it. Learn about how you can. You don't even need to think. Ask AI. And that will get you started and then you'll go from there.

0:38:21.0 Junior: Love it. Okay, that's the episode for today. Thank you everybody for tuning in. We appreciate your time. We've covered a lot of ground, as is evidenced. I feel like we proliferate every time, I'm bringing new pens, digital pens. We've got a lot of stuff to keep track of. We've covered a lot of ground. Because of that, we put all of the valuable nuggets, the distillation, the summary into downloadable PDFs and guides for you. If you didn't know that, go check them out. Go to leaderfactor.com/resources. If it's not that, it's probably something close to it that we will put in the show notes. But I highly encourage you to go and download some of those guides because those are helpful, handy, very fast, quick resources that you can use as reference material, moving forward. You don't have to listen to this whole thing over for 30, 40 minutes, just look at the guide. You can also send that link to other people, if you think that they would be interested in this content. With that, we will bid you goodbye and catch you in the next episode. Take care everybody.

0:39:29.1 Jillian: Hey, LeaderFactor listeners, It's Jillian. If you liked the content in today's episode, we've compiled all of the concepts and slides into a downloadable resource for you. Click the link in the description or visit LeaderFactor.com to explore our full content library. Don't forget to subscribe and we'll catch you in the next episode.

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