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Skilled Incompetence
Why are companies cutting their most experienced employees right when AI is making it harder than ever to find the real problem to solve?
Chris Argyris spent decades at Harvard studying why smart, capable people keep solving the wrong problems. His answer is uncomfortable if you are one of the capable ones.
He found that the people least likely to question their own assumptions are the high performers. He called it skilled incompetence. His logic is simple. If you are good at something, you have usually been good at it for a long time. You have been rewarded, defended, refined, and built an identity on it. So when something goes wrong, you reach for these hard-won skills. Yet, you almost never question the goal, because questioning the goal means questioning the very thing you are best at.
Your competence is real, but the incompetence comes from the inability to see past it.
Skilled incompetence is a bias that compounds with tenure. For companies this means the same long experience produces two things at once: the judgment that makes your most experienced people worth keeping, and the rigidity that gets them written off as outdated.
Now put AI in the mix.
Ask AI a question shaped by your assumption, and it returns a thorough, credible, and well-reasoned answer that confirms your…
