Elevating our AIQ with Special Guest Bob Pulver

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[00:00:25] Welcome everyone to a very special episode of the HR & Payroll 2.0 Podcast. I'm Pete Tiliakis and as always I'm joined by the legendary Julie Fernandez. Welcome Julie.

[00:00:33] Thanks Pete. Super happy to be here and excited to create a second podcast here from the Workday Bus.

[00:00:39] Yeah, here on the Forever Forward Workday Bus live from the HR Technology Conference. Not only at the conference, we are on the floor in the bus, you know, in the expo. It's amazing.

[00:00:49] And I'm really excited to have one of our fellow podcasters, AI thought leader and transformation expert, digital transformation expert, Bob Pulver. So welcome Bob.

[00:00:58] Thank you guys so much for having me.

[00:01:00] Yeah, excited to have you man.

[00:01:01] I feel like I'm meeting cousins for the first time.

[00:01:02] Yeah, right. Yeah, right. We, we, I've been on your show, Elevate Your AIQ. If you haven't checked it out,

[00:01:09] absolutely check it out. Bob's doing some great work on the topic of AI, which we know is super buzzy and super exciting and a little bit scary and all, all the things wrapped into one. So excited to have you here, man. I want to talk about the show. I want to talk AI.

[00:01:22] Yeah.

[00:01:23] Yeah.

[00:01:23] Recent news, all that stuff. So welcome.

[00:01:25] Awesome.

[00:01:26] Julie, you do the honors.

[00:01:27] Yeah.

[00:01:27] Yeah.

[00:01:28] So Bob, we always ask folks how they got into HR or payroll, wherever your space is and why on earth you stay.

[00:01:36] Great questions. How did I get into it? I sort of tripped and fell into it. Honestly, my background is in large enterprise transformation. So 22 years at IBM, about 12 roles and 12 cities.

[00:01:53] It's as big as you get, isn't it? Big blue.

[00:01:55] Well, the great thing about a big company is there's always a lot of opportunity for internal mobility, exposure to different parts of the business.

[00:02:03] A mentor once said to me, if you want to succeed, you really need to know the business, not just preside over it.

[00:02:10] And so I think my, I guess what I would describe as a lattice more than a ladder kind of career as I traversed IBM and then NBC Universal, helping with their transformation to the cloud, embracing automation, starting to dabble in some machine learning and predictive AI, the last generation of AI that people forget about sometimes.

[00:02:35] But it was at NBC where I started working on workforce strategy. So how are we going to control our own destiny? How are we going to attract engineering talent? How are we going to pay them competitively? Because there was a lot of competition for top talent across media and technology sectors.

[00:02:54] And so I had any background in HR whatsoever, although I was always interested in the people side of the equation.

[00:03:03] I spent a lot of time at IBM doing work around collective intelligence and crowdsourcing before there was a gig economy.

[00:03:10] So how do you find the right people? How do you find the right sponsors for ideas? How do you build teams that can rapidly be sort of assembled?

[00:03:19] And how do you understand their skills and competencies, not just to fill a particular role, but as a team member on a new team?

[00:03:27] How do you understand the dynamics of that?

[00:03:29] So I spent a lot of time in social analytics, trying to understand sort of Monday morning quarterbacking people's behavior a little bit.

[00:03:35] But it was the struggles that I saw at NBC where we were trying to hire talent, but we weren't able to hire full-time talent for accounting reasons.

[00:03:45] But you could hire as many contractors as you want, and then you could convert them when hiring freed up.

[00:03:50] And so I just saw significant inefficiencies and opportunity to understand where talent may exist, and it might be right under your nose.

[00:04:02] So internal mobility, how are we facilitating that? How are we understanding transferable skills?

[00:04:08] And who are the people that are willing to actually reskill where you've got automation opportunities and people's jobs become jeopardized?

[00:04:18] And so I tried to get teams to think a few steps ahead of what the impact would be, and it came up more acutely when I was trying to develop an automation strategy.

[00:04:32] And so as you're developing that strategic plan, it was like, well, if we invest in some solutions on the technology side, we can automate all kinds of things and save 50 headcount.

[00:04:45] I said, well, please don't tell me you plan on getting rid of 50 people because you've got a lot of – NBCUniversal is a big popular brand.

[00:04:56] So that has a lot of meaning.

[00:04:58] It's driven a lot of loyalty to the brand.

[00:05:00] And so there are people that want to stay if only there were opportunities for growth.

[00:05:05] And so if you think about not just NBC but Comcast proper and their entire family of companies, if you could start cross-pollinating talent, you could extend these shrinking tenures.

[00:05:17] You could see – people could see that you're actually investing in them and potentially transitioning them out of a role that – it's half-life is shrinking.

[00:05:29] But have you thought about this?

[00:05:31] Have you thought about that?

[00:05:32] And so how do you target specific people who might have the propensity and the willingness to shift gears and go into a more technical role, not just as a developer, but as a product leader, maybe doing data science, other more technical disciplines, right?

[00:05:48] And so when I got – when I got like, oh, during COVID, I was like, you've got to be kidding me.

[00:05:54] Like, I'm the – yes, absolutely, I understand business decisions need to be made.

[00:05:58] And yes, I understand that I'm the least technical on this technical team.

[00:06:03] However, I'm also the only one trying to move you to where the puck is going.

[00:06:09] Yep.

[00:06:09] And you need to start thinking about these things because you didn't even give me the opportunity.

[00:06:15] IBM always did this.

[00:06:16] If they did some kind of reorg or whatever, they would at least give you time to look around, leverage your network, understand where you might be shrinking in one area but growing in another.

[00:06:26] Do you have the transferable skills to make that shift?

[00:06:31] And, you know, I made a lot of those – I did a lot of that navigation around IBM on my own accord.

[00:06:38] But part of that was because they had some of the tools that enabled that really big company to feel a lot smaller because you could just – you could see it in the knowledge grab.

[00:06:50] Right.

[00:06:50] You could see it in the social network visualization.

[00:06:52] You could see that I'm only two degrees away from, you know, all these senior people.

[00:06:58] And, like, so it facilitated a lot of conversation and it wasn't just pure serendipity for me to find another opportunity.

[00:07:06] Anyway, long-winded answer to I was like these – I'm leaving and I'm going to go off on my own and I'm going to learn as much as I can about talent acquisition, about how some of these decisions are made.

[00:07:18] And I'm going to understand how technology can be properly applied to make sure that we stop wasting all this potential that may exist within your four walls.

[00:07:28] And making sure that we find people who were otherwise overlooked by some algorithm that just isn't being –

[00:07:37] Right.

[00:07:37] It's just not –

[00:07:38] It's not working.

[00:07:39] Yeah.

[00:07:40] It's just not working.

[00:07:41] It's just not working.

