The Tech is Here. People are the Decision. Our Download from the UNLEASH America Conference.

We just got back from UNLEASH America with one big conclusion:

The tech decision is over.
The people decision is still up for grabs.

In this episode, we break down what we heard from some of the biggest voices in AI, HR, leadership, and the future of work and where the conversation is getting very real, very fast.

Because right now, companies are saying humans are the competitive advantage.

At the exact same time, the market is rewarding cuts, automation, and cheaper labor.

That contradiction is the story.

We get into the three futures of work, why AI training is becoming obsolete almost as soon as it’s delivered, why psychological safety is suddenly a business survival issue, why middle managers are getting absolutely hammered, and why so many organizations are mistaking tool adoption for actual transformation.

We also unpack the bigger questions underneath all of it:
What work still belongs to humans?
What happens when AI can generate the output?
What skills actually matter now?
And who is making these choices for everyone else?

Inside the episode:

• the three possible futures of work
• why the AI and jobs conversation feels so chaotic
• insights from Ethan Mollick, Amy Edmondson, Gary Bolles, and more
• why you can’t install your way through change
• how culture debt is building inside organizations
• the pressure building on managers, employees, and leaders
• and 8 practical moves to respond right now

If you work in HR, leadership, talent, strategy, learning, or you’re just trying to figure out what AI is actually doing to work, this episode is for you.

Disclaimer: This podcast is for informational purposes only and should not be considered professional advice. We are not responsible for any losses, damages, or liabilities that may arise from the use of this podcast. The views expressed in this podcast may not be those of the host or the management.

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Transcript

Train Left Station Stakes

Speaker 2 0:00

The train has left the station. The question is whether people making the decisions in the next 12 to 18 months are gonna make the right call on humans and for humans when every market signal is telling them to make the cheaper one.

Speaker 0:27

Hey, this is your work friends. I'm Mel.

Speaker 2 0:30

And I'm Francesca.

Speaker 0:31

And we break down the now and next of work. So you stay ahead. Just a little over a week ago we attended the Unleash America Conference. Their motto is Reinventing HR together. And although the target here. Is primarily HR executives. One of the things that we noticed is this is not just an excellent executive conference on the future of work, but the rooms were filled with academics, economists, practitioners in the seat all in one place, which I've never really seen many other conferences. If you've not been to this conference. It is the one you should add to your list. Unleashed World is coming up in the fall in Paris, we attended the keynotes, the breakout sections. We bummed around the tech expo interviewing everybody and their mom on everything that was coming out of that. We interviewed 10 plus experts on site and we came back with a lot of thoughts. And this episode is the full download. Why? Because we want you to have the latest information to help you stay ahead. The main headline here was that there are three possible futures ahead of us right now. So before we get into anything, the reason the public conversation that you are hearing about AI and jobs is so confusing. And contradictory is because of these three possible futures. And so we had the opportunity to interview Gary Bowles. He is the global fellow of transformation at Singularity University. So he knows a little something about a little something in this space. And he shared with us that there were three potential futures.

Speaker 2 2:04

There's a future of abundance where there's tons of work and not enough workers. There's a future of scarcity where there's not enough work and tons of workers, and there's a future of both. And what we're in now is a future of both.

Speaker 2:21

Which is really why you are feeling all of these realities all at once.

Speaker 2 2:25

And here's our big thesis. The technology decision has already been made. Companies have already invested in AI and their tech stack. We'll talk about how heavily in a little bit, everyone has the same tools, but the people decision is still in front of all of us, and the structural incentives are actively working against making the right one. That's the real inflection point, not will AI change work that's been settled? The train has left the station. The question is whether people making the decisions in the next 12 to 18 months are gonna make the right call on humans and for humans when every market signal is telling them to make the cheaper one. And here's the tension that we literally cannot let go of. And just so apropos for the situation that we're in right now, the same week leaders keynote about humans having that competitive advantage, a FinTech company cut its staff for ai and the stock went up 24%. That's literally the microcosm of the world that we're in right now and the incentive structure we're in right now. So for the next 60 minutes, we're gonna talk about where things converged, where they diverged, and the eight moves you can consider next. Let's get into it.

Speaker 3:46

We are gonna jump right in, and this is where everyone actually agreed. Themes of we're all in alignment here. Let's agree on that. The first one, the playing field is completely flat and the speed is beyond exponential at this point. Ethan Malik is a professor at Wharton University and one of the leading voices the AI transformation Right now, if you are not following him, you should absolutely follow him on LinkedIn. One, he's funny as hell, and two, he just has really good information about how to move through this transformation. Malik said it plainly, if you ran an AI training in January, it's already obsolete. That's not a hyperbole here, folks. The models are improving so fast. The speed of AI is now exponential. We're sitting in sessions with leaders, they're doing great things, but it didn't really feel like we're removing at the speed that this moment actually demands. And I think people are in agreement about that as well. Like they don't know that they're necessarily moving at the speed that it demands. There were things that were discussed that were transformational maybe in 2019, but not as transformational. When we think about the space that we're in 2026, Ethan said even the AI labs themselves use his Twitter feed to find use cases. Nobody has figured this out. That's either terrifying or really freeing at this point, depending on how you look at it. We always talk about how we're optimistic realists over here. I'm gonna go with, that's really fucking freeing at this point, or should be. So if you're in your organization and you're trying to position your organization as the panacea of making things happen, just stop and build in public now in this movement requires the courage, vulnerability, sharing without perfection. And that was something I really appreciated about Malik's presentation.

