You may have seen this one making the rounds this week. It's a well-done analysis from the perspective of one man, who's knee-deep in AI. Even if he's only half right, the implications on your business, your career, and your team are as dramatic as you may think. Worth 10 minutes of your time: https://shumer.dev/something-big-is-happening

This group is a little more in tune with AI than the average manager so I thought I'd ask the question. What do you think most business managers actually struggle with when it comes to the notion of this generation of AI (meaning generative AI, not reasoning and planning models). Is there a fundamental misunderstanding of what it is? Maybe they don't fully understand the implications, or what? Not thinking of the CEO and executive team when I'm asking this, I'm thinking more the middle managers in non-tech companies (you know, the ones that drive the US or NA economies that aren't sexy).

Pinterest just laid off 15% of its workforce to "redirect resources toward AI." Then some of its engineers built a tool to figure out exactly who got cut. Pinterest fired them too. The CEO called it "obstructionist behavior." The engineers say they just used the company's own staff directory. Either way ... the message was clear. We're restructuring. Don't ask questions. Here's the thing. Pinterest's stock is down 20% this year. They're scrambling to compete with Meta & Google on AI-powered ads. And now they're burning trust with the people who survived the cuts. That's the cost of doing AI transformation the wrong way. (Remember: The tech will sort itself out; the "people part" of AI will prove to be the most challenging) So here's the strategic question most leaders aren't asking: When AI automates a process & frees up headcount ... do you cut those roles or redeploy them? Both paths are 100% legit. Path 1: Reduce headcount. You pocket the savings. Margins improve. Wall Street loves it. That's the Pinterest play. Path 2: Redeploy headcount. You move those people into growth roles ... sales, innovation, customer experience. Profits take longer but compound harder. High-class problem either way. But here's what's true regardless of which path you choose ... You can't make that decision until you've proven AI actually works in your operation. You need Pilots that deliver real, measurable results. That's what gives you the credibility (and the data) to go to your Board and say "here's what we're doing with the people this frees up." No results? No leverage. No leverage? No strategic choice. You're just guessing. That's exactly what today's *live* session is about. I'm walking through the "AI Pilot to Profit" framework ... the step-by-step system for going from AI idea to measurable ROI in 6 weeks. Today (2/5) at 1pm ET / 12pm CT / 11am MT / 10am PT Join us live. Here's the Zoom link.

When the opening ceremonies for the 2026 Winter Olympics take place this Friday in Milan-Cortina, the flame will burn bright for athletes who earned their spot. 🔥 But here's the harder truth the cameras won't show: the tryouts that ended in heartbreak. The skaters who practiced for years but couldn't land the triple axel when it mattered. The hockey players who gave everything but still got cut. 💔 They weren't bad people. They just weren't Olympic-ready. Sadly, you have the same people on your team right now. I call them "The Resisters" ... and they're threatening to freeze your AI transformation before it even begins. These aren't necessarily your longest-tenured employees. Tenure has nothing to do with it. I've seen 20-year veterans embrace AI like it's the best thing since direct deposit. And I've watched people hired 20 months ago dig in their heels like they're defending a castle. The Resisters share something deeper than a start-date. Here's what they have in common: 1️⃣ They've built their identity around how they do the work, not what they accomplish. The process is the point. Challenge the process, and you've challenged their very worth. 2️⃣ They see AI as a referendum on their career. If a machine can do it, what does that say about the last decade? 3️⃣ They're skilled at sounding reasonable. "I just want to make sure we're being thoughtful" is Resister code for "I'll slow-walk this until everyone forgets." Here's how to spot The Resisters in the wild: 👀 They ask for "more research" on tools that millions are already using successfully. They volunteer for the AI committee ... then miss every meeting. They find 1 edge case where AI got something wrong & treat it like they've discovered plutonium. 👀 Watch for the person who says "I'm not against AI" and then follows with "but" and 17 reasons to wait. Their favorite season? An eternal winter of delay. Now, here's the part no one wants to talk about: You have to manage them out. Soon. 🚪 Not because they're bad people. Not because they haven't contributed. But because your transformation will die if you don't. And that's no longer an option.

One of our Roundtable members, CEO of a 150-person company, got blindsided. He'd rolled out AI tools companywide. Same training. Same resources. Same deadline. 3 months later? 20% of his team was crushing it. 60% was fumbling along. And 20% hadn't logged in even once. He thought he had a training problem. He didn't. He had a "human" problem. Clayton Christensen's infamous "Adoption Curve" (5 types of people: innovators, early adopters, early majority, late majority, laggards) doesn't just apply to customers buying products. It applies to your employees adopting AI, too. See the bellcurve pix below. Not because they're tech people or non-tech people. Because they're people. This is how humans adopt anything new... from the printing press to cars to smartphones to AI to that weird standing desk trend from 2015. So stop treating your AI rollout like everyone will magically get on board at the same pace. They won't. 👍🏼 Find Your Early Adopters These folks are gold. They're the ones already experimenting with Claude & Gemini on their own time. They're sending you articles about AI. They're asking "what if we tried..." in meetings. Don't wait for them to raise their hands. How to find these 16% of your people? > Ask your managers: "Who on your team is already tinkering with AI tools?" > Look for the people who get excited when things break... because it means they get to figure something out. Then harness their energy. Appoint them your AI Champions. Give them permission to experiment. Have them train their peers. Nothing spreads adoption faster than a trusted colleague saying "let me show you something cool." 👎🏼 Face The Uncomfortable Truth About Laggards Some of your people will be late. That's fine... the late majority just needs more proof & hand-holding. Budget extra time for them. But some people will never get there: "The Resisters" I'm not being harsh. I'm being realistic. A percentage of your team will resist AI no matter what you do. They'll find reasons. They'll create workarounds. They'll slow everyone else down.