Hello AI Enthusiast,
This is a short preview of our latest blog post. For the full version, click here.
The gap between "active users" and actual adoption
Your company has an AI tool. The dashboard shows active users. But nobody is quite sure what those users are actually doing, or whether it matters. Sound familiar?
This is where most corporate AI programs sit right now. Not failing exactly, just... not moving. And the reason is almost always the same: the rollout skipped a few critical steps.
There's a pattern to what actually works
Working across many different organizations, we've found that successful AI adoption tends to follow a consistent shape. The same things unblock progress in roughly the same order. It's not about which tool you pick or how big your launch was.
The insight that surprises most people? It starts before any training happens. Running a short baseline survey across all employees, before designing anything, changes the quality of everything that follows. Most companies skip it because they think they already know what employees need. That picture is almost always incomplete.
The teams that seem enthusiastic often have a narrower range of actual use cases than expected. The teams that seem resistant often have specific, solvable concerns that nobody has addressed directly.
There's more to the story
The full post walks through each phase in detail: what leadership actually needs to do first, why generic training fails where role-specific training sticks, and how to build lasting capability after the formal program ends.
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We'll be back with more AI tips soon!