[00:07:48] Yeah, absolutely.

[00:07:49] So what's kept you around, man?

[00:07:50] What's kept you in this space?

[00:07:51] Yeah.

[00:07:51] I mean, the responsible AI thing is one of my big focus areas because I feel like AI is becoming ubiquitous.

[00:08:00] I mean, we see it all over the expo hall here and we've seen it for a while.

[00:08:03] But we don't have standardization about what it means to be responsible, what it means to have ethical practices and governance and checks for fairness and how are you being responsible by design, either as a solution provider or nowadays everyone's a builder, right?

[00:08:23] Yeah, it could be.

[00:08:24] Yeah, absolutely.

[00:08:25] So what have you done to make sure that the data that you've collected, the algorithms that you're training, that you're not sort of disadvantaging a subset of the population?

[00:08:37] Right, yeah.

[00:08:38] And so I think that's an important component for everyone's sort of upskilling journey when it comes to AI.

[00:08:45] And I also think that a lot of the programs that we hold dear or some that are controversial for unknown reasons, like DEI, I mean, how, if you're not being fair with the way that you're using AI, how on earth do you expect to achieve the original intent of DEI?

[00:09:07] Whatever you think about the program at a particular company or whether they're dissolving certain groups or whatever.

[00:09:14] The fundamentals were sound.

[00:09:17] It was almost like a branding issue around that.

[00:09:20] But the point is, some of these topics that we all hold dear around diversity, inclusion, equity, belonging, if the AI is allowed to continue to learn these from biased data.

[00:09:36] Bad habits, yeah.

[00:09:37] Then we're all in quite a bit of trouble.

[00:09:41] Yeah.

[00:09:41] We're doomed to repeat the past.

[00:09:42] Yeah.

[00:09:43] In a lot of ways, right?

[00:09:43] Continue to replicate it.

[00:09:45] So that's a big focus of mine.

[00:09:47] The other is just transformation, all that transformation experience that I have.

[00:09:50] It's like, look, most organizations were not good at any kind of significant transformation.

[00:09:57] It doesn't have to be necessarily an enterprise level transformation.

[00:10:00] Maybe it was within a particular domain or within a particular division, line of business, what have you.

[00:10:07] I was talking to Charlene Lee about this because she's like the poster woman for transformation.

[00:10:13] But I was like, what is different about this?

[00:10:16] And one of the things that she pointed out, which I thought was really interesting, is a lot of those other transformations, they weren't just smaller in scope.

[00:10:23] Like we're going to transform all our processes.

[00:10:25] We're going to transform workforce, whatever.

[00:10:29] It was also a lot of it was like grassroots.

[00:10:31] Like find your deputized people.

[00:10:34] You've got change agents.

[00:10:35] You've got champions.

[00:10:36] And we're going to do this bottom up thing.

[00:10:38] And that's going to help drive some of that transformation.

[00:10:41] But this time, it's bigger and broader such that you really do need upskill.

[00:10:47] She described the top two layers.

[00:10:49] I just think everyone, no matter what your role, seniority, everyone should be upskilling.

[00:10:54] Totally.

[00:10:55] 100%.

[00:10:56] The analogy that we used was one from IBM where they really embraced design thinking.

[00:11:01] Yep.

[00:11:02] And I said it wasn't just that if you worked in the IBM design, you had to take that.

[00:11:08] You could have, if you were in that group, hopefully you could teach that.

[00:11:10] But it was all the product managers and product leaders, product owners, and all of the senior

[00:11:18] leaders across the organization.

[00:11:19] Because these are principles that apply across domain.

[00:11:23] And it changes your mindset of how you approach some of these problems.

[00:11:29] And so I think, as she talked about yesterday, if you don't understand what it's going to

[00:11:36] take to grow and move forward and lead, you can't do that unless you get your hands dirty and

[00:11:43] you understand what's possible.

[00:11:44] Yeah.

[00:11:45] Because then you also appreciate when people bring you ideas, you'll see that they're not

[00:11:50] that far-fetched.

[00:11:50] And you'll see that that's solving a real problem because some leaders are just not tuned in

[00:11:57] to some of the frontline things because they're more big picture folks.

[00:12:02] But you've got to balance the design thinking with the systems thinking.

[00:12:06] You've got to balance real world challenges.

[00:12:10] And then, of course, navigate this maze of AI solutions.

[00:12:15] But the transformation piece is huge.

[00:12:17] And in general, it keeps me here.

[00:12:20] I don't want people to fall behind.

[00:12:23] Agreed.

[00:12:23] Yeah.

[00:12:23] I worry about that.

[00:12:24] If everyone's getting a computer, you can't just say, no, I'm good.

[00:12:28] Yeah.

[00:12:28] You know, I'm good with my pencil.

[00:12:30] Right.

[00:12:31] Right.

[00:12:31] And typewriter.

[00:12:32] Yeah.

[00:12:32] I'll pass on the internet.

[00:12:34] You know what I mean?

[00:12:34] No, thanks.

[00:12:35] You know, I don't need Google.

[00:12:37] I've got Joe's super smart.

[00:12:38] Yeah.

[00:12:38] He sits like two doors down.

[00:12:40] Right.

[00:12:40] Right.

[00:12:40] Forget podcast.

[00:12:41] Yeah.

[00:12:41] Who needs it?

[00:12:42] Yeah.

[00:12:43] So look, as you look, I mean, I know you're on the pulse of what's coming and going.

[00:12:48] I mean, as you're walking around here, what's getting you excited?

[00:12:50] What kind of worries you?

[00:12:51] Have you seen anything?

[00:12:52] I always love kind of going through the startup pavilion and see who's going to be here next

[00:12:56] year.

[00:12:57] Who's going to be the next big thing.

[00:12:59] But what have you seen?

[00:13:00] What are you hearing?

[00:13:00] Yeah.

[00:13:01] Just particularly on the AI front.

[00:13:04] You know what you should know?

[00:13:06] You should know the You Should Know podcast.

[00:13:09] That's what you should know.

[00:13:11] Because then you'd be in the know on all things that are timely and topical.

[00:13:15] Subscribe to the You Should Know podcast.

[00:13:18] Thanks.

[00:13:19] Yeah.

[00:13:19] I mean, you can't, as my old boss has just said, you can't swing a dead cat without hitting

[00:13:24] somebody selling AI.

[00:13:25] But I think there's definitely some uniformity in some of the messages.

[00:13:34] So I think it takes more to stand out, which is, again, goes back to the responsibility of the AI piece.

[00:13:41] I think that will become a differentiator in short order.

[00:13:44] I think buyers are going to become more educated and are going to start asking tougher questions.

[00:13:50] I mean, I was just talking to our friend Jerry Crispin about that this morning.

[00:13:54] Where are the standards around this?

