It's hard to catch something that keeps moving.
I'll just say it, I find AI overwhelming.
I'm an early adopter. The person who was using ChatGPT before most people knew what a prompt was. I've tested tools, broke things, rebuilt them, and told everyone who would listen that this was going to change everything.
And I was right. It is changing everything. The problem? It won't stop changing.
In the first quarter of 2026 alone, there were over 255 model releases. In February, twelve significant updates dropped in a single month. Gemini, Claude, GPT, Grok, all shipping major upgrades within weeks of each other. By the time you've learned what one tool can do, three more have launched and the one you just figured out has a new version.
So if you feel behind, if your team feels behind, if your entire organization feels behind, you're not imagining it. You are behind. We all are. That's the world we're living in now.
The Numbers Don't Lie
Organizations know AI matters. They're spending shows it. Eighty-eight percent are now using AI in at least one business function. Leaders are actively leading the way, with 85% using gen AI regularly.
But only 51% of workers do.
And it gets even more interesting. Thirty-one percent of U.S. knowledge workers admit to actively working against their company's AI initiatives. Among Gen Z the number is a surprising 41%. More than half of employees say they'd use AI tools without formal approval, and nearly one-third keep their use hidden from employers.
So we have leaders pushing AI from the top, employees resisting or going rogue, and a massive middle where nobody feels competent, in control, or supported.
It's not surprising that 54% of C-suite executives admit that AI adoption is tearing their company apart. And 73% of CEOs report stress or anxiety about their AI strategy.
(Yes, the CEOs are stressed too.)
Meanwhile, only 6% of organizations are capturing meaningful enterprise value from AI. Not 60%. Six.
It's Not a Training Problem. It's a Human One.
There's a natural instinct to just throw more training at it. More workshops. More mandatory lunch-and-learns.
But the reality is that people don't resist AI because they're lazy or afraid of technology. They resist because something deeper is being threatened.
We, human beings, need to feel capable and effective at their work. We need to feel in control of how we do it (some of us need a bit more control than others, just saying). We also need to feel connected to the people around us.
AI can strengthen every one of those needs, or it can destroy them. When a new tool redefines what "expertise" means overnight, when a rigid rollout removes autonomy (a fundamental, innate human psychological need), when collaboration gets disrupted by automation, resistance isn't irrational. It's predictable.
McKinsey's research shows employees are actually more ready for AI than their leaders think. They're already using it. But the gap between experimentation and real, scaled use remains enormous. Gartner predicts organizations will abandon 60% of AI projects that lack AI-ready data.
The speed isn't the only problem. It's the speed plus the human cost of not addressing what that speed does to people.
What Actually Works (Action Steps)
The organizations getting this right aren't treating AI as just another tech rollout. They're treating it as an organizational transition, one that requires as much EQ as technical infrastructure.
- Let people be bad at it. The fastest way to kill AI adoption is to make everyone feel like they should already know what they're doing. Make it safe to be a beginner. Because right now, a lot of your best people are quietly pretending they've got it handled. They don't. Neither do I. That's fine. Create space for experimentation, the performance increase will come later.
- Pay attention to what people do, not what they say. Some employees are already playing around with it, building, pulling peers in to work together. Others are going silent, ignoring AI tasks, or using tools behind closed doors. That's not a policy problem. That's a trust problem. You fix it by making it safe to say "I tried this and it didn't work" without it getting you in trouble.
- Throw out the universal training plan. A senior analyst and a new hire don't need the same onboarding module. They need different things, different pacing, and room to learn in ways that actually match their work. Relevancy is key for adult learners.
- Fix the work before you add the tools. Plugging AI into an already broken process doesn't make it a better process. It makes it an exponentially bad process. Simplify workflows first. Then give AI the repetitive, data-heavy stuff. If you're not rethinking the work itself, you're just automating the mess.
So Who Wins?
Not the organizations that moved fastest. It's the ones that brought their people with them. Honestly, humanely, and with enough humility to admit that nobody has this figured out yet.
I include myself in this. (Especially on Tuesdays, when three new tools drop before lunch.)
The catch-up game never ends. The question isn't whether you're behind. It's whether you're building the kind of organization, or the kind of career, that can keep moving with it.
That's the real difference.
P.S. If you're a leader reading this thinking "this is exactly what's happening at my company," forward this to your team. Not as a mandate. As a conversation starter. That's step one. If you need help with what follows, DM me.
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