Ep 832: The Human Side Of AI Readiness

0:00Many employers are investing significant time and money in developing AI strategies. However, having a strategy is very different from having a workforce that uses AI well. So what turns an AI strategy into real change? And who should be leading the work? Keep listening to find out.

0:38Hi there, welcome to episode 832 of Recruiting Future with me, Matt Alder. If you're new to the show, you're very welcome. And make sure you follow us on Apple Podcasts, on Spotify, or wherever you listen to your podcasts, so you never miss an episode. AI is moving from a specialist technology to something employees in large parts of the organisation are increasingly expected to be using. Skills, mindsets, and long-established habits are much harder to change than software, which is why meeting that expectation is proving difficult. If the challenge is mainly a human one, AI readiness is as much a matter for HR and talent leaders as for technology teams.

1:22So what does it take to get a workforce ready for AI and what opportunity does that create for talent leaders? My guest this week is Dr. Michael Hausman, co-founder and CEO of AI Performance Lab. Michael has spent 17 years building AI and machine learning platforms and now helps leadership teams around the world adopt AI. In our conversation, He explains what the human aspect of AI readiness means in practice, why execution matters more than strategy, and why HR and talent leaders are well-placed to lead the change. I'm Michael, and welcome to the podcast. Hi, thanks for having me, Matt. A pleasure to have you on the show.

2:02Please, could we just start off with you introducing yourself, telling everyone what you do, and a little bit about your background as well. Yeah, absolutely. I tell everyone I was a data nerd and doing AI before it was sexy and cool. Then I have that claim to fame. I have a PhD in econometrics, spent about 17 years building AI and ML applications, starting first in HR technology. So building hiring software, I'm sure we'll dig into that. And then moving on, doing more financial services, consumer lending, fraud detection, so on and so forth. And now I spend a lot more of my time actually teaching about AI and delivering keynotes and workshops, boot camps all over the world, unpacking what's happening for executives and helping them leverage the tools.

2:46So yeah, it's been a, it's very different than the PhD program that I came out of, but it's been a really fun journey. And here I am. I mean, it's been an especially sort of crazy two years or so. But as you say, this has been going on for a long time before that. So you've been working with data and, you know, AI as it's developed for, as you say, before it was a thing, before it was fashionable, what's changed the most and what hasn't changed during the time that you've sort of been working in this space? Yeah, these are great questions. I would say what's changed the most is it's really gone mainstream.

3:2315 years ago, I worked for a company called Evolve. We were using data to help hiring managers make better hiring decisions. And I remember we got a lot of attention and press because it was so unusual. Like Moneyball was everyone's frame of reference. Like, oh, you can use data to make better decisions about talent when it comes to, you know, major league baseball teams. But there were articles, you can look them up online, just look up like Evolve and Hiring. And it was the New York Times, the Wall Street Journal. We were very privileged in that. All of a sudden, everyone sat up, took notice and said, you're using data and algorithms to hire human beings into roles.

4:00It was shocking, right? And this space has been around for decades. It predates, you know, me and the hiring work we did. Fast forward to today and it's mainstream. It's weird when three years ago, Chad Chippity emerges, it just sets the world on fire. And now everyone's talking about it. It's an expectation of everyone in the workplace to be fluent in these tools. It's, you know, you see the content everywhere. So I'd say that's the biggest thing is, is back then people were much more skeptical of data and algorithms. And, you know, there's still some skepticism, but it's interesting that folks have accepted, no, no, no, this is really the path forward for businesses, for individuals.

4:41What stayed the same is the challenges. Data is always hard, right? The data that companies have, it's never in great shape. No client company has ever come to me and said, our data is perfect and it's pristine and we're ready to go on this journey. Like that's a challenge. And then frankly, the people getting buy-in. I mentioned, yes, it's mainstream. Yes, folks now believe in it and realize the way forward, but it's still, there's a lot of fear out there about algorithms. There's a lot of worries about job loss. Will they turn into Terminator and try to take our lives? And so the biggest challenge is still getting folks bought in, getting them to use the tools, getting them to kind of acknowledge, yeah, I'm a hiring manager, but AI can make me better as a hiring manager and it doesn't compete with me and my intuition.

5:24Yeah, it's funny when I sort of look back through the podcast archive, we've been talking about AI for about 10 years. And a lot of it was the, there was this big debate about algorithms weren't real AI and what was kind of going on. And it's quite funny to look back on and, you know, to look back on how things have changed. But as you also say, how a lot of things have stayed the same. And I think that the people angle of this is really, is really interesting as well, which is I'm sure something that we'll, sort of pick up on. But AI readiness is a really, really big topic in every industry at the moment.