[00:13:56] How do I know that you've complied and are being responsible in the way that everyone else views as the right ways to be responsible?

[00:14:06] Are you thinking about this end to end from applicant to alumni?

[00:14:12] Are you thinking about the full talent lifecycle and how this is applied to make sure there's no adverse impact?

[00:14:18] Because I think some subcategories of talent technologies, they think they're removed from it because they're not actually part of the decision-making process.

[00:14:30] Or, oh, we're top of funnel.

[00:14:34] Like, these people aren't even, they haven't even applied to anything.

[00:14:38] So how is their adverse impact?

[00:14:40] Well, maybe you're not casting as wide a net as you should.

[00:14:45] Maybe you're not hitting on the people who have already been disadvantaged.

[00:14:48] Maybe you're not thinking about neurodivergent candidates.

[00:14:53] There's all kinds of, I mean, not to mention.

[00:14:56] Non-linear career paths is another one.

[00:14:58] You know, I mean, we've been, it's a generational thing.

[00:15:00] There's been generations thinking about linear career paths.

[00:15:04] And now it's like, no, no, these skills are portable.

[00:15:06] Right.

[00:15:06] Right.

[00:15:07] Widely portable if you have an open mind.

[00:15:10] Well, the other thing about that is thinking much more about, like, soft skills.

[00:15:15] And I say that knowing that I need to stop saying it.

[00:15:19] Yeah.

[00:15:20] Because there's nothing soft.

[00:15:21] It meant something specific.

[00:15:22] Right, yeah.

[00:15:23] Emotional intelligence is what I kind of like to clump it in as well.

[00:15:26] Yeah, EQ.

[00:15:26] And creativity, critical thinking, systems thinking.

[00:15:30] I mean, some of these things are just not easily replicable in any algorithm, right?

[00:15:36] Yeah.

[00:15:36] So in a sense, those are the more durable skills.

[00:15:40] And they are always part of your transferable, you know, skill set.

[00:15:44] And so, you know, how do you think about that?

[00:15:47] Yeah.

[00:15:48] So there's still a lot of work to do.

[00:15:50] Yeah.

[00:15:50] I mean, there's a lot of opportunity.

[00:15:51] But I just think there's too many people that are on the sidelines, either sort of underemployed or unemployed, completely unnecessarily just due to sort of inefficiencies in the ecosystem.

[00:16:06] You know, shortcomings in the way that people have approached applying AI, not sort of reimagining and rethinking how the whole thing could be transformed, but instead thinking in incremental steps so that they don't disrupt sacred cows and the status quo.

[00:16:24] Yeah.

[00:16:25] Yeah.

[00:16:26] You know, there's a new report that came out this week, and I apologize.

[00:16:28] I cannot remember the name of it, but the World Economic Forum put out some points of view on re-skilling.

[00:16:32] And I want to dig into that.

[00:16:33] And, you know, in there, there's some conversations about this sort of bridging, I guess you could call it.

[00:16:39] I can't remember what the words they used about helping employees kind of get from where we are to where we're going to have to be skill-wise.

[00:16:44] And obviously, employers are going to have to do that.

[00:16:47] There's probably education elements of that.

[00:16:48] And it's not just the employers.

[00:16:49] If you think about it, employers don't necessarily make the connection or connect the dots with nonlinear skills.

[00:16:56] But nor do employees or workers.

[00:16:59] Workers themselves, you know, oftentimes limit their, you know, like they know what they've done.

[00:17:03] Yep.

[00:17:03] But they might not actually identify with a skill that is portable to something completely different.

[00:17:09] Yeah.

[00:17:09] Yeah.

[00:17:10] I think that's where all the skills technology is coming into play.

[00:17:12] Because, like, we were talking earlier on the other show that, you know, it's like I remember being in consulting.

[00:17:16] I was an IBMer, right?

[00:17:17] We actually had some interesting cross paths with media and entertainment and IBM, maybe even at the same time.

[00:17:22] But I always thought about that.

[00:17:24] Like, I've done things in my lifetime that's maybe not on my resume, but I could actually be impactful with it still.

[00:17:29] And maybe, you know, you have something and I know that, but maybe the organization doesn't know that.

[00:17:34] And then you see someone leading something, you're like, well, why would they pick that person when this person had such great experience?

[00:17:39] That person had, you know, and it's like, I don't know that they knew to know that those skills were there to even activate that skill.

[00:17:46] So that's where I think the tech is.

[00:17:47] It even goes to the death of the resume, right?

[00:17:49] Exactly.

[00:17:49] I mean, like you could rewrite your resume in so many different personas.

[00:17:52] Mine would be so long if I put everything I had experience at, right?

[00:17:55] Yeah.

[00:17:55] Or, I mean, it's all about the positioning and how you're actually viewing.

[00:17:58] Yeah.

[00:17:59] What lens you're viewing the skills that you have through.

[00:18:02] And it'll be interesting to see if AI can help us figure out how to do that better than we naturally do it ourselves.

[00:18:09] Yeah.

[00:18:09] Whether we're the guy looking for work or we're the guy looking to employ somebody.

[00:18:13] Yeah.

[00:18:13] No, totally.

[00:18:14] I think I could come up with a whole second resume with all the like projects.

[00:18:21] Experiential moments.

[00:18:22] Experiential moments, yeah.

[00:18:23] Yeah.

[00:18:24] Things that I just felt passionate about and I just wanted to get involved in.

[00:18:28] And they may appear, you know, sparsely throughout like just a single bullet.

[00:18:32] We're not at all, right?

[00:18:33] Totally, right?

[00:18:34] But you're drawing on that at some point.

[00:18:36] The other thing, you know, I don't think, I'm not quite sure why LinkedIn has a limit of like 50 skills, but like I have LinkedIn premium.

[00:18:43] So I see if there's a job and it'll say, well, you have, I'll see a job that I'm like, I could totally do.

[00:18:49] It's just like this job I had, you know, at IBM or NBC, whatever.

[00:18:52] And it'll say, well, you only have like three of the 10 skills.

[00:18:56] Like, oh yeah?

[00:18:57] Really?

[00:18:57] Let me show you.

[00:18:59] Yeah, yeah, yeah.

[00:18:59] So now I gotta go, now you're gonna make, I'm in the middle of this and now you're gonna make me go back and update.

[00:19:04] Yeah.

[00:19:04] The skills, well, which one is sort of stale?

[00:19:07] Yeah.

[00:19:08] And everybody should have that or whatever.

[00:19:11] Right, right.

[00:19:11] So it's just like not differentiating.

[00:19:13] So I gotta remove that and then add a new one.

[00:19:15] And, but like, yeah.

[00:19:17] So it's just like this artificial sort of barrier, especially if you, you know, if you use LinkedIn to.

[00:19:23] But you raise a great point.

[00:19:24] Like how is AI, if AI is just assimilating data and extrapolating, right?