Speaker 2 5:35

The other point of agreement that we wanted to call out here is what we're calling the 93 7 problem. Deloitte Human Capital Trends comes out every year. Kyle Forrest was there. We love Kyle. But in this year's report, they looked at how companies are actually spending their transformation budgets. 93% of the companies spend are on technology and only 7% are on people. That people budget accounts for things like rule design, culture capability, building. That 7% is what really creates a learning organization. It creates those skills that you build the AI with. And without it, you accumulate what's called cultural debt. 42% of workers say their organizations aren't thinking about AI's cultural impact at all. So people are feeling it within their organization. An even more stunning quote was 80% think their colleagues AI use is performative, polished output and no substance underneath. Which I was like, damn, it's harsh. It's a little harsh, it's a little harsh. You know that 80% number is wild to sit with though, because most people think that the people around them are faking it, and yet the incentive is to keep faking it because no one's measuring what's real. We heard a lot about AI adoption. Now we need to start looking at how are we weaving it into the organization? Because it's one thing if people are using it to do what you know, and if that feels performative, it means nothing. Again, this idea of cultural debt is something that people are absolutely looking to pay attention to, which I, for one, am a big fan of.

Speaker 7:10

I'm too, all right. The third thing that everyone was in alignment on was this idea that you cannot install your way through change. We met with Ben Smythe. He's the SVP of HR and Talent Advisory over at LHH, and he had one of the best analogies I think I heard during our interviews at the conference.

Speaker 4 7:30

One of the mantras we have is you can't install your way through change. Okay? So an analogy often used with them is, it's a bit like trying to build a home gym. You can build all the shiny equipment and you can put everything in, but it doesn't really change the habit of working out. It's how you get fit. Just'cause you've got the. And I think a lot of clients have tried to buy everything and then hope the adoption works.

Speaker 7:48

Companies are doing this exact thing with AI right now. They're buying the tools, they're expecting adoption to follow. They're wondering why nothing has changed. The missing ingredient isn't the equipment, it's the behavior change. And Francesca, you and I talk about this all the time, it all comes down to behavior. All of the behavior change, and that's what that quote unquote 7% is funding right now. So Kyle talked to us about how it needs to flip, and here's why, because you're not gonna get true transformation through this ai rush. If you are focused on just buying all of the tools and the equipment and you're not thinking about the human behavior component. The equipment isn't wrong. The equipment's just fine, but what's missing is the human habits here.

Speaker 2 8:35

You ever use a Nordic trek? I remember where we bought a Nordic junior high. That thing's possible. It's not a

Speaker 8:40

Boflex baby. Bowflex

Speaker 2 8:44

a Bowflex. Alright. Alright. The last one in the agreement phase if you want to have a learning organization, you truly need to have psychological safety. And so our girl, Amy Edmondson at Harvard, spent her entire keynote on this. You cannot have intelligent failure without psychological safety. One more time for the cheap seats and back. Okay. These aren't soft HR concepts. They're the structural conditions for whether your people can help you figure out the future. And you need your people to figure out the future. What is intelligent failure? This is something that Amy Edmondson talks a lot about in her keynote. The right kind of wrong, that is her latest book as well on what intelligent failure is. But it is a thoughtful experiment in genuinely new territory with a credible hypothesis, no longer than needed to gain the knowledge, not just breaking things and calling it culture. Fail well, might sound like Silicon Valley happy talk until she defines it. She's not saying break things. She's saying design your experiments to learn, not to impress your boss. Those are completely different things,

The Incentive Contradiction Gets Real

Speaker 9:49

yeah. You know what happens when you just break stuff? It stays broken. Wanna get into where it got complicated?

Speaker 2 10:00

Okay. This is chapter two.

Speaker 10:03

Chapter two. Yeah. It gets complicated. Francesca and I had such a great time and we noticed there was a lot of divergence also happening in the moment, and we were like, oh, these are opportunities we need to start talking about, okay, this is a big one. This was a central contradiction for us when we were talking about what are those forks in the road the conference overall was saying humans are your competitive advantage. Meanwhile, what we're seeing in the market is companies week by week, cutting half their staff and saying, it's because of ai. This is a structural problem. The black announcement that came out wasn't unique either. We're seeing that weekly. The market rewards it until investor incentives, executive compensation structures and board accountability change. Choosing humans can mean choosing a lower stock price. That's the mechanism. Nobody named on the main stage. I didn't hear that once. Did you hear that?

Speaker 2 11:07

No. No. It felt very, this is for organizations and individuals to figure out.

Speaker 11:13

Nowhere in this did we hear about government needing to be involved, and France and I talk about this all the time, it's like that famous meme where everyone's pointing the finger at each other. Who's on deck? Who's responsible for this? So we interviewed Kendra Jeer she's the CHRO over at Totality, by the way. Amazing person follow her on LinkedIn. And she said

Speaker 4 11:32

our shareholders are expecting that there will be the promise delivered of automation. Because it actually takes our cost of goods down, our cost of labor down and also creates a better customer experience.

Speaker 11:45

So that's the reality that these companies are dealing with, is they're managing of their shareholders here and the need to bring the workforce along on this journey, but also educating your shareholders here on what's needed to get there. Peter Henson the keynote was given by Peter Henson. He's a bestselling author. He wrote the Uncertainty pri principle. He gave a keynote on the Never Normal'cause. That's what we're in now. And he is a global serial entrepreneur and he has something called the Apple Chapel. So check him out. Peter Henson also gave a little bit of urgency in his keynote here, and he said that the cost doing goes to zero, but we're living in a world where the cost of waiting becomes a catastrophe. There's a real urgency here, but here's the rub that Francesca and I walked away with right now there's approximately 2000 people, C-suite leaders that sit in the Fortune 50. That includes all the C-Suite board, et cetera, and key government representatives. When we think about our government, they're making decisions around this that will shape. The economic future of 342 million people.. So there's 1% of people making huge decisions that are going to impact 100% of people. That's an extraordinary concentration of power. At a moment when incentive structures, reward cuts. The other issue, most Americans don't work at Fortune 50 companies. They work at 50 person companies. They work on Main Street. They work in 500 person companies, school, districts, municipalities, governments. The locus of innovation has to be inside organizations in the crowd, not waiting for the Fortune 50 or government to figure it out. We have to notice our power here in terms of figuring this out together, and organizations that start to really tap in to their people to help do this together, they're gonna be the winners that come out on top in the future.

