Workers are starting to protect expertise from the agents they are asked to train

Enterprise AI adoption has a people problem hiding inside the workflow charts. If employees believe the agent they are training will later replace them, they have every incentive to withhold the messy expertise that makes automation useful in the first place.

That is why reports of workers hoarding knowledge matter. AI systems need examples, corrections, edge cases, and process context from the very people who may feel threatened by them. A company can buy tools and still fail if the internal trust contract collapses.

The better implementation pattern is transparency: explain what the system will do, what humans will keep owning, and how expertise will be rewarded. Otherwise the agent rollout becomes a quiet labor negotiation disguised as a software deployment.