[00:19:28] And, you know, even applying intelligence, if it's only drawing on the words or the language that are out there in the, whatever ecosystem it's drawing from.

[00:19:38] We can't possibly expect it to also infer unless it's also, you know, looking at, well, if you did this in a retail environment, you probably just to survive would had to have had, you know, familiarity with distributed, you know, locations or, you know, like something like hires that are jumping from a location to another location five miles away.

[00:20:01] Or, you know, you'd have to infer quite a bit of stuff to get beyond just data.

[00:20:05] Yeah.

[00:20:05] Yeah.

[00:20:06] I think, so what if I didn't use this exact word that matches?

[00:20:10] This is another thing that drives me crazy about the resume, this cat and mouse game with the AI generated JD now with an AI generated resume matched and graded by a third.

[00:20:20] By something.

[00:20:21] Yeah.

[00:20:21] Yeah.

[00:20:22] AI or whatever.

[00:20:22] I mean, this, we're not, this is not a good direction to go in.

[00:20:25] And so the more you can have an interpretation of someone's, what someone's capability is.

[00:20:32] I mean, look, we all have a single LinkedIn profile.

[00:20:35] Why do I need to customize my resume?

[00:20:37] This is a game.

[00:20:39] Yeah.

[00:20:39] You're making me customize my resume.

[00:20:41] Yes.

[00:20:41] It's a lot easier to do now, but now everything is like homogenized.

[00:20:46] Now all these candidates sound the same.

[00:20:48] Whether they have one or 10 years of experience.

[00:20:51] And yet people still aren't taking, realizing that there's got to be a better way.

[00:20:55] And so I know that's easier said than done.

[00:20:58] I know that there's challenges with, you know, well, we could do this at scale if we use AI, but what we've heard is our candidates don't want to talk to AI.

[00:21:07] They want to talk to a human being.

[00:21:09] Well, do they?

[00:21:10] Yeah.

[00:21:11] They think they do, but maybe they don't.

[00:21:13] Maybe they wouldn't even know the difference.

[00:21:14] Yeah.

[00:21:15] Right.

[00:21:15] Yeah.

[00:21:16] It's so crazy.

[00:21:16] It's so fascinating.

[00:21:17] And sometimes you're thinking like, what level, you know, are you talking to a human being who has had enough breadth of experience to even know how to direct, you know, some of their own questions and evaluations.

[00:21:28] Yeah.

[00:21:29] Yeah.

[00:21:29] About a particular job.

[00:21:31] So, you know, Bob, we've been talking a little bit about like this week with some of the leaders about like, is HR adapting and digesting innovation fast enough?

[00:21:40] But are they reskilling fast enough?

[00:21:42] I don't know.

[00:21:43] I don't think so.

[00:21:44] Right.

[00:21:44] I think there's a lot of folks are still trying to figure out what skills they have in their organizations, which ones they should have and when should they have them, which is, you know, all the great insights and talent intelligence we have now.

[00:21:55] But is everybody getting that to have that power and that ability?

[00:21:59] And I don't think they are.

[00:22:00] No, I don't think they are.

[00:22:01] I do applaud some of the approaches that people are taking, right?

[00:22:05] Like personalized learning, coaching, mentoring.

[00:22:10] I think there's a lot of potential with those.

[00:22:13] And, you know, again, back to my earlier point, even those need to think about responsibility and ethics or whatever, because anything I'm thinking about Europe in particular, where it really.

[00:22:25] It's strict on how you're using personal, personally identifiable information and anything that can impact someone's livelihood.

[00:22:32] Yeah.

[00:22:33] Not just whether they're employed or not, but their future prospects.

[00:22:38] If you're using it for performance management, if you're using it to guide and give you insights on, you know, leadership development.

[00:22:48] Yeah.

[00:22:48] You only got a couple of seats to put people in the next round of, you know, leadership development or whatever.

[00:22:53] And so how do you mitigate the human bias?

[00:22:58] Because, you know, every people manager is going to be like, oh, I got the guy.

[00:23:03] Everybody out of my way.

[00:23:04] I got the guy.

[00:23:04] Right.

[00:23:05] It's my spot.

[00:23:06] Going up.

[00:23:06] Like, what do you mean?

[00:23:07] Let's use it.

[00:23:08] Let's take a data driven approach.

[00:23:18] Yeah.

[00:23:19] Yeah.

[00:23:19] But, I mean, I've seen that countless times.

[00:23:22] I mean, to be honest, I mean, maybe I've been the beneficiary of that too, because I've had strong relationships or whatever.

[00:23:29] But that was a while ago.

[00:23:31] And we've wised up since then.

[00:23:33] And we've acknowledged that there are human biases at play.

[00:23:37] And we just don't want to continue to.

[00:23:40] Yeah.

[00:23:41] Same mistakes over again.

[00:23:42] Right.

[00:23:42] Yeah.

[00:23:42] Continuously repeating our mistakes.

[00:23:44] I kind of wonder if maybe some of the innovation in this area or just rethinking how we might connect those dots and use automation might come from the next generation, right?

[00:23:55] Generation Z.

[00:23:56] We see already a DNA, you know, like when you described how you got into this, it was very much, you know, reskilling was a thing that was imposed upon you, right?

[00:24:05] And people went kicking and screaming.

[00:24:07] And it's like, I don't want to sign up for that, you know?

[00:24:09] But the tides have turned and it's like a whole new generation has been born with the mindset that you might have wanted them to have 30 years ago, right?

[00:24:17] Or 20 years ago.

[00:24:18] And so now that we have this generation that feels like they can just pop all over the place and, you know, like they want that variety.

[00:24:25] Maybe there's something about the way that they view jobs that we should tap into and really try to figure out when we're thinking about skills, upskilling and incorporating.

[00:24:36] I think they're used to agility.

[00:24:38] I think they're used to failing fast.

[00:24:40] Like, oh, this sucks.

[00:24:40] Let me do something.

[00:24:41] Let me use something else.

[00:24:42] Or, you know, and they're happy with that.

[00:24:44] And that's an expectation.

[00:24:45] And I also think that they're largely used to, they're eager to learn and where, you know, some of us, right, we get a little complacent in the way we are.

[00:24:53] I'm used to doing, you know, my wife, we're still fighting over sometimes, like I cannot get her on a digital shopping list.

[00:24:59] She loves the paper.

[00:25:00] I'm like, come on, you know, but like.

[00:25:02] Don't get me started.

[00:25:03] I know, I know.

[00:25:04] I'm like, we need the one where you can cloud it and the whole family can go in there.

[00:25:07] My wife just cannot take that, right?

[00:25:08] So, look, that's okay.

[00:25:09] That's a preference.

[00:25:11] Not to say that it's entirely generational, but I think that when I talk to my.

