George Jagodzinski (00:00):

Today's episode is a little different. Normally I bring on one guest. Today I'm bringing on the whole year. We went back and reviewed every single conversation we've had on evolving industry in 2026 so far. And somewhere around episode 66 or 67, I started noticing something. There was this thread that kept showing up. No matter who was sitting across from me, a chief product officer in government, a Wall Street risk guy, a robotics investor, or a columnist who's written more than 500 columns for the Wall Street Journal, everybody came in talking about AI at some point, but almost nobody's real edge turned out to be the technology. Over and over, the thing that actually moved the needle was human.

(00:38):

So today, I've pulled the four biggest things I think every leader needs to carry from the back half of this year straight from the people who are actually out there getting the hard work done. Let's dig in.

(00:59):

Welcome to Evolving Industry, a no BS podcast about business leaders who are successfully weaving technology into their company's DNA to forge a better path forward. If you're looking to actually move the ball forward rather than spinning around in a tornado of buzzwords, you're in the right place. I'm your host, George Jagodzinski.

(01:25):

Let's start with the one that surprised me the most. If you'd asked me at the start of the year what the number one skill for 2026 was going to be, I probably would've said something like, "Learn the tools, learn the prompts, keep up with AI." I literally told all my friends and employees to go spend a couple hours in the AI gym every day, but it turns out the most valuable skill might be the exact opposite, learning what to ignore. Nobody made that case better than Chris Mims. He's the technology columnist over at the Wall Street Journal. He's written more than 500 of these columns and he's built up about the best BS detector I've ever come across. And he told me it doesn't start with the tech at all, it starts by looking inward.

Christopher Mims (02:02):

I've learned to be careful when I'm excited. I've learned to be careful when everyone else is shouting that this is the latest, greatest thing and you got to get on the hype train or you're going to get left behind. Obviously we get a lot of that with AI, but we had it not so recently or not so long ago with cryptocurrency. I don't know how far down Bitcoin is now. I really start with how am I going to remain calm, cool, and collected? There's a way to kind of filter out information in advance because of course the amount that you're overwhelmed with information contributes to all these other problems. That's called critical ignoring. I wrote a column about that. I was like, "This is the most important skill you need for 2026." So there are a lot of things that you can use, but step one is don't get sucked in by the hype. The important asterisk on that assertion is all of us are going to get sucked in by somebody's hype at some point.

George Jagodzinski (02:52):

Now, if Chris is the guy telling you to check your excitement, Oliver Mitchell's the guy who has to do it with real money on the line. Oliver's a robotics investor. He wrote a whole field guy on building in the age of robots and AI, and he watches founders fall in love with the shiny thing all the time.

Oliver Mitchell (03:07):

Founders that got attracted to shiny objects got attracted to the technology, but they never asked, "Well, what problem am I really solving?" And they never went to the toolbox to say, "Well, what is the best tool to solve that problem?" No, I want to build an AI company. I want to build a robotics company. But when Mick Mountz went to build Kiva, he did that based upon his experience in Webvan, a huge dot-com bust, the first sort of online grocer because their fulfillment centers were beautifully built and really expensive, but really inefficient. They were taping $20 to every box that went out there and he said there must be a better way.

George Jagodzinski (03:45):

What problem am I actually solving? In a world screaming at you to adopt everything right now, the edge is knowing what to tune out. Okay, onto big thing number two. So once you've cut through the noise and decided AI actually belongs somewhere in your business, what does it do to your people? Because that's the fear, right? That's the conversation happening at every water cooler in America. And the best framing I heard all year was from Denise Hemke. Denise is the chief product officer at NEOGov. They build software for the public sector, the people who serve the people. And she doesn't talk about AI replacing anybody. She talks about super workers.

Denise Hemke (04:18):

AI made me a super worker, that I could create all this content in a way that I don't have the skills to do otherwise. And so taking that same idea of how do you equip an individual with these super skills, that's what we're doing in government, right? Kind of putting a cape around their neck to make them a super worker.

George Jagodzinski (04:38):

A cape around their neck, but, and this is the part I want leaders to hear. She was really clear that a super worker still has to bring the judgment. More isn't the only goal.

