AI Adoption
5 counter-intuitive lessons from AI training and coaching
Five lessons from supporting dozens of teams through AI activation: the opposite of what the market keeps promising.
This article is the core of the methodology used in AI Activation Sprints. In five lessons, it describes what I see repeat from one team to the next, and what separates teams that move into action from teams that stay stuck in exploration.
The market promise vs. the field
The AI training market sells a simple promise: more tools, more productivity. My coaching work tells a different story. Teams that successfully integrate AI into daily work are not the teams that watched the most demos. They are the teams that agreed to question how they produce before touching a single tool.
What follows are five observations repeated in the field. Each one is counter-intuitive. Each one can be tested.
1. The problem is almost never the tool
[Migration in progress - full article body to be brought across from the original Notion source.]
2. Training does not create adoption; guided practice does
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3. The best use cases come from the business, not from IT
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4. ROI is measured in hours returned, not tools deployed
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5. A team’s autonomy is not trained; it is revealed
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