[00:25:14] There's a DNA.

[00:25:15] Yeah, I've got a millennial.

[00:25:17] I've got, you know, I've got a couple of gen, I guess a gen Z.

[00:25:20] A gen Z.

[00:25:20] Yeah, gen what would be Y.

[00:25:21] Well, I don't know what age that is.

[00:25:23] But anyway, I've got a mix.

[00:25:24] Yeah.

[00:25:24] And it's interesting to see how they each like kind of look at work and they look at tech and they and what their expectations are of like, like I've said this before.

[00:25:32] I don't think my 20 year old, 21 year old now.

[00:25:34] I don't think he would even acknowledge your organization is on the planet if you didn't have a mobile app.

[00:25:39] Like it just doesn't even register to him in the same way you and I wouldn't.

[00:25:43] We would be skeptical of a firm with no website.

[00:25:45] You know what I mean?

[00:25:46] Like to them.

[00:25:46] Well, and the same thing with the importance of getting of working your way into a full time employment.

[00:25:52] Right.

[00:25:52] I mean, like that's not everybody's dream these days.

[00:25:55] Yeah.

[00:25:55] And if you can make it doing gig stuff or having that freedom or working and then stopping and then, OK, now I'm out of money.

[00:26:02] I'll go do something else.

[00:26:02] But all those skills.

[00:26:03] That's cool.

[00:26:04] Right.

[00:26:04] Could could at some point be brought together to be like, hey, I am qualified for this role in this in this more traditional organization where, you know, it is a career path.

[00:26:12] And I've got all these experiential learnings that I think, you know, I always talk about like the military.

[00:26:18] I've learned more in four years in the military than I mean, I can't even.

[00:26:21] You do talk about it a lot.

[00:26:22] We beat something into you, Pete.

[00:26:23] I mean, they just you're trained at such a scale and such a standard that I think you draw on those skills later than you don't realize.

[00:26:31] Like, I actually have a skill there.

[00:26:32] I have, you know, and I think that's an awakening that we're all kind of coming around and that employers have to come around to that.

[00:26:37] Like, you've got to find these.

[00:26:39] They're in your organization.

[00:26:40] You just got to draw it out and know about it and activate those people in a way that can give them the chance to be successful.

[00:26:46] I'll tell you, for as long as I've been doing consulting, which has been most of my career, it really didn't dawn on me until a good decade in that I was having so many experiences, so many so quickly with different paths and different journeys to try to achieve similar objectives that there was a value in that.

[00:27:04] Yeah.

[00:27:05] And I, you know, you had to get past, you know, that stage where you feel like you don't really know what you're talking about or everything feels new or is a different pattern and you don't recognize it.

[00:27:13] And then all of a sudden it's like, wait a minute.

[00:27:15] Like, I see this, you know, a hundred more times a year than a practitioner who is doing it once in their organization, fighting all of those battles with red tape.

[00:27:25] Right.

[00:27:25] Right.

[00:27:25] And the administration, whatever they have to fight to make something happen, like who wouldn't want to be me?

[00:27:31] Yeah.

[00:27:31] I know.

[00:27:31] I can walk away from those things and say, okay, good luck.

[00:27:34] Yeah.

[00:27:34] Yeah.

[00:27:35] I think the skills thing is really, really interesting because, you know, you have organizations like World Economic Forum that have been talking about, well, these are the future sort of projected skills.

[00:27:45] And we see just going from those durable, you know, power human skills to the technical skills.

[00:27:52] I mean, if you look at the expected in-demand skills, you know, five years out, say, you know, 20, whatever, 20, 29, 20, 30, most of them are those human skills.

[00:28:04] They're not saying like, you know, you got enough job.

[00:28:06] All the things you listed earlier, the adaptability, creativity, you know, critical thinking.

[00:28:11] Right.

[00:28:12] So part of it is, again, I'm not saying, and this is easy, why aren't people doing better?

[00:28:18] Yeah.

[00:28:19] You've got to understand the new half-life of some of these skills.

[00:28:22] You've got to incorporate that as you're doing your skills sort of gap analysis and where you guys need to be to execute on your business strategy, your technology strategy, and align your talent strategy to that.

[00:28:37] But you've also got to incorporate the speed at which AI is taking on new capabilities.

[00:28:43] Yeah.

[00:28:44] So whether that's getting better at math or some of the new reasoning capabilities in the latest ChatGPT 01 release, it's going to get better and better.

[00:28:59] We're not going backwards.

[00:29:01] Right.

[00:29:01] And so you've got to look at that skills trajectory and that half-life while also incorporating the potential trajectory of AI, which is, you know, just breakneck speed right now.

[00:29:12] Yeah.

[00:29:12] And so it's hard for organizations to keep up.

[00:29:15] I think the other thing to consider is today what are jobs tomorrow are maybe more sort of granular than that because especially even just automation.

[00:29:29] Right.

[00:29:29] It takes tasks off people's plates and at what point do you get to, you know, the double-digit percentage of things that you've taken off of that current role as its defined, you know, plate.

[00:29:40] And either get rid of that role or shrink the team or whatever and then figure out what else they're going to move on to do.

[00:29:47] Hopefully, you know, higher value things.

[00:29:49] But you've really got to understand a lot of factors that play into each other to do this right.

[00:29:57] But it's very possible that as, you know, you were talking about younger generation, you know, Gen Z and what's the new one?

[00:30:05] Gen Alpha?

[00:30:06] Why, right?

[00:30:06] No.

[00:30:07] Is it not?

[00:30:07] No, it goes back to the Alpha's, right?

[00:30:09] Why is it?

[00:30:09] Yeah, okay.

[00:30:10] So what was it now?

[00:30:11] Starting back at the Alpha's.

[00:30:12] I saw it the other day and I can't remember.

[00:30:13] I think it's –

[00:30:14] Yeah.

[00:30:14] I'm X and then there's millennials.

[00:30:16] Same.

[00:30:16] Yep.

[00:30:17] Which is why.

[00:30:18] And then Gen Z.

[00:30:18] And now there's Alphas.

[00:30:19] And now there's Alphas.

[00:30:20] I think that's what – yeah.

[00:30:21] So I think now there's Alpha.

[00:30:22] Oh my God, we're old.

[00:30:25] We're too far removed now.

[00:30:26] We're too far removed.

[00:30:27] No, no, no.

[00:30:28] We're seasoned.

[00:30:30] I think a lot of the jobs –

[00:30:31] Some of the jobs that exist today will not be career options.

[00:30:35] Do you remember when we – not to date ourselves, but we are Gen Xers, we've said.

[00:30:38] But do you remember when the internet was kind of peaking, like really starting to come about, like say early 90s, I guess it would have been.

[00:30:44] Maybe even – well, yeah, it would have been early 90s.