Speaker 2 13:56

The other place where this gets complicated is the escalation that no one's really ready for. The speed of this intelligence, this is the stat that you make every leader update their timeline. Ethan Molik, again, the Wharton professor cited the GDP eval experiment one of the most rigorous tests of AI versus human performance on complex, long form domain specific tasks. So this is can you pass the bar exam, right? Can you play chess, again, complex, long form domain specific tasks. And when it launched last summer, the best AI was beating or matching humans about 45% of the time. Within the latest models, it's 82%. In literally less than a year, these models have gotten that much better that jump is significant. That scaling law means that every 10 x increase in compute produces a meaningful jump in capability, a very meaningful jump in capability. They're building bigger and thinking longer simultaneously. And the implication here is if you built your AI strategy around what technology could do 12 months ago, you are working from a fundamentally different baseline than what exists today. And we hear this all the time. People are like, oh, I'm gonna need an AI train training for this summer. I'm gonna need an AI training for fall. And you're like, you can't.

Speaker 15:17

That's not it.

Speaker 2 15:18

The speed of this is something like we've never, ever seen. So this is why Ethan says that the AI training you ran in January is already obsolete. Not as a criticism, but as a feature of the environment. this Isn't whether you're keeping up. The question is whether you've built an organization that can keep updating, and I think this is where I started having a panic attack, and if you talk to Mel on day two, I was like, oh shit.

15:43

We're

Speaker 5 15:43

fine. We're fine.

Speaker 2 15:45

And you're like, are you okay? I'm like, no, because I don't feel like we are meeting the moment with what needs to be done in terms of the human capabilities. And when the cognitive labor of a human can get matched by a machine that is much cheaper, I have a big worry. That's number one. Number two, when we're talking to a lot of leaders in these organizations about what they're doing to meet that. They are, they're talking about my people need to learn how to use chat GPT or copilot. And I'm like, not right dude. You should be running like agents and workflow or something.

Speaker 16:28

Not the right move.

Speaker 2 16:29

Yeah.

Speaker 16:30

Yeah.

Speaker 2 16:30

It's a little, it's a little, that was a big rub that, that we talked about. And I had a mild panic attack,

Speaker 16:39

but I think it, it leads into this next point, which also comes from Ethan Molik by, you just gotta follow Ethan by the way. He said there's a bitter lesson here around what we value output versus process. And that's going to change what your organization gets out of this moment. His sharpest warning to us in his keynote was that AI already beats MBA students at generating startup ideas. It outperforms humans at persuasion and creativity in most controlled studies, you guys, that's. Wild. Okay. His bitter lesson is if your organization only values the final output, the deck, the report, the deliverable AI can and will systemically replace that work. The only survival is if the value lives in the process. And this is where this human edge comes back in the discussion, the conflict, the judgment, the human relationship component that is critical. There's a darker implication to this. AI is 9.7% more persuasive than humans in debate context and can shift deeply held beliefs for people including conspiracy theories. In three rounds of conversations, just three rounds of back and forth. With ai, it can change hearts and minds. That's crazy. So if organizations start using AI to communicate transformation to employees, the question isn't just is it effective? It's, is it honest? I don't know. So start to think about what is your job actually for? If it's just to produce output, that's gonna be a problem. If it's to think, decide, build, trust, have the hard conversations, that's gonna be the differentiator. But this is also where organizations have a moment in time where they also need to decide what do you value more the output or the process. You have agency here if you're an employee, but if you are in the C-Suite, again for that Fortune 50, this is also the decision point you need to make for your organization because your employees are taking your lead on what you value most.

The Great Stay And Secret AI

Speaker 2 18:54

All right. Two more to go in. Where this gets really complicated, I'm bringing it in with the Great Stay and the Secret A I use. So Andrew Flowers, who's an AB cast economist, painted the labor market for us. No surprise here. We're frozen. Like frozen low hiring, low quits, workers of job hugging, grateful for the stability and not going anywhere, I hear that from employers and I hear that from employees too. I I can't find this exceptional talent'cause they're not leaving for a sure thing. Meanwhile, if we go back to Ethanol's data, it shows that nearly half of workers are using ai, 33% are using it every single day and reporting three times productivity gains on their tasks. Of the things I thought was so funny about his quote was like, your workers are saying that 33% of them are using it every day. Three times productivity gains on tasks is what they report. And guess what? None of you are getting three times productivity gains. Your policies have made it very scary to use ai. So no one's telling you they know what productivity gains means, and it means you wanna fire people. Yeah, they're afraid of AI bands afraid of being replaced or just don't see what's in it for them to share. or they're planning a startup to compete with you. And that one lands a little differently too. And I get that. There's an opposite of this, and I wanna go back to Kendra from totality CHRO of a 5,000 plus organization, this is not someone that is running a small shop. This is a major billion dollar company

Speaker 4 20:22

80% of our employees are using these tools across the entire organization. So enablement for us has been a huge focus but everybody that's using AI is saying that their personal capacity has improved 20 to 25%. They have more time to be creative. They have a thought partner or guide by the side. Even some of the quality of their work has improved and so that's super exciting.

Speaker 2 20:44

That to me says they have created the right environment, the right psychological safety, and that organization to actually think about how do I use this for my job and get to that higher level work. I've seen a lot of AI adoption case studies and use cases in a lot of smaller organizations. She's one of the more major organizations that I was like, that amount of adoption, that amount of productivity gains in that safe environment, I think is phenomenal. And she should be on the speaker circuit as far as I'm concerned. It's not a coincidence, it happens because culture signals safe and some technology completely different outcome, and it's based on the trust architecture.

