The #1 thing you can do to safeguard your career right now? Invest 1 hour per day learning, experimenting with, and using AI tools. One. Hour. I know that sounds dramatic. But I've been recruiting for 30 years. Which means I'm old enough to have watched these tech waves roll through ... dot-com, mobile, social, and more. And here's what I've seen every single time: the people who are last to jump on the adoption curve often don't make it. Management Teams do the math. They look at the cost of driving behavior change in someone who's resistant ... and decide it's easier to just hire someone who already gets it. I'm no tech genius. Yet I can assure you the tools are far easier to use than you might think. You need not become an expert. But by now, it's clear that AI is not going away. Becoming proficient is the single best thing you can do to protect your (current) job & your (future) career. And if you happen to become excellent at it? Perhaps even enjoy it? Then, position yourself as an AI Champion within your department, your team, your company. You'll be seen as a leader. Looked to for guidance & expertise. 1 hour per day. That's it. p.s. If you're currently not working, I'd up it to 2 hours.

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

My first job out of grad school was at Intuit ... makers of QuickBooks and TurboTax. I had no idea that what I learned there would be the single most useful lesson for leading through AI ... 30 years later. Here's what happened. Intuit's co-founders, Scott Cook and Tom Proulx, had a problem. They'd built Quicken, personal finance software they thought was intuitive. Customers said it was great in surveys. But support calls kept flooding in. Surveys lied. Focus groups lied. People told Intuit what they thought Intuit wanted to hear. So Scott & Tom invented something radical. They called it "Follow Me Home" research. The concept was dead simple: Ask a customer buying the software at a retail store if an Intuit employee could literally follow them home and watch them use it. No helping. No guiding. Just observing. (People said yes, kinda bizarre.) What they discovered was brutal. People didn't read the instruction manual. They didn't follow the Setup Wizard. They invented bizarre workarounds that no engineer would have predicted. The gap between how Intuit designed the experience and how people actually experienced it was ginormous. That gap changed everything about how Intuit built products. We adopted the assumption that nobody would ever read the instruction manual. And this should change everything about how you approach AI in your organization. Here's the connection: Right now, most leaders I talk to are doing one of two things with AI. They're either (1) dabbling with tools themselves & assuming their experience reflects their team's reality. Or they're (2) surveying their people ... asking "Are you using AI?" and "Do you find it helpful?" ... and getting polished, useless answers. Both approaches have the same flaw Scott & Tom discovered in the early '90s. People don't do what they say they do. Your marketing director will tell you she's "using AI for content creation." What does that actually mean? Is she pasting entire strategy docs into ChatGPT and blindly publishing the output? Is she using it to brainstorm headlines and then rewriting every one? You have no idea ... and neither does she, really, until someone watches. Literally.

Yesterday delivered the perfect case study in AI investment. ICYMI: Meta's stock jumped 10%. Microsoft's cratered 10%... wiping out $357 billion in a single day. Same week. Same AI spending story. Opposite results. The difference? Meta proved that its AI actually does something. Revenue up 22% year-over-year. Ad clicks up 3.5%. Real conversions, real money. Microsoft? A record $37.5 billion in capital spending. Azure growth slowing. Investors finally asked the uncomfortable question: "Where's the payoff?" This is becoming a common pattern: The AI pilot doesn't translate to profit. But here's the thing... you're not Microsoft. You're far smarter & more disciplined. You don't have billions to burn on infrastructure hoping that something sticks. Which means you can't afford their mistakes. So, here's how to be sure your AI investment actually pays off: (1) Tie every tool to a measurable business outcome before you buy it. Meta didn't just deploy AI... they deployed it specifically to improve Ad Conversions. If you can't name what number moves, don't spend the money. (2) Start with your highest-volume repeatable task. Meta focused AI on their ad-ranking model... something they do billions of times daily. Find your equivalent. Is it Recruiting? Onboarding? Customer response? Service tickets? Pick one thing you do constantly & automate that first. (3) Upskill two people deep, not one. Meta's CFO didn't just report AI results... she understood the architecture changes that drove them. Your AI champions need backups. When one person holds all the knowledge, you've built fragility, not capability. (4) Set a 90-day ROI checkpoint. Microsoft kept spending without clear feedback loops. You won't. Before deploying any AI tool, define what "working" looks like and when you'll measure it. (5) Kill what isn't working. This is the hard one. Microsoft kept doubling down. Meta doubled their GPU usage on what was working (ad ranking)...not everything. Be ruthless about stopping pilots that don't perform.

Half of us are likely to get slammed by snow & ice this weekend. Over 160M people under winter alerts. States of emergency declared. Flights canceled. And still Monday morning, your boss will say: "We need to do AI. Move faster." Here's how I'd respond without looking lost: 👍🏼 Don't ask: "What do you want me to do with AI?" Ask these instead: - "Are we optimizing for efficiency or revenue?" - "What's the guiding metric? Cost? Speed? Quality?" - "Timeline? 90 days or 18 months?" 👍🏼 Map AI to your real problems Your 48-hour homework: - List your top 5 business problems (cost, bottlenecks, quality) - Pick the ONE with measurable impact - Example: Customer support takes 48 hours. AI triage cuts it to 4. 👍🏼 Show evidence, not PowerPoints Week 1: - Run a pilot (ChatGPT, Claude, n8n, whatever) - Pick something you control - Track before & after Week 2: - Email: "Tested AI for [X]. Cut time by [Y]. Next steps: [Z]." 👍🏼 Here's what your boss/board actually want 1. You understand the business problem (not AI hype) 2. You're testing something real now 3. Data, not theory Do this next: - Book 15 minutes: "To validate priorities before we invest" - Pick ONE process to test - Report back with numbers Stop strategizing. Start testing. Stay safe this weekend, Jeff