[00:30:46] And they were talking really in the media a lot about like fewer but better jobs.

[00:30:50] I feel like it's the same sort of thing, right?

[00:30:52] We're going to have different jobs, right?

[00:30:53] We're going to have a different transition of, okay, this won't exist anymore, but now this will.

[00:30:57] Right.

[00:30:57] To replace that.

[00:30:58] So, yeah, I think it's kind of like that.

[00:31:00] But I'm also bullish on the gig economy and people inside large organizations also rethinking how they sort of orchestrate across these different talent pools to access good talent wherever it exists to execute on a subset of what is today a full-time role or full-time equivalent role.

[00:31:20] And to say, now that we have the efficiencies, we've got the backbone, we've got the infrastructure to do this.

[00:31:26] And responsible AI is important to sort of do that properly.

[00:31:30] But as you have these tools getting more integrated where you could tap – maybe you've got a workforce optimization module that says, okay, based on the half-life of these skills, based on our project outlook and some of the things that we're going to invest in, we're going to go and the optimal solution is get two guys off of this freelance platform, get one contractor.

[00:31:55] Yeah.

[00:31:56] Contracted, you know, project manager, get whatever.

[00:31:58] And it could basically help you like build sort of a recipe.

[00:32:02] Yeah.

[00:32:02] Right.

[00:32:03] I was going to say almost like a –

[00:32:04] Yeah.

[00:32:04] Give me two cups of that guy.

[00:32:05] Yeah.

[00:32:06] Yeah.

[00:32:06] Yeah.

[00:32:06] A pinch of this and a pinch of that in the moment too.

[00:32:08] Exactly.

[00:32:09] Like that I think is going to be really key is being able to use that tech and use AI to identify, is it best for me to get a freelancer here?

[00:32:16] Is it better for me to have – promote someone?

[00:32:18] Is it better for me to go and get a full-time resource?

[00:32:21] And what is the right resource for each of those?

[00:32:23] So, yeah, I love that part of it because I think that's the guesswork that leaders have to be able to remove in order to make decisions on the fly, in the flow, and have actionable outcomes.

[00:32:32] I think a lot of this goes back to something that you mentioned earlier as well.

[00:32:36] So, while all of that's happening, the leaders who've worked their way up to the, hey, maybe I can just watch stuff happen.

[00:32:42] Do I really need to be in the weeds?

[00:32:43] There's also a culture that goes with that that says, you know, my husband's a tradesman.

[00:32:48] And he just fundamentally thinks, you know, engineers, if you haven't cut your bones going through the steps to actually have made something and made sure that, you know, you can access a screw.

[00:32:59] You know, you can just design it in CAD or do something.

[00:33:01] We have a bias built into the older generations who tend to be more the leaders right now that says there are certain paths and steps you have to take to be able to do job X.

[00:33:12] And the fact of the matter is, at some point in time, AI is quite likely to help an engineer who didn't cut their bones in the trades recognize that they put the screw in a stupid place.

[00:33:24] And you could never get to the screw without removing and discombobulating the whole dang thing.

[00:33:29] And so, do you need to have cut your bones by going through all of the motions that take 20 years to gain X amount of experience?

[00:33:37] And if the leaders or the folks that are in, you know, responsible for cultivating talent don't also have a bit of a mind shift and have an openness to the fact that, you know, people can cut their bones in different ways now.

[00:33:51] Then, you know, we're stymied still.

[00:33:54] Also learn in different ways.

[00:33:56] Right.

[00:33:56] So, what we had to go to take a class for and da-da-da, like, I don't know, my daughter would just be like, I got this up.

[00:34:05] Just give me 20 minutes on YouTube or TikTok or whatever and, like, I'll be good.

[00:34:09] Yeah.

[00:34:09] Stop talking so I can pay attention.

[00:34:11] My son's trying to become a chef and he's largely been taught on YouTube.

[00:34:15] And now he's working with a chef who's training him and teaching him not only the, you know, the profession of that skill, but also the business of running a restaurant, right, and a high-performing business.

[00:34:26] And I think it's really interesting because he found that on YouTube and he's leaned into that from his hobby and now he's kind of creating a career out of that.

[00:34:34] That's the creator economy.

[00:34:36] Like, that's so cool.

[00:34:37] That's the speed of skill.

[00:34:38] That's the speed of technology enabling skill that I think is super exciting.

[00:34:43] We've got to figure out how we put that in the hands of every worker, right?

[00:34:46] And I almost feel like to some extent the government has some responsibility to help.

[00:34:50] The education system has to help.

[00:34:51] Not just the employers sort of being burdened by all this.

[00:34:54] We've got to reskill our entire workforce up and down, right?

[00:34:57] Ah, I'm going to stop short of asking the government to do anything.

[00:35:01] Well, there already are, right?

[00:35:02] Israel has done a lot, I believe.

[00:35:03] There's a couple of countries that have done a lot to really lean into reskilling their workforces.

[00:35:07] You know what I think is really interesting about that is, though, so, you know, we have similar age kids.

[00:35:13] And so the same kid that applies that to do something that they're really interested in will come to you and say, I don't know how to fix the light switch.

[00:35:23] And it's like, don't tell me there's not a 10-minute YouTube that will tell you how to fix that dang thing.

[00:35:31] Like, why is this an unpassable problem for you?

[00:35:36] Apply it to life, kid.

[00:35:37] I have this thing with my daughters.

[00:35:38] I don't want them to be dependent on a man, right?

[00:35:41] You know, whatever.

[00:35:42] We can philosophically talk about that.

[00:35:43] So when my daughter, my younger daughter, it will often lean on, you know, dad will fix it, right?

[00:35:48] Oh, dad, I can't get into my computer.

[00:35:50] I make her do it, right?

[00:35:51] And a lot of times I will take her to something like YouTube or whatever, or I'll show her how to do something.

[00:35:56] And so she is self-supportive and she does it herself.

[00:35:58] But I love that, that you can just go pull that training.

[00:36:01] Like, I do it.

[00:36:02] I've got to paint something or fix something in the house.

[00:36:04] I go to YouTube.

[00:36:04] I go to the internet.

[00:36:05] I try to find somebody, some social media person showing how to do that.

[00:36:09] Yeah.

[00:36:09] You know, I love that.

[00:36:11] But we got to get that micro learning out there, right?

[00:36:14] To everybody.

[00:36:15] Yeah.

[00:36:15] And I don't really got the technology to handle all that now.

[00:36:18] Right.

[00:36:18] So.

[00:36:19] If you like swiping, then head over to Substack and search up work defined.

[00:36:24] WRK defined and subscribe to the weekly newsletter.

[00:36:27] You know, I do think that's one of the things about just tying back to elevate your AIQ kind of concept.

[00:36:34] It's like your excuses have gone away.