Denise Hemke (04:48):

Judgment becomes more and more critical in this world of AI because it will become easier and easier to just push out more and more is not always better. And so, we've been heavily focused on AI and we're doing that in a number of different ways. I mentioned smart job recommendations a moment ago. There is a real need in government to get people into the seat, especially in what I would say are these really hard to fill roles. That is certainly challenging. If you look at the number of applicants overall, the number of applicants hasn't gone up. Yet, if you dig into the data, most of those applicants are going to the jobs that frankly are already getting enough applicants.

George Jagodzinski (05:33):

More is not always better. That lands even harder when you think about how these tools actually show up in your day-to-day. Jeff Cohen spent years inside Amazon as their ads evangelist, watched the business go from 37 billion to over 60 billion. And they'll tell you, you can't just hand the keys to the AI. You've got to stay in the seat.

Jeff Cohen (05:49):

So you have to participate in them, but can you add some layer of intelligence to it where you're still maintaining your budgets, you're managing the return on investment that you're looking for, you're taking the cross-functional output of what's happening and bringing that in to give it additional context.

George Jagodzinski (06:09):

Participate, but add your layer of intelligence on top. Whether it's a recruiter in government office or a marketer running ad spend, the pattern's the same. The AI does the reps, the human brings the judgment, which brings me to big thing number three. And this is the one that gets ignored right up until it bites somebody, governance. I know. I can feel half of you reaching for the skip button because when leaders hear governance, they hear bureaucracy, they hear slow, they hear the department of no. Alec Crawford completely flips that. Alec ran risk on Wall Street, started a risk management job on January 1st, 2008, talked about jumping into the deep end, and now he builds AI safely for regulated companies. He told me a story about what happens when you skip governance. Somebody rolled out AI across their whole company, opened it right up, and on day one-

Alec Crawford (06:55):

Literally the first day someone says, "How much money does my boss make?" Finds out the correct numbers, not only his boss, but the entire management team, "Hey, here's how much money they make." Within seven hours, the legal department had shut down that AI effort, and that is a failure of governance, meaning data governance. Right? Instead of saying, "Well, when Alec logs in, Alec can only see the data he's supposed to in SharePoint." They just open it up wide. So what we do is we maintain what's called permission awareness. So it doesn't matter if I'm using Salesforce through AI, through my own AI, or looking at SharePoint or checking my emails or whatever, I can't see the CEO's emails. I'm not going to get an answer to the question that says, "How much money does my boss make?" So that actually speeds things up because otherwise AI is terrible on its own with cybersecurity and governance. You need to have a layer around it to control that.

George Jagodzinski (07:51):

Seven hours. And you notice what he said at the end there, doing it right actually speeds you up. That's the whole reframe. Governance done well isn't the brakes, it's the headlights. The way I put it to Alec was most companies are running through a dark obstacle course with the lights off, and this is the thing that lets you see the obstacles and get to the other side faster. But the biggest thing he left me with wasn't about safety at all, it was about your data and whether you're about to hand your single biggest advantage to somebody else.

Alec Crawford (08:17):

You should actually keep all your own data, use your own AI to do the analysis, which is the analysis that you want. That's going to be the differentiator between winners in AI and losers in AI over the next few years. Do you have your own proprietary data that other people do not have? Because if other people have your data, then it's not that valuable anymore.

George Jagodzinski (08:36):

That's your mote, your proprietary data plus the wisdom you've built up around it. That's the thing nobody can copy. Give it away and you're just renting your own advantage back from somebody else. So cut the noise, turn your people into super workers, own your data, which leaves the biggest topic for last of all, the one that decides whether any of this actually works.

(08:54):

Execution. Here's a stat that stuck with me all year. Kevin Ertell got so obsessed with why smart strategies keep failing that he interviewed 62 operators, over a thousand years of combined experience, and he wrote a book on it and his conclusion isn't about technology or budgets or the perfect slide deck.