5:56No, it's an area in which you do sort of most of your work. From your perspective, what does it mean? What does it mean to be genuinely ready for AI, particularly in larger organizations? Yeah, it means I think a lot of it is mindset and culture. It's making sure that the team is excited about the possibilities. They're not fearful that this is going to take their jobs. So there's that. I think approaching AI not as a tool. What research has shown is that it's not a traditional SaaS tool, that it actually is more like a digital colleague. So that's a mindset shift is like, okay, I need to engage with this like I would a person.

6:36And it helps that their chat interfaces, you just converse with it and it can go and do. Thinking of it not as something that just executes instructions, but it's a thought partner. So in the workshops I do, we try to cultivate a lot of those mindset shifts so that folks are really ready to embrace this and absorb the information. And then the second piece is that this is a skill set as well, right? And so we need to teach individuals and employees how to use the tools, what's out there, how to engage with it. Prompt engineering is a piece of it, but more broadly, it's thinking about an engineering and agentic workforce.

7:12It's so funny because it's a technical topic, but the truth is the biggest challenge and the biggest opportunity is the human side of it, is getting an employee base excited, cultivating the mindset, cultivating the skill set. When you do that, they just flourish and they thrive. And that's when we see just transformational results. And I guess one of the challenges with this is because it moves so quickly, people feel that they can't keep up or don't know how to keep up or they're being left behind. I mean, how do you deal with those kind of issues, particularly sort of keeping pace with everything that's going on?

7:47Because it is just moving at an almost ridiculous pace in terms of how the innovation is happening. Yeah. I mean, again, great point. Number one, people don't realize this. There's a reason why it feels like it's moving faster and faster. It is. So technology moves at an exponential rate. If you think about Moore's law, the number of transistors you could fit on a chip, it's doubled predictably every 18 months. And humans have their hard time wrapping around their minds around exponential growth, but doubling and doubling and doubling, that's what's going on. And by the way, it's happening not every 18 months for AI, it's happening every seven months.

8:21So it's happening even faster than Moore's law. So that's number one is just acknowledging you're not crazy. It's happening faster and faster. And by the way, this is the slowest that it's going to be. This is the worst the models are going to become. That said, you're exactly right. The biggest challenge, If you look at the pace of innovation, it's basically going hockey stick. If you look at adoption and usage, it's very flat because humans really struggle to retrain themselves and reskill and to relearn their jobs. I don't want to do the shameless plug thing, but that's a big chunk of what I do.

8:51And what we do at AI Performance Lab is taking all of this signal and helping distill it into the noise that are relevant to a company. In our case, we work with leadership teams. So I'm saying, you know what? There's so many changes. There are thousands of model releases. There are new products. There's news. There's research. We then distill it and we share it with execs. And we say, these are the 10 things. These are the five things that need to be on your radar. And these are the skill sets and tools you need to be cultivating right now. But if you don't have us at your side, that's totally fine.

9:20I think everyone should dedicate an hour a day to what I call AI playtime. And so if you think of it as like a fitness journey, you never get to a point. You don't work out in the gym for a week and say, okay, I've got that handled. I can stop. It's an ongoing journey. And you spend an hour a day and you carve that out. And I think everyone should be doing that, following the key thought leaders, continuing to cultivate those skills and build those AI muscles. And sort of getting into the leadership teams that you work with, what are you seeing in terms of how C-suites are thinking about AI right now?

9:53Because, you know, there are loads of headlines out there about what companies are doing, how companies are thinking. And I suppose what that means for people leading talent functions, how can they, you know, How can they get budget? How can they make progress with AI and their function? Yeah. Yeah. Look, I think there's a lot of initial momentum that comes out of the desire to cut costs, right? I think there are companies out there that approach this from the perspective of, you know what? We have call center agents and we have this and we have that. We can probably, you know, let's figure out a roadmap that allows us to cut costs and headcount via AI.

10:29And look, that is one strategy. What the research is showing is that companies that are early and intense adopters of AI, they actually grow their headcount on average. And that's because it's creating opportunities to do work you couldn't do before. There's a different skill set they're hiring than they did previously. The companies that are leaders when it comes to AI and in terms of their industries aren't using it as a replacement. They're actually saying this is an augmentation tool and we're growing our headcount and we're beating the competition. So I think that's one key thing that I noticed in the companies I've worked with.

11:07Like some approach it as a kind of cost reduction tool. The winners seem to be saying, you know what, we're going to expand our customer base. We're going to grow. You know, our goal is we're going to expand 50%, but we're not going to grow 50 % of our headcount. Right. And so that's one key piece. And then, yeah, the other thing is there was a lot of strategy work. They're going to McKinsey and they're going to KPMG and they're spending a couple million dollars and they're getting a really glossy deck. And that shows them, OK, here's your AI roadmap. And my take is two things. Number one is the landscape moves so quickly that that deck you got six months ago, I don't even know if it's relevant anymore.