Speaker 21:20

Alright, we're moving on to the last diversions here, which was skills versus experience versus AI and talent strategy. We sat in a talent panel around whether or not your talent strategy during this time is actually driving revenue or reinforcing old paradigms of how work should work. In that panel we heard from Brian Miller from Levi's as well as Shannon Caswell from Prudential. Brian was interesting. He mentioned that Levi's was moving away from skills mapping toward experience and judgment assessments, he's calling out that AI is compressing the time to skill so fast. That skill alone is less meaningful as a differentiator when it comes to talent and identifying talent and getting people up to speed. What he specifically said was, skills right now are really getting disrupted by ai. Your ability to come up to speed is a nanosecond. Your ability to have the reps to be seen as someone in a hard moment who's done this, that's a new way of looking at assessments of leaders. And again, this goes back to humans as your competitive advantage to have this lived experience. That's the thing that's gonna really drive your organization. as well.

Speaker 2 22:41

Chapter three.

Speaker 22:42

All right. There are a couple things that nobody was really saying out loud

Speaker 2 22:46

A, that the middle manager is in real crisis. Almost every speaker kind of pointed here lightly, but never solved it and never spent enough time here to say that this is at a crisis level, which we believe it is. Middle managers are where the apprenticeship breaks and where AI policies get enforced or ignored. Where cultural debt accumulates on a Thursday afternoon, they're being squeezed from above, they're, they need to move faster. They need to prove ROI show adoption metrics. They're probably taking on more because they've been reorged five times from below. They're managing people who might be secretly using AI and not telling them, might be freaking out about their job, trying to mentor when AI would do it faster, and they probably have more people underneath them than they ever have before. It's this perfect storm, I'm also a little bit fearful for the fact that this is also one of those groups that's still being a target of elimination in roles as well. So we see a huge hollowing out of the middle manager when we should be putting a lot more investment there. It'll be interesting to see, and I'm hoping that might be one of those places where people cut too hard and they need to bring it back. Because if you wanna run at the speed in which AI is moving, you need that apprenticeship model. You need those managers coaching. If you want your business to run with some semblance of humans, you need them.

Speaker 24:08

They don't get enough love the other thing that we were seeing, Francesca and I love a good tech expo, we were paling around and we started to see a theme and we're not sure whether to officially call this the quote unquote career score. There was a lot of technology and we're not gonna name names. A lot of technology out there that was really talking about how there is this profile being built on you right now. 8 million plus professional profiles in a system based on 20 to 30 public data sources per profile, legally gathered public information. That is essentially presenting you as candidates for roles based on these profiles and saying how good of a match you are. And all of the vendors that are providing these profiles say the same thing. They're just providing the profile. It's up to the organization to bring in the human component to decide. But there was a booth set up by Experian who is really in the talent game. Experian, as is a credit bureau agency, but they are heavily in the talent game. Which was a surprise to me. And I might just be like, really out of the loop there.'cause I haven't been in talent acquisition for some time. But Francesca, was that surprising to you to see how involved experience was in the talent space?

Speaker 4 25:35

Yeah. And I don't mean to be all conspiracy theory by any means, but it felt a little black mirror.

Speaker 25:46

Yeah. That episode where you have that public social score and people can up vote or down vote. It wasn't to that level guys, we don't wanna create like a whole thing. But here's the thing. Again, legally gathering publicly available information to create what is this desirability score, for lack of a better word, for every working professional. So it wasn't just based on your resume, it's also based on inference. This one scared me the most. I think. One example that was shared with us off the record is if you held a VP or senior director role during a certain period at a company, one of the things that they were measuring was whether or not that company was profitable during that time. If it was your score goes up but if you were there when it wasn't profitable, your score could potentially go down. There's a real big problem with that though, because that doesn't necessarily mean your specific performance had anything to do with influencing that. There could have been business considerations, et cetera. I think that's where Francesca and I were like, I. What, what is happening here? Company performance does not equal your personal performance. It just doesn't, never, has, never will. There's so many additional contributing variables here that need to be considered. Yes. So the other side of this a number of vendors are already in the legal system in getting sued because the legal system hasn't really caught up with this framework yet. And we're not saying this tech shouldn't necessarily exist. It's just thinking about the human sides and your own personal rights here on the information you own that's being shared about you. To others, especially when it comes down to your livelihood and how it can impact your career in the long run. Those are absolutely things that we should have within our control. You have, for example, within your control, your LinkedIn profile, you've built that. You own the data and the information. When a company is calling to verify your employment for background checks, you consented to that HR and those organizations can confirm the dates of your hire and whether you're rehirable or not. That's for a reason, folks, safely. There needs to be a layer here where you can say, yes, I consent to this or not.

Speaker 2 28:05

I think it's fair to say this is in its infancy in terms of figuring out this, but you will have a score just like your credit score as it relates to your desirability as a candidate, and just like you cannot buy certain things or you're not eligible for certain things without a high enough credit score, that will most likely be the same for your job.

Speaker 28:27

This is an opportunity though. We had Gina Clementon. She is the co-founder of Good Story a couple months back, and she did a great episode on your personal brand. If you haven't listened to it, you should. If you aren't already treating your LinkedIn or your public profile as a personal SEO venture, you absolutely should. You need to be findable. You need to be discoverable. You need to be able to attribute your work across the internet. You can't hide anymore if you want to be a viable candidate for opportunities. There's also a real opportunity here though, for HR leaders or tech people who are making decisions about the types of tools that you're bringing into your organization. There needs to be a real vendor governance conversation right now because. This could be a real weird legal zone I could have dove into this for hours. One will be following for sure.

Education Access And Policy Wild West

Speaker 2 29:20

Here's the other one that blew my mind. This is actually the thing that totally put me over the edge.

Speaker 5 29:29

We did some breathing. We did some snacks.

