Last week, I saw an image online that perfectly captures where we are with AI right now. It showed ChatGPT telling a user, “Oh yeah, that mushroom is totally edible,” followed by, “You’re right, it’s not—would you like to learn more about poison mushrooms?” when the user ends up in the hospital.
Funny, yes—but also revealing.
It’s a reminder that while AI can produce an answer, it can’t judge whether that answer is right. And that difference matters more than ever.
Over the past year, many companies replaced hundreds of workers with AI. But now, we’re seeing a reversal—organizations quietly bringing people back to do the work that AI couldn’t quite get right.
Why? Because AI makes mistakes that are hard to catch unless you already know the right answer.
And that’s not going to change anytime soon. Large language models don’t understand the world—they predict the next most likely word. That’s what makes them fast and flexible, but also what makes them unreliable without human oversight.
Used well, AI can draft reports, summarize data, or generate creative ideas in minutes. But it still needs people to check the work, connect it to reality, and make the final call.
This is good news for experienced workers.
Every time I start working with a new client, people on the floor worry that AI will take their jobs. But what actually happens is the opposite. The workers who learn how to use AI become more valuable.
They stop spending time on routine tasks and start focusing on the exceptions—the complex cases where experience and judgment matter most.
An employee who can use AI to speed through 80% of their workload and then apply judgment to the tricky 20% becomes irreplaceable.
The key isn’t coding. It’s communication and critical thinking.
AI tools are language-based, not code-based. If you can explain what you want clearly—in plain English, French, or Spanish—you can use them.
That means your domain experts, your managers, and your frontline teams already have what it takes. They just need confidence and structure.
Here’s how to build that:
Start small, but start fast.
Pick one everyday task—emails, KPI summaries, report drafts—and introduce AI there. Quick wins build momentum.
Make experimentation safe.
Let people try prompts, fail, laugh, and learn. The goal isn’t perfection; it’s familiarity.
Pair AI with human review.
Don’t just use AI—evaluate it. Ask what worked, what didn’t, and why. That’s how you develop real oversight.
Empower your curious people first.
Find the naturally inquisitive ones. Train them, then let them coach others.
Keep it practical.
Tie training to real business needs—logistics, reporting, customer service, whatever your team actually does.
There’s a popular idea that AI will give younger, tech-savvy workers an edge. But in reality, it amplifies the value of judgment—the kind that comes from years of experience.
AI can make anyone faster. But only people can decide what’s right.
So the real competitive advantage isn’t having the most AI tools—it’s having the most capable humans using them wisely. Because the future isn’t one where AI replaces people. It’s one where people who know how to use AI replace those who don’t.
AI will keep getting cheaper and faster. Answers will keep getting easier to generate. But judgment—the ability to tell good answers from bad ones—will remain rare and valuable.
If you’re leading a team, don’t wait for the perfect plan. Start small. Start this week. But start.
Because in this new era, the question isn’t if AI will change your work—it’s how fast you and your team can adapt to make it work for you.
In the age of AI, answers are cheap. Judgment is not.