[00:36:37] Like, yeah, it's just go in, start playing around, seeing how it reacts to you, tweak your responses.

[00:36:44] Yeah.

[00:36:44] There's plenty of people that can give you a structure, like a prompt structure to make sure you're getting optimal output.

[00:36:50] But you've got to just keep playing with it, understanding that and still apply your critical thinking.

[00:36:56] Don't take what it says at face value, even if it's giving you sources.

[00:37:00] And, but just think about it as you're, you know, planning a trip.

[00:37:05] You know, any everyday thing.

[00:37:07] I tell my daughter, you know, it's, it's intended to be like a, optimally it's for a student.

[00:37:14] It's a tutor.

[00:37:14] Yeah.

[00:37:15] Right.

[00:37:15] It's a personalized tutor.

[00:37:17] It's not giving you the answers.

[00:37:18] How are you going to learn if it's giving you the answers?

[00:37:22] It's not the same as a calculator.

[00:37:24] Calculators often approved now.

[00:37:27] Right.

[00:37:27] They literally had to go buy a TI scientific, you know, calculator.

[00:37:32] You're not going to be able to do this.

[00:37:33] It's not like you can do this in your head and this advanced math.

[00:37:36] But this, the subject of learning how to use generative AI, like it is, as you're using it,

[00:37:44] it is also the, the help section and the, the, the community forum.

[00:37:49] And you're teaching it by the way at the same time, which is interesting.

[00:37:52] So, but if you get stuck, just literally, you don't have to leave the screen.

[00:37:57] Yeah.

[00:37:57] I mean, let's ask it, how do I get a better response from you?

[00:38:01] Yeah.

[00:38:01] How do I ask this question better or whatever?

[00:38:04] But there's just no excuse for not going in there.

[00:38:07] There's free tools.

[00:38:09] There's free training.

[00:38:10] Yes.

[00:38:10] Yeah.

[00:38:10] Google has some great learning tools you can do and go out there and learn generative and

[00:38:14] regular, you know, just based on AI.

[00:38:16] Yeah.

[00:38:16] A lot of the, a lot of the big technology players.

[00:38:18] I mean, I know IBM has skills, skills build.

[00:38:20] I think it's called and, you know, Coursera, LinkedIn learning.

[00:38:24] There's a bunch of things that you don't have to spend money to, to do it and you can use

[00:38:28] it every day.

[00:38:29] I mean, there are some limitations to free accounts like anything, but, but yeah, you've

[00:38:33] just got to get in there and, and get started.

[00:38:35] And I have no doubt that the Gen Zs and Gen Alphas of the world are going to be.

[00:38:40] They'll engage it.

[00:38:40] Right.

[00:38:41] I find that, you know, my kids love to have people.

[00:38:43] Recklessly though sometimes.

[00:38:44] Oh yeah.

[00:38:44] Well, yeah.

[00:38:45] That's a whole other episode.

[00:38:47] That's the problem, Julie.

[00:38:47] The problem is to Pete's point before, like the education system is not keeping up.

[00:38:53] It's not.

[00:38:54] You know, my daughter's school is, it's a very good public school system, but like to say,

[00:38:59] do your own work.

[00:39:00] It's not a strategy.

[00:39:02] Yeah.

[00:39:02] Yeah.

[00:39:03] Totally.

[00:39:03] And there, you have to acknowledge that they're using it just like your employees are using

[00:39:06] it, whether you sanction the use of something or not.

[00:39:10] And so knowing that, what are you going to do to mitigate the risk?

[00:39:14] What are you going to do for students so that they know responsible use?

[00:39:19] And before they go create their own custom GPTs to do their history homework and write

[00:39:25] their English papers and whatever, like someone's going to raise a flag if you leave any of

[00:39:33] its natural language in there.

[00:39:37] I was talking to someone before about building a detector for AI content and I'm just like,

[00:39:44] didn't we try that once before?

[00:39:46] I don't know if it's any better.

[00:39:47] It was a lot of false positives, you know, especially for non-native English speakers

[00:39:52] who write proper English.

[00:39:55] I'm like, some of us, including me, who don't always use proper English.

[00:39:59] But that doesn't mean you're a robot.

[00:40:02] Yeah.

[00:40:02] We've already evolved beyond what was, you know, early on in the schools, you were saying,

[00:40:08] you know, the teachers could ingest students' papers and there were ways to spot plagiarism.

[00:40:15] Right.

[00:40:15] At this point in time, we're so far beyond that.

[00:40:17] I mean, it has become impossible, you know, from being on the school board, right?

[00:40:22] That you can no longer anticipate or cure for all of these things because of the pace at which,

[00:40:29] you know, okay, change my content by 10% or more, right?

[00:40:33] I mean, like we have to catch up.

[00:40:35] But I mean, is it really catching up and creating those fail-safes?

[00:40:38] Or is it more educating, you know, folks about the proper use, the right way to use?

[00:40:44] It wouldn't take that much to scare students into realizing that they can't just take an output from one of these tools.

[00:40:54] And maybe it's because some of the main ones have become a little bit homogenized.

[00:41:00] They're sort of, you made this point earlier, Pete, like it's sort of ingesting other AI-generated content because it doesn't have the difference.

[00:41:07] Yeah.

[00:41:08] So, but all a teacher would have to do is say, I'm going to put myself in the seat of a student.

[00:41:16] Here's verbatim.

[00:41:17] Here was the assignment and stick it into a couple of these tools.

[00:41:21] Yep.

[00:41:22] And see how well that matches against the student.

[00:41:26] Because you'll see that percentage that you were just talking about.

[00:41:28] You'll see that there's a, you know, 80% match.

[00:41:31] Now, that might be a good match score if you're a candidate, customizing your resume to your job.

[00:41:36] But if you're a student trying to submit what is supposed to be your own work.

[00:41:41] Right.

[00:41:41] And it's that easy for your teacher to tell, not from their own sort of judgment, but literally sticking it back into the same tool that the student probably used to generate it.

[00:41:53] You're walking into a buzzsaw.

[00:41:55] Yeah, absolutely.

[00:41:56] Absolutely.

[00:41:57] So, look, I could keep going on.

[00:41:58] We say that without your guess, but man, I got so many questions.

[00:42:01] We'll have to do this again.

[00:42:02] And I've been on your show.

[00:42:03] I love it.

[00:42:04] And I've been listening to some of your episodes.

[00:42:06] I'd love for you to share a bit about, you know, elevate your AIQ, what you're doing on the show, and where folks can get in touch with you.

[00:42:13] Yeah, absolutely.

[00:42:13] Thank you.

[00:42:14] So, yeah, the show, I really love doing the show.

[00:42:17] I'm talking to a lot of different people doing different cool things.

[00:42:21] So, people who are writing books on these topics.

[00:42:24] Yeah, you have some great guests.

