Four out of five organizations are running AI training. Three out of five still report an AI skills gap. The training is happening; the gap isn’t moving. That isn’t a quality failure — it’s a targeting failure.
This episode works the argument from chapter two of AI Empowered: the three dominant responses to the AI collaboration gap — education, prompting technique, and change management — each address something real, and each aims at the wrong layer. The live element is a Microsoft field experiment with 388 employees at a Fortune 500 retailer, published this spring, where everyone got the same AI tool and only the structure around its use was varied. The structured behavioral protocol was associated with *lower* document quality and substantially less work finished. Partnership training that reframed AI as a thought partner was associated with higher quality — but only at the top of the distribution, and the authors are candid that their belief-change result likely reflects carry-over rather than the training itself.
Also covered: why the social cost of AI adoption (a measured nine percent competence penalty from peers, twenty-six percent for women engineers evaluated by male non-adopters) is a barrier no communication plan reaches, and what turns up when you go looking for a product that teaches the layer underneath — trust calibration, knowing when to override, what you personally bring that the model can’t generate.
The question to stop asking is “have our people been trained.” The question to start asking: when someone on your team opens an AI tool, what do they believe their job is in that exchange?
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This show extends the book AI Empowered: The Psychology of Extraordinary Human-AI Collaboration. Read the first chapter free at https://aiempoweredbook.com, or get the book on Amazon.
Aaron Douglas runs Auspicious, a fractional marketing and AI empowerment practice.