11:42Like the tools, like the capabilities are changing constantly. So that's number one. And number two is where companies struggle. Research shows this. I've seen this in my own experience. it's not the strategy, it's the execution and it's the practice. It's really cultivating those skills within the workforce. And that starts with the leadership team. Research shows it flows downward, but we're starting with leadership team and empowering everyone to use the tools. And so that's, that's the other thing is like the board saying, what's our AI strategy? Someone's running off and paying McKinsey a lot of money to come back with a deck and they're feeling, you know, they're sleeping better at night.

12:17But the truth is, I don't think that's what gets the job done. Support for this podcast comes from Pebble. I know that many of you listening are hiring internationally and you'll be all too familiar with the wall of paperwork, rules and approvals, and you know just how much this red tape can slow things down. That's what Pebble is designed to fix. Pebble makes global hiring simple through embedded compliance and AI-driven workflows. The Pebble platform takes the delays and guesswork out of going global, so you can move fast without adding risk. The bottom line is that anywhere is possible with Pebble.

12:56With global hiring simplified, founders and HR leaders can spend their time on focusing on what and where comes next for their business. Pebble has a special offer for recruiting future listeners. Pebble is normally$399 a month per employee, although a no-brainer for what you get. But right now, there is a limited time offer on their site that makes it even easier to get started. Go to HiPebble.ai before it's gone. That's H-I-P-E-B-L dot A-I. Terms and conditions apply. Yeah, I mean, it very much comes back to the people thing that you were sort of talking about earlier. Yeah, definitely. And on that people point, as AI sort of takes over more work, gets more embedded in companies, what's your sort of view on where human judgment sits in all of this?

13:52Where is it essential? Do we need to think about it differently? What's your take on that? Yeah, I think, you know, we need to start with human in the loop. So especially, you know, you think about like customer communications, everyone's had a bad chat bot experience. So you need to decide as you survey the organization, where are the pieces where you need a human touch? You need someone who can kind of mediate that relationship with a customer. Is the margin for error very low where you need to have, you know, yes, the AI can do a lot of the heavy lifting, but every message, every chat, every email is going to run by a human being.

14:28Every business needs to decide this on their own, depending on which are the kind of high risk and the low risk touch points. But over time, I think naturally humans and organizations get more and more comfortable handing more and more off to the AI, right? And I built tools to do customer service communications. And again, like initially it was the human that was mediating and moderating, but eventually they more often than not just promoted what the chat bot had suggested. Did the same in title insurance where human beings were still taking the inputs from the AI. but over time there's a trust that's built and inevitably humans get more and more comfortable trust in the AI or frankly they also tend to get a little lazy there's also research that shows once we feel the AI's got it our brain kind of shuts that skill off and so no one knows how to read a map anymore and you know and because GPS exists but I tell everyone start with human in the loop at every touch point is with a human being but what is the engine starting to surface that information is AI.

15:30Makes a lot of sense. And I suppose it's encompassing a lot of the things that you've already spoken about. What practical advice would you give to, you know, talent leaders in terms of, in terms of what they should be doing right now? Because there's always a lot of talk about the future, but we'll talk about the future in a second, but what should people be doing right now? Yeah, I do want to call this out. This is a really exciting and unique time for HR professionals and for talent leaders. I've been in those trenches of HR technology. And I think, frankly, a lot of companies see it as a cost center.

16:03And I think those folks, the CHROs, don't feel as empowered as the chief revenue officer or the chief technology officer. This is like, not only is AI transformational, but the biggest challenge is transforming the human capital, retraining and reskilling folks. So I don't want to give folks the kind of rah-rah, you know, cheerleading energy. But the truth is like, this is your time. If you're a talent leader listening to this, you frankly matter more than, it's not a race, but at the end of the day, this is your opportunity to really lead and to form a partnership with either technology or IT, because this is the most pressing issue I think every organization is facing.

16:43Every board is saying, what's our AI strategy? And the answer is not a deck. It's how to empower human beings to use the tools properly, to explore, to experiment. that to me is the kind of number one message is don't see it as a threat and don't think of it as like, hey, you know, this is gonna take my job or people are afraid of it, but see this as, you know what? This is the number one challenge facing organizations and we can really embrace it. And I've seen chief, you know, CHROs, but especially bigger companies that have a chief learning officer, right? Someone whose sole job is L &D. And they, you know, one I can think of in particular where he came up with his own AI training curriculum.