Speaker 2 29:32

Sorry, Lance and that guy from Workday I talked to after this. Sorry about, sorry. I apologize. I'm sorry. So it's the education and access fork. I attended a session with the Chief Innovation Officer from the Department of Labor, and they're building an AI literacy strategy, which is great. I have no problem with that. I really don't. I think that's great. But the detail that sent me into a panic was the fact that they are transferring$10 billion in funding from the Department of Education to the Department of Labor that one really bothered me. So the reality here is this fork creates an issue with access. If the access point for AI literacy and skills development is now the labor market participation being already employed already in this system of age, whatever that means, child labor laws are getting rolled back. Then people who are not yet in that system are being left further behind. The most equitable distribution mechanism we had for education is being d resourced and I would argue too, that AI literacy is fantastic, but if we go back to that training you ran in January is already obsolete and that you're human. Edge is going to be your differentiator. Then I would argue that potentially we need to be investing way more in education and double click into the skills that the world economic forms, they matter most are those human judgment things, critical thinking, curiosity, emotional and social intelligence, and those are the skills that are being cut, underfunded, or even merged. I'll tell you right now, Portland Public Schools. Which is pretty well funded. They're needing to combine fourth and fifth grade next year because there's not enough funding. Think about that. I'm more concerned with what our budgets say about what we value in this country, we value military spending, we value labor. But if critical thinking, curiosity, emotional and social intelligence are going to be what's needed. And we are not funding those. In fact, they're getting gutted from the educational system. That feels pretty bad, the other thing for me is the US government's ai, like AI policy. Is basically like Yippy, Cayo, Caye motherfucker. It is truly wild west. They are de ragging. They have CEOs from AI companies on their board advising about regulation, which is a conflict of interest. No one is coming to save us from a government perspective. So the question is, which leaders, especially in boardrooms or in communities or in budget meetings, are gonna treat this as their problem to solve?

Speaker 32:27

Yeah I keep coming. When you and I did the math on, okay, let's take a look at this. Who's really influencing this right now? When you think about like social structure, society, what jobs even mean in the future for people? It is this moment in time for the Fortune 50, of course the Fortune 500. Okay, if you wanna expand that number. But that's still a small number of people who have incredible power right now to really influence the government here in a partnership. To make sure we live in that future of abundance. And and the, that humans do maintain and remain the competitive edge, not just in our workplaces, but in our communities, in the way that we show up in the world. And I don't know, I think this one is really important. I think you're reaction and panic around it is valid, and we all should feel that because this is our future. Yeah.

Speaker 2 33:25

One of the things I did take Sola in was when we talked to Gary from Singularity, who is, an optimist by trade, he said this, I'm optimistic that we can do this. I'm optimistic. That humans are the ones that are gonna solve these things, not the technology. I'm optim optimistic that when you go back to communities, you go back to anchoring people and being connected with each other, whether it's where you live or it's where you work. leaving on a high note. All right, Mel,

Repairing Apprenticeship And Middle Management

Speaker 34:01

So let's get to number four of what no one was saying. The apprenticeship model is broken. We did hear one really good fix that we wanna cover, but we didn't hear a lot of around fixes for this and we hope to hear more. I think CHROs came in really excited about the AI native Gen Z folks. But Ethan Molik really came out with a strong quote that I think is important to call out. He essentially was pressing on this comment from CHROs, pushing back and saying, oh yeah, these AI native kids are so great. You're not talking to AI native kids. You're talking to Claude. All they're doing is parroting every question you have, pasting it into Claude and handing back the answer. They have no idea whether it's good or bad. That should verify you. This is what I think, Francesca, why your point about this move of funds from the Department of Education is so important. And if you guys don't think this is real I'm a coach. I meet with a lot of actual, what I would consider ai, native Gen Zs, and I've seen this in real time we have to really nurture their own critical thinking. What are your thoughts on this? I don't know. And they'll ask Claude or Chachi BT in real time. And I'm like, nevermind what Claude or Chachi BT thinks about this. What do you think about it? What do you feel about it? And there's a real struggle there. And Francesca and I do a lot of strategy work. We've done our own research here. There's a fundamental problem with people not even knowing how to learn. We actually have to reteach people how to learn for themselves. There's a huge gap there happening right now.

Speaker 2 35:50

Huge.

Speaker 35:50

And a huge

Speaker 2 35:51

Of all ages, by the

Speaker 35:52

way, of all ages. Like I, they just don't even know how to learn. And there are multiple studies, on how people are relying too much on AI to do their critical thinking. For them, it is making us dumber. We're losing the competitive edge, everyone said is needed for your organization to have a competitive edge. That's a real problem. And this is where apprenticeship really has to be fixed. So something else that Ethan Malik was saying is every middle manager has stopped trying to teach people because interns will cry that they're not that good and they'd rather just have AI do the work for them. So there's this perfect cycle. Falling apart in the existing apprenticeship system. This is also where cultures of coaching become critical within organizations because we need to be coaching people around this. One of the people that we had the opportunity to meet with was Jason descent from Toshiba. He's A-C-H-R-O there. And what I we really love to hear from him they're bringing back high school co-ops and company paid apprenticeship systems, which is huge. Huge. I grew up in Marden, Connecticut. You could look it up. There's a high school there, Wilcox. They were a trade high school, which was amazing. And we need to have more of these within our public school system where they can get that experience. What he told us is they're going into these high schools and trying to create partnerships to have an apprenticeship model for Toshiba. I think that's incredible that you're offering people this second path. I think Francesca and I talk about this all the time. We covered the trades and how there's a huge gap happening there because of this, push for college only. But now we're seeing why both paths, all paths are critically important for everybody. The biggest thing here though is that they're paying for it. We don't see that often. Francesca, have you seen that often?

Speaker 2 37:44

No. I remember when he said it when we were interviewing and we asked, oh, are you paying for that? He was like, yep. And you gotta make the investment. And I'm like, fuck. Yeah. Because there's two things you typically see with these apprenticeship programs. A the pay is not front loaded or these kids need to invest in their own equipment, their own tech, which is substantial. So

Speaker 38:02

huge barrier.

Speaker 2 38:03

Yeah. So she was taking care of all of that kudos. And the other thing is they're not guaranteed a job after they're done. And so Toshiba was taking care of that. And so to me that's viable path.

