The technology is rarely what kills an AI rollout, resistance from the people expected to actually use it is. Change management deserves as much planning as the technical deployment itself.
Employees asked to adopt a new AI tool are often quietly wondering whether it’s the first step toward replacing their role. Our coverage of the real gap between company AI framing and worker experience of layoffs shows why vague reassurance doesn’t land, being specific and honest builds far more trust than avoiding the topic.
A tool designed without input from the people doing the actual work tends to miss real workflow details that only show up in daily use. Bringing in a few actual users during the scoped pilot phase, not just after rollout, catches problems while they’re still cheap to fix.
Generic “how to use AI” training lands far less effectively than training built around the specific tasks people will actually use the tool for. Show the exact workflow it changes, not a general demo of features.
Concrete, specific examples of the tool saving real time build more organic adoption than a mandate ever will. Our guide to measuring agent ROI covers the metrics worth tracking and sharing back. See McKinsey’s own research on enterprise AI adoption.
