I Call Agism: What We Get Wrong About Training for AI Adoption
At a recent event on the future of skills, I heard a leader in training and change management at a large organization make a sweeping generalization:
The younger workforce adopts AI with much less friction than the older generation.
I get it. Generational dynamics are always at play in the workplace. But this framing? It was too simplistic and, frankly, counterproductive. No wonder their adoption rates are lower than target.
This isn’t just about calling out ageism (though let’s call it what it is). It’s about how these kinds of over-simplifications undermine real, lasting change.
Here are two big takeaways from that moment:
1. Facile Trust vs. Thoughtful Reluctance: Two Sides of the Same Coin
When it comes to adopting new technology, both blind enthusiasm and skepticism are very human and both carry risk.
Facile trust can lead to uncritical use of AI tools, skipping essential layers of human judgment and oversight.
Reluctant distrust can spotlight usability issues, training gaps, or deeper misalignments that need to be addressed before meaningful adoption is possible.
The goal shouldn’t be to push everyone toward blind adoption. It should be to create informed engagement. Shortcut diagnoses of what is driving resistance erode empathy and, in doing so, sabotage adoption efforts. Change doesn’t happen in spite of skepticism—it happens through it.
2. Change Management Is the Juggling Monkey
In her book Quit, Annie Duke describes a mental model used at Google for framing projects: the pedestal and the juggling monkey. The premise is that every initiative should be approached as teaching a monkey to juggle on a newly built pedestal.
The pedestal is the easy part—systems, tools, and infrastructure that are known and proven feasible.
Teaching the monkey to juggle is the hard part—the feat of engineering, the journey to the unknown, the core obstacle of the initiative.
The problem? We often focus on the pedestal-building and underplan for teaching the monkey to juggle.
In learning and development, we produce more/better content, systems, and skills taxonomies. Important? Absolutely. But none of that guarantees adoption and business outcomes. That’s the monkey.
The real work lies in:
Building trust
Understanding resistance
Creating room for identity evolution
Supporting values shifts and culture change
And no system alone can do that for you.
The Bottom Line
If we want people to adapt to AI—or any technology—we need to respect the human work required to get there.
That’s the juggling monkey. And change management is how we teach it to juggle.