Speaker 38:18

A hundred percent. I loved his quote

Speaker 2 38:21

what I'm trying to do in my own organization is go back to the old playbook, which I would say. Probably late nineties. Even before that they used to have co-ops in high schools. Yeah. Yep. A senior where you could work in the factory half a day and then you have school for half a day. So I'm gonna try an old playbook method.

Speaker 38:36

We're bringing back apprenticeship programs, we have to pay for it. It's an investment, and then it's up to you what you do other than just training to keep those employees. He's talking about organizations there. You can't just offer training. And we talk about this all the time, there are other incentives you have to be keeping. If you're worried about the cost, it means you haven't yet looked at your system to say, how are we gonna retain these folks once we've done this and made this investment in them?

Speaker 2 39:02

Let's talk more about that frontline, because that frontline worker gap is missing from the conversation. The unleashed conversation skewed almost entirely toward white collar knowledge workers, but we also wanna talk about the entire labor market. If we go back to Andrew Flowers, who's that app cast economist. He made a related but distinct point that the entire US labor market is being carried by one sector, Mel, what is it?

Speaker 39:27

Healthcare.

Speaker 2 39:29

Healthcare. And that's about to face a massive policy shock with 1 trillion in Medicaid cuts designed to bite around 2027. His concern was a policy driven threat to the one pillar the labor market is standing on. 95% of all net jobs added in the US last year can be attributed to just the healthcare sector. And in the tax bill, there was 1 trillion in Medicaid cuts designed to really bite at that midterm elections around 20 27, 90 5% of all net jobs were in healthcare.

Speaker 40:00

And the biggest thing for me here is that policy risk is the biggest risk to where we head next. When I was sitting in the breakout for this and I heard healthcare is the industry holding us up and it's about to get hit all I could picture was the US on a toothpick that had a little crack in it. That was the visible that went in my head. I was like, it's not even ai, it's healthcare is holding us up and Medicaid's about to knock us out. What's going on?

Speaker 2 40:27

We're

Speaker 40:27

all having this AI conversation. And I think like some of the real important stuff is going through the cracks.'cause that to me was a huge headline

Speaker 2 40:35

it's a huge headline. It's interesting because it was so AI heavy, but to your very good point. We're on a toothpick with healthcare. There's the private equity markets thing that's happening, right? There's a fucking Warren Iran right now. My yogurt is$2 more than it was a month ago. And I'm pissed. There's a lot going on,

Work Slop And Measurement Failures

Speaker 40:54

there is a lot going on. Anyone wanna donate to our therapy fund after this? No. Okay. Here's a couple other things and we'll go through this quickly to get you to the moves. So the next one was around work slot being the silent cultural crisis. And we touched on this a little bit, up at the top right 80% of employees think they colleagues are using, performative ai. But this is what we go back to that whole, what do you value as an organization, right? Is it the process and the human judgment? Those, the taste, critical thinking, the curiosity, the discussion around these things. Or is it just the output? And it, this point really stood out to me because when organizations optimize just for productivity as the primary AI metric, that's what they're getting. Work slop output, that looks great, but there's no substance to it. And what Ethan called it, essentially a fools dashboard. This is the Fool's Dashboard. So as we mentioned, 80% of workers are already watching this happen with their colleagues in real time, which is contributing to cultural debt. It accumulates on every single call where someone shares an AI polished deck and nobody believes in what the hell they're even presenting. They're just like, great. Did you come up with that or did AI come up with that? I just got off a call with a friend who said she presented on something, she's running a strategic project. And then someone was like, oh, did AI help you write this? And she's no, I had to think about it. And they were like, oh, really? But it's so good. Imagine how all the hours of work she put in with her own thinking to come up with that, and then it's just assume AI did the work for you. What we didn't really hear clarity on, there were a couple of things. If there's, this is the Fool's dashboard, what is the innovation dashboard look like? What are we really measuring that matters That I don't know that we got a lot of clarity around.

Speaker 2 42:54

And that might depend on your company. That might be depend on what you're doing, but the whole idea that everything's around adoption now. Everything's around productivity. What the fuck does that get you

Speaker 43:04

right?

Speaker 2 43:04

Which brings me to eye point, which is around, we really have a mem, we have a measurement problem and no one to your very good point, Mel had a really satisfying an answer at all. Companies are measuring adoption great, but not outcomes. The difference really is everything. So Kyle Forrest, our friend from Deloitte was really candid in his interview saying that most organizations are tracking logins, session time, feature usage but lagging indicators of adoption, not leading indicators of whether the human edge is actually being built. And again, what those things are as your differentiator. And without a real measurement framework for human investment that 93% of your budget spend on tech and 7% on the human piece loses in every single budget meeting. You can't keep fighting for that 7% if you can't show what it produces. I think this is fascinating because I think a lot of people are like, oh, just have an AI training or, my people just need to know ai. We get into these conversations a lot for what. And then you get into a bigger conversation around, you need to rethink your whole system. One thing that we thought was in really interesting is Amy Edmondson, if you go back to her speech on how do you really build a learning organization that produces that ROI, on that 7%, she has something called an integrated employee value proposition, and it offers a starting framework where you measure things like material offerings, growth and development, connection and community and purpose. These are the four elements of what people are really looking for in a job. An employee value proposition. Why should I work here? Why should I give it my all? Why should I continue to learn and innovate? And again, what they need are, yes, the material offerings, like your salary, your Benny's growth and development. Not just learning programs, that's like a great manager coaching, apprenticeship, different job opportunities, connection in community, like feeling like they belong, feeling like they're part of something and purpose. They know why they're doing something. They understand how their role contributes to the greater good all together, not separately. And when measured in an integrated way, they predict performance, engagement, psychological safety, and lower burnout, and turnover far better than any single metric alone. She's doing really deep research on this. So if you're in this conversation in your organization right now, absolutely check out her work. That to me was the most interesting framework to start to look at. It's a place to start.