Kevin Ertell (09:12):

Ladder of abstraction is this concept by a linguist from the 1930s, Hayakawa, and he came up with this idea where he said language kind of works in these different levels of abstraction and people in different areas talk about it in different heights, for lack of better word. He calls it a ladder. His example was in the farm world basically. He said executives or stock traders or whatever, they might be talking about agriculture or livestock sort of thing. They'd use these sort of words, but if you go all the way to the farm, they're talking about the cows or even like Bessie. There's this very specific language when you're closer to where execution's happening and there's a strategic language that happens in boardrooms where it's a shortcut for some broader view. His point was, if you want clarity, you have to work your way up and down that ladder.

(10:01):

The farmer person can't be just talking about Bessie to somebody who's talking about a wide scale asset investment across livestock. There has to be a connection and the opposite is also true. People at the very top level can't be talking about strategy at a level that doesn't make any sense for someone like me who was on the shop room floor. You have to make that connection constantly go up and down the ladder. And when you do that, you're able to keep people aligned to the vision. And to your point, the vision can travel the hallways because you're moving the language back and forth so that people get the big picture at the same time they understand the details.

George Jagodzinski (10:39):

That gap between the language in the boardroom and the language on the shop floor, that's where strategy goes to die. Kevin's fix is beautifully simple. Make the right thing the easiest thing to do. If the important thing is also the hard thing, it won't happen. Curt Miller from the private equity turnaround world says it a different way, you cannot cost cut your way to prosperity. It's not about being best in class overnight. It's about being a little bit better than you were.

Curt Miller (11:04):

There's an awful lot of money to be made from taking a company that's really bad and making them only slightly less bad.

George Jagodzinski (11:15):

There's definitely truth in that, man. I love that.

Curt Miller (11:20):

I took that to her. I'm like, "Yeah, I think you're right. We don't need to be best in class. We just got to make continuous improvement here," was his point. It wasn't like, "We don't need to be best in class. We only got to be better than what we bought it at."

George Jagodzinski (11:31):

So there you go. Four things. Learn what to ignore, turn your people into super workers, own your data and execute like it's a human-centric game because it is. Now, if you've listened to this show before, you know I end every single episode with the same question. In your life, in your career, what's the best advice you've ever received? And when I stacked all the years answers up next to each other, they told the same exact story we just walked through. Not one of them is about technology.

Denise Hemke (11:57):

I think it is that feedback is a gift. When somebody gives you feedback, to say thank you. I think oftentimes when we hear feedback sometimes it can put us on the defensive. And instead, looking at that and saying, "What part of this is true? What part can I do differently? I believe the day you stop learning is the day that you are dead."

Jeff Cohen (12:16):

Always be truthful and honest about the mistakes that you make. Listen, you're going to always make mistakes. Mistakes are part of how you're going to grow. It's more about learning from the mistake that you made. And by the way, if I had known that you knew that you made that mistake and you lied to me and you covered it up, I'd fire you. Be open, be honest. Failure is not a bad word.

Christopher Mims (12:39):

It was the most basic advice that I got from my college mentor at the very, very beginning of my career. What you should do in life is whatever's at the intersection of what you're good at and what you enjoy. And it was just so practical. It wasn't like follow your dreams. Her underlying message was be of service and you will always, A, be employed and B, feel a sense of purpose.

Oliver Mitchell (13:02):

Just spend time with the people that you love. There's a great Warren Buffett interview and he said he knows a lot of extremely wealthy people in the world, but the people that are happiest are the people that spend time with their families.

George Jagodzinski (13:16):

Relax and do good work. Feedback's a gift. Own your mistakes. Spend time with the people you love. That's the whole game right there. All the AI in the world doesn't change a word of it. Catch you next time. Thanks for listening to Evolving Industry. For more, subscribe and follow us on your favorite podcast platform and pretty pleased drop us a review. We'd really appreciate it. If you're watching or listening on YouTube, hit that subscribe button and smash the bell button for notifications. If you know someone who's pushing the limits to evolve their business, reach out to the show at evolvingindustry@intevity.com. Reach out to me, George Jagodzinski on LinkedIn. I love speaking with people, getting the hard work done. The business environment's always changing and you're either keeping up or going extinct. We'll catch you next time and until then, keep evolving.