AI Adoption
The process of getting people in an organization to actually use AI tools — not just installing them. Most AI adoption failures aren't technical failures: the tools work, but people don't change their habits, don't trust the outputs, or weren't involved in the decision. Successful adoption requires genuine usefulness (not just novelty), training, support, and often visible backing from leadership. The hardest part of enterprise AI is almost always adoption, not the technology.
In practice
Your team starts using Claude for meeting summaries. A month later, half the team has stopped using it. AI adoption is the gap between "we have access to this tool" and "people actually use it consistently and get value." Getting adoption right means training, real use cases, and visible wins early.
Related concepts
Where AI Adoption shows up
4 articlesMost companies think AI adoption is a switch you flip. It isn't. It's a progression — six distinct phases, each unlocking capabilities the last one couldn't. Here's what they are, what separates them, and which phase you're probably in.
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