Every week, another company announces an AI mandate. Use it for meeting notes. Use it to write job descriptions. Use it to move faster. The directive comes from the top, and then it trickles down through layers of managers and teams, each one interpreting it a little differently.
By the time it reaches employees, “use AI” means something different in every corner of the organization. That inconsistency is a major problem that has little to do with the technology itself. According to a recent KPMG report, the biggest barriers to AI adoption are slow organizational change management and a lack of role-specific use cases — not the tools themselves. And yet HR leaders are expected to bridge that distance with no shared definition of what good adoption actually looks like.
The organizations making real progress are defining what AI use looks like in practice by role, team and even expected behavior. That work falls to HR because adoption depends on people changing how they work, and that requires clear expectations, aligned managers and the psychological safety to experiment.
How vague direction becomes inconsistent execution
When a mandate lacks definition, managers fill in the blanks themselves. One team treats AI as