[00:42:26] Some of them have their own boot camps.

[00:42:29] They're transformation experts.

[00:42:31] I mean, our friend Larry's going to come back on the show.

[00:42:33] Yeah.

[00:42:34] Who was an analyst.

[00:42:36] He was a CHRO, and now he's back.

[00:42:38] Is it all HR?

[00:42:39] Driving transformation.

[00:42:39] Is it all HR based?

[00:42:41] That's definitely a focus, like talent and HR, but I don't want it to be exclusively that.

[00:42:45] I want to talk to other folks who are thinking about how to transform any type of organization, how to think about, you know, previously sort of disadvantaged, you know, groups.

[00:42:57] So, I do want to extend, and I expect to extend to people who are building solutions for some of those hidden talent pools, right?

[00:43:05] So, Pete, we were talking yesterday about people returning to the workforce, whether you're coming out of the military or previously incarcerated people.

[00:43:15] There's been a lot of video hype.

[00:43:17] There's been a lot of video hype on some of what has been done recently with, like, ALS patients who can't speak anymore.

[00:43:23] And, you know, they figured out how to anticipate.

[00:43:26] Yeah.

[00:43:28] I think neurodivergence is a really interesting topic to me, not just because of my own, you know, challenges, but, you know, the people on the autism spectrum.

[00:43:39] And the very significant percentage of that population who are often very bright.

[00:43:47] Oh, yeah.

[00:43:48] Oh, yeah.

[00:43:48] And are falling into what we talked about before, like, either underemployed because they haven't, people haven't acknowledged and appreciated the, given them the accommodations.

[00:43:59] Right.

[00:43:59] That they need.

[00:44:00] And so, I think that has shortchanged a lot of people and maybe even discouraged them from applying to jobs that they could very well do if only they had those accommodations.

[00:44:09] But instead, they've sort of decided that I'm not going to cause a big, you know, ruckus.

[00:44:15] And, you know, this job is fine or, you know, whatever.

[00:44:19] And I just think nobody benefits from that.

[00:44:21] No, you're right.

[00:44:22] Yeah.

[00:44:22] And it looked like you said, there's skills everywhere, right?

[00:44:24] And everybody deserves an opportunity.

[00:44:26] Everybody deserves to be engaged and empowered.

[00:44:29] So, you're absolutely right.

[00:44:30] There's a lot of underserved populations that need that help.

[00:44:32] Yeah.

[00:44:32] And I think just on the responsible AI piece, my goal is to amp that up and really, because I think legislation's coming.

[00:44:39] We've seen what the EU is doing.

[00:44:41] I think that's something that everyone needs to pay attention to if you've got global, you know, aspirations and you're thinking about what's going to impact potential U.S. legislation.

[00:44:51] So, we're not left with this patchwork of municipal and state level policies.

[00:44:57] Localized AI, as I'm calling it now.

[00:44:59] It's like I've been asking vendors, like, how on earth are you going to localize your AI when New York's got one rule and Illinois's got another?

[00:45:06] And it's going to get interesting here.

[00:45:07] And I worry we're going to – our lawmakers tend to react and then throw, you know, we've had podcasts about – episodes about this.

[00:45:14] Just throw sort of, you know, laws at innovation that aren't really purpose-fit for that innovation.

[00:45:20] And so, yeah, I hope we protect it for so many, many reasons.

[00:45:24] Yeah.

[00:45:24] So, I think, like, AI governance, AI ethics, those kinds of things I think are important to pull in.

[00:45:31] I mean, that was part of the impetus of me starting this in the first place and just – but, yeah, I've got a lot of folks, you know, lined up to bring those perspectives.

[00:45:40] I'm supposed to catch up with Commissioner – ex-Commissioner Sondreling today.

[00:45:44] Yeah.

[00:45:44] Yeah, he does a lot of shows with some of our peers.

[00:45:47] Yeah, it'd be awesome to have him on there.

[00:45:49] Yeah, I caught up with him at RecFest.

[00:45:51] Yeah, very cool.

[00:45:52] And so, yeah, I told him I was going to –

[00:45:54] Awesome.

[00:45:55] Hound him to get on the show.

[00:45:57] I love his attitude towards it all.

[00:45:59] He doesn't seem like the average lawmaker.

[00:46:01] He seems very, you know, future forward and obviously very – an ally, I think, for it versus –

[00:46:06] Absolutely.

[00:46:06] Some of the lawmakers are like, ah, we're going to attack it.

[00:46:08] I think he purposely went into that role.

[00:46:12] That's awesome.

[00:46:12] Because it was like a sort of rotational two-year stint.

[00:46:15] Is he here?

[00:46:15] Was he here at the –

[00:46:15] Saw him yesterday.

[00:46:16] Yeah, okay.

[00:46:17] Cool, cool.

[00:46:17] Walking around, but he was engaged in conversations, so I haven't talked to him.

[00:46:21] Maybe we'd get him on our show.

[00:46:22] Who knows?

[00:46:23] Yeah.

[00:46:24] Awesome.

[00:46:24] No, he's been great.

[00:46:25] He's absolutely great.

[00:46:26] He's been an ally and he came into that role taking a different tact deliberately.

[00:46:31] And I think he did a great job.

[00:46:33] Yeah.

[00:46:33] So let's make sure people know how to reach you, where to find you, where to look for the stuff that you're doing.

[00:46:40] Yeah, I mean, LinkedIn's the easiest to find me directly, just Bob Pulver.

[00:46:44] And then ElevateYourAIQ.com will route you to my advisory page where I do some other work beyond the podcast.

[00:46:51] But yeah, that's probably easiest.

[00:46:53] And the podcast Elevate Your AIQ is on Spotify.

[00:46:57] Everywhere.

[00:46:57] Yeah, it's on the Work to Find Network, just like we are.

[00:47:00] So check that out.

[00:47:01] Check out all the shows.

[00:47:02] We're neighbors, family.

[00:47:03] We're cousins.

[00:47:04] We are cousins.

[00:47:05] Yeah, in the beginning you mentioned that.

[00:47:06] So, Bob, listen, it's been excellent having you on.

[00:47:09] Thank you so much for coming on.

[00:47:10] Thank you so much to Workday for the hospitality.

[00:47:13] The Forever Forward Bus is literally – this is amazing.

[00:47:16] This is the most beautiful studio I think we've ever recorded an episode in, and we're just thankful to be here.

[00:47:20] So thanks for coming on, man.

[00:47:21] Awesome.

[00:47:21] Thanks so much for having me.

[00:47:22] Enjoy the rest of the week.

[00:47:23] It's been great.

[00:47:35] I get it.

[00:47:36] The podcast just isn't enough.

[00:47:39] That's all right.

[00:47:40] Head over to your favorite social app, search up Work Defined, WRK Defined, and connect with us.