Genuine question for people working inside organizations doing AI rollouts: when your leadership says “we’ve achieved X% AI adoption,” what does that actually represent? I’ve been embedded in tech strategy work across a few orgs here in the Phoenix area and the number almost always means one thing: the percentage of employees who have logged into an AI tool at least once in the last 30 days. That’s it. That’s the metric that gets reported to the board, celebrated in all-hands meetings, and used to justify continued investment. It tells you almost nothing about whether AI is changing how work gets done. The more interesting question and the one almost nobody has a clean answer to, is what the proficiency distribution looks like. Not “are they using it” but “how well, across how many use cases, with what sophistication.” Because the research is pretty clear that there’s an enormous gap between what a basic user extracts from AI tools and what a power user extracts. Same tools, same access, completely different outcomes. I keep waiting for the conversation to shift from “how many people are using AI” to “how well are they using it.” Is that happening at your orgs or are we still stuck on the adoption number? submitted by /u/