17:24He consulted with me. They brought me in to do workshops and boot camps, but he's coming with all sorts of prompt engineering frameworks. He's kind of re-energized. And before his job was, to be frank, he was like, okay, I have to make sure everyone takes the sexual harassment training video within two months of joining the job. Otherwise they're gonna, like that was, I'm kind of being, I'm kind of joking, but like that's not very fun or exciting. But now he's like, no, no, no, oh, I am going to be a contributor to this company's top line revenue. And the way I'm going to do that is by enabling people to lean into AI.

17:58So, you know, I get really excited about this stuff because it's so impactful. Like those HR folks, I think, are getting this huge opportunity. And some are really grabbing it by the horns and some are letting it go. And I think everyone should be leaning in. As we said, this is more about people than it is about technology. So it's absolutely in the talent lane. Impossible question to finish with. So we're talking about technology that's growing exponentially and adoption that isn't. How does this play out? What might things look like in two or three years time? Yeah, I mean, I think that you're going to end up, unfortunately, with a world where there's an even bigger gap between the haves and the have nots.

18:38So I think there's a lot of fear. My job's going to disappear. Yes, some jobs are going to be automated. The good news is what history has shown us and what we're seeing is that more jobs are being created. However, they're different. They require a different skill set and you need to be AI first and you need to take the initiative to learn these skills. People, and I know this from hiring and recruiting, like it's really hard to change behaviors, right? And hiring managers that have done one thing, the one way for 10, 20 years, it's very hard to tell them, hey, you need to use this color code.

19:10We made it as simple as possible. Use this color coded hiring score, green, yellow, red. Use that to inform your decisions. You're going to make better decisions. I can't tell you how frustrated I was trying to convince people to just change a behavior, you know, instead of brushing their teeth left-handed, do it right-handed. So that's my big concern is I think there's huge opportunities here. I think companies and people that realize that and dive headfirst are going to absolutely crush and, you know, leave the rest behind. But I think most employees, I think a lot of people are going to struggle.

19:40And frankly, I think there'll be some age relevance. I think older folks tend to struggle a little bit more. I do these workshops all the time. Digital natives tend to really take to the tools. Folks that are late career struggle a little bit. But yeah, I think there will be big opportunity. And the question will be who leans in and who learns these skills. We're going to see a lot of change and upheaval in the interim, right? And frankly, I think that the threat of losing your job will inevitably be a big enough motivator that everyone will say, hey, I can't sit this one out. You know, we've seen this also.

20:13One last thing I'll say is we've seen these digital disruptions before the Internet 30 years ago. And a lot of people dismissed it in their articles that said, oh, this is just a fad. It's going away. Dot com bubble burst. No one now doubts the power of the Internet. It's changed everything. Social media 20 years ago. It emerged. People were like, all right, this is silly. We're just sharing photos with our friends. This is not a thing. So the good news is we've seen these two before and we now know this is here and it's here to stay. And just on the age point, in the same way that, you know, this is a big opportunity for HR, from a people perspective, do you think that actually this is a big opportunity for older, more experienced people because of their skills, their knowledge, their understanding about how things work?

20:56And that helps when you're applying AI to these problems or kind of reinventing things? Yeah. I think if you have both the subject matter expertise of years of years of experience and the willingness to lean in and learn your job, learn how to do it a different way, I think you become just an absolute force to be reckoned with. I have conversations, but I'll tell you, I present this content all over the globe. And not only I've run into a lot of very, very smart senior partners at firms you've heard of, and they've struggled. And some of them will take me aside and say, listen, I got five years till I'm going to retire.

21:34I'm just going to chill and ride this one out. And then at the point where this becomes required, then I'm just going to, I'm going to retire and fade into the sunset. That is a strategy. I shouldn't knock it. Those folks have, you know, can do it. But I imagine if those folks who are at that point in their career were like, you know what? This gives me a chance to do something. I can combine years of experience and I can combine my wisdom with technical skills and I can lead by example. for me, that's so much more exciting. Like you are just an absolute powerhouse. And so, yeah, I encourage everyone like lean in.

22:06And frankly, I think it's fun. It's like rigging up something new that didn't exist before. You vibe code your way into some application or tool. I can give you dozens of examples and then it exists and it's running and you converse with it and you fix it and you tweak it. I love building. So I think it's a really fun skill set. Michael, thank you very much for talking to me. Thanks so much. This was a lot of fun. My thanks to Michael. And if you think this conversation would be valuable for anyone in your network, please share the episode with them. A quick reminder that you can follow the show on Apple Podcasts and Spotify.

22:36And if you enjoyed this episode, I'd be extremely grateful if you could take a moment to leave a rating or a review on those platforms. It really helps other people in teleacquisition find the show. You can search all the past episodes by topic at RecruitingFuture.com. On that site, you can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that's coming up on the show. Thanks very much for listening. I'll be back next time, and I hope you'll join me.