Speaker 45:43

Yeah. She also had a quote out of her talk where she said, companies tend to go for the easy, easier things to offer, pay remote work, but those have the lowest lasting impact. Meaning and purpose is hardest to get in place in a meaningful way, but the most lasting impact on your organization. That stood out to me because again, we keep talking about this human as your competitive edge, that takes time. Everyone wants to move fast, fast, fast, but there are some things you're gonna have to slow down on to get it right.

Speaker 2 46:15

Yeah, and when we talked to Kyle too, he was saying that the majority of CEOs they interviewed said their strategy is being fast and nimble. So many of these things that are needed for that lasting impact

Trust Architecture And CEO Profile

Speaker 46:28

that is a huge tension. All right. Last thing Cita Berg was speaking, she's the former CHRO over at Spotify. And what she was talking about was IA versus ai, which is the most actionable insight. It was great to hear her say this on stage, but I didn't hear it necessarily throughout. So Katerina Berg's argument was the conversation is too focused on AI when it needs to be focused on information architecture. IA is what she was calling it. What does that mean? Clear, consistent, and compelling communication context that actually guides humans through stress and change. Trust architecture, which is the foundation that makes any AI rollout work or fail. It is not about the technology, as we mentioned, it is about the people. So we're throwing technology at everything. We're not throwing enough at the people side of things. This is the moment that needs to be met right now. That's the lever that needs to be pulled. So if you're approving budgets, you need to start making that flip from the 93 7 to something a little more 50 50 at least, to get things moving. You want lasting impact. You gotta invest over here. So loved her call out about information architecture. That's super important. You can't just shoehorn in new technology. It has to be built through this trust. We all know that when trust goes up, speed goes up, when trust goes down, speeds goes down and we saw it with the trust report from Gallup this year that we covered. It just keeps getting lower and lower.

Speaker 2 48:02

The last gap here is the C-Suite profile gap. And let me just sum this up. What got us here will not get us there. And that's very clear. We heard a lot about what employees need to do and what middle managers need to do, but almost nothing about what the C-Suite profile actually needs to look like right now. The current profile isn't built for this at all. There's a significant uptick in CEOs that are coming from tech backgrounds, right? In 2000, it was like less than 3%. Right now we're sitting at 31% of leaders that have a tech background. But what's fascinating when your differentiator is humans, what does that mean for this moment? There was also a lot of talk about the need for courage. Courage to push back on shareholders. When the incentive is to cut, it takes a different literacy to orchestrate human plus agent labor, so it's a fascinating place to be. A we're ultimately gonna be doing work very differently and it calls for a very different type of leader. There was a lot of discussion around CEOs and C-suite executives needing to be bold, courageous, empathetic systems thinkers. But bold doesn't mean break. It doesn't mean butcher your workforce and just cut big slabs off of it. It's leaders that need to be more courageous to make choices that make sense for their organization in the long term. More of that idea of getting more humans over to the side as possible. And it's not, again, just the CEO or the CHRO or the CMO, it's all of them, and it's all of them working together in unison. And that is a. Very different task. I think we've had the visionary, CEO or the great CMO with the CEO or the great CHRO and the CEO. But now they all need to be working in cahoots

Eight Moves For The Next 90

Speaker 49:58

yeah. And Pete Hints insured, we asked who's a good example of this, right? In terms of what that looks like. And I think it's being defined and that there's an opportunity here to really outline this and get it right. And he mentioned the Walmart CEO stepping away'cause he realized, hey I'm doing all the right things, but I might not have the right profile to be the one who takes this through this. Alright, so what do we actually do? Let's get into moves. Let's get into moves. Okay. Ask the business problem. Question first. Every single time before you build, buy, launch, anything, get aligned on what the problem that you're actually trying to solve is. We talk about this all the time. This should be the number one thing. This sounds obvious. Shannon Caswell from Prudential named the most consistently violated rule and organizational transformation is this exact thing. And if you leave this episode with one habit, make it this one. Nothing else in this list works without it. It's the foundation. Every move that follows depends on knowing what you're actually trying to build and why. Alright, move

Speaker 2 51:08

two. Map your work, assisted, augmented, or powered. Now that you have the problem, understand what you're working with. Go through your organization's work, not people. Work and categorize it. And this applies whether you're a Fortune 50 CHRO or a team with eight direct reports, three categories AI assisted IE humans doing existing work faster with AI support ai, augmented humans with AI genuinely working together, different output than before, or AI powered AI doing the work. Human role fundamentally change. Then the critical parts. Share the map with your workforce so they can co-create their future. That level of transparency is really what's separating culture debt from culture investment.

Speaker 51:50

All right, move number three. Hunt down your yester work. You can't add new capabilities while old ones are still clogging up your organization. Peter Hinson's concept around yester work needs to just become part of your permanent vocabulary within your organization. Yester work is any legacy process that keeps persisting because people are comfortable with it, not because it's actually adding value. So that report, nobody reads the meeting. That could have been an email, the 20 15 approved chain, the nine box, get rid of it.

Speaker 2 52:24

So move number four. Sorry, move number four, fix your information architecture before your AI strategy. You don't need a new tool for this. You need to be clear, honest, consistent communication about what is happening, why it matters, and what it means for your people. So before your next AI rollout audit, the trust architecture, do people understand the context? Do they believe what they're being told? Is there a safe place to ask questions that might sound dumb? I love that IA before ai. Little reversal there every single time. And remember the persuasion data. AI is more persuasive than humans in most communication tests. That capability cuts both ways. Use it to build trust, not to manufacture compliance. If your organization has been quietly using AI to cut costs, while publicly messaging about human investment, people know they always know. And no new tool will fix a trust deficit.

Speaker 53:18

Nope. All right. Move number five is to build your lab and your crowd. Stop waiting for the vendor to fix all your problems. Ethan Malik's model was three things. Leadership that sets the tone and uses AI visibly. A small internal lab doesn't need to be technical, that experiments constantly and ships things fast, and the crowd, your actual workforce, who understands their domain better than any single vendor. One of the things that he said was, the most successful teams I see implementing ai, get a small cross-functional team, an impossible task, and see how far they get. If they fail, it's learning for everybody. If they succeed, oh my gosh, don't just try and do 5% improvement. Try and transform things. I loved that quote from him. MasterCard's Unlocked platform is what a crowd investment looks like. In practice, an AI powered internal marketplace, connecting employees to projects, mentorships, learning opportunities tied to business outcomes. This is not a formal training program, and we've seen other examples like this too through Kendra Totality. We also interviewed Brandon Sammu from Zapier earlier this year. They're also an example to follow. So you wanna create that living infrastructure for internal mobility skill building with ai, making the matches and getting smarter over time. Give teams impossible tasks to solve. Not 5% efficiency improvements, actual transformations. If they fail, it's learning for everybody. If they succeed, everything changes and potentially for the better.

Speaker 2 54:48

Okay, move number six, design for intelligent failure. Stop rigging your pilots.

Speaker 54:53

Yeah, that's a

Speaker 2 54:53

folks, stop rigging'em. So if you're running an AI pilot right now, ask yourself, is this designed to succeed? And if yes, you're actually doing it wrong. So Amy Edmondson has four criteria for a real pilot. A, it needs to be representative of real work conditions. It has to have an explicit learning goal. No compensation tied to the pilot success. We see that a lot. And explicit changes made afterwards, she had talked about if you wanna be a better innovator, you better design your pilots to fail. Not in big, ugly, expensive ways, small, safe, and smart enough to learn from. And the key here is you need to learn from your pilots. That's the goal of a pilot, not success learning, a pilot that only succeeds, taught you nothing. And learning again is the goal.

Speaker 55:46

All right. Move number seven. Answer the question, what do you do with the time you've saved Speaker, after speaker said, AI frees up time for higher value human work, but no one really defined what that actually looks like. So name it, explicitly, when AI handles the scheduling, the scorecard summaries, the first draft reports, what specifically are your people doing with that time? If the answer is more of the same, but faster you're actually just building an efficiency treadmill, which isn't the purpose of this whole thing. If the answer is deeper relationships, solving harder problems, building judgment in your junior staff, that's that human edge component that you're nurturing and building over time. So absolutely, ask yourself that question yesterday.

Speaker 2 56:35

All right, move number eight in our last move. Measure the human edge, not just the adoption rate. If you can't measure it, you can't protect it in a budget meeting, and I think that's a really important thing to remember. Edmondson's, integrated employee value proposition gives you a framework, measure, material offerings, growth, community, and purpose, together not as separate initiatives, and the integrated approach produces significantly better predictions of performance, engagement, psychological safety, and lower burnout and turnover than any single metric alone. Honestly, right now, that's probably your best business case for that 7% spend Forced distinction is the starting point. What's your lagging indicator? Adoption logins versus your leading indicator like your team, your composition changes tied to business outcomes, decision quality, judgment. Development and junior staff, et cetera. So the CFO will always ask you for the ROI, build the measurement framework before you need it, not after you already lost the budget argument.

Speaker 57:45

All right, friends, we're gonna close this out with our optimistic realist read here. Okay. One, this is genuinely exciting and genuinely hard for everybody. Both of these things can be true at the same time, they are true At the same time, the people doing well with this are holding both. They're not pretending in any way. And that's really important I think for me. Ethan Molik, building in public and the vulnerability piece is huge. And then there's a two level social contract, right? Level one. If you're one of the. Approximately 2000 people in the Fortune 50 C-suite or government seats making decisions that touch 342 million lives. We need to see real action, not the keynote, the white paper. Real visible, proof bold doesn't mean break as we said above, but it does mean something. So show us what that looks like for real level two. If you're not in the room and most of us aren't, you have p more power than you actually think. So you know this isn't just happening to you. The locus of innovation is within your team. It's how you use the time that AI gives back to you. It's in whether you build judgment in the people around you instead of just outsourcing it to a bot, and then really doubling down on this. Bold does not equal break because breaking things just breaks things. We heard the word courage more times than we could count over the course of that week. But courage is the, at this inflection point it's a choice and a deliberate one to invest in people when the market is telling you to cut people, to redesign work instead of just automating it, to build the conditions for your people to actually help you figure out the future. Bold means taking action right now that sets your organization up for the future of abundance, not the future of scarcity, the future of abundance where there's enough work for everybody where, and enough prepared people to actually do it. The future doesn't happen by accident. It's because we decided to build that future and we built it together. So this can't be built alone. The one ask that we have here is don't try to implement eight things from this episode. Pick one move that you wanna try out the next 90 days. If anything. The business problem, the work map the yes or work hunt down the ia, audit the lab, the honest pilot that question to ask yourself. Start managing your own professional SEO If you're looking for a job, I guess one thing this week, reach out to us. We wanna hear what you're trying to do. So yeah, if anything, make one of those moves yours. Navigate through this, I don't know, trust yourself. What would you say, Francesca,

Speaker 2 1:00:42

I think at the end of the day I am asking myself, what are we doing all of this for? What's the point? Genuinely. And my hope is that we make choices that will make all of us healthier and more prosperous in the long run. My fear is that I don't see a lot of evidence of that.

Speaker 1:01:04

Agreed. I keep coming back to that statement around what do we really value? Is it output, is it productivity, is it efficiency? Or is it the human competitive things we keep saying is the most important thing. There's a, I feel like oh, fast and nimble doesn't. It doesn't align with these human things, and I think a lot of people right now are focused on output

Speaker 2 1:01:34

Yeah. I know that in the arc of history, there's always people that will come outta nowhere and just do some really amazing things and do some really beautiful things, and it is very clear that the tech has left the station across the board. I am looking forward to seeing people making some great decisions about people.

Speaker 6 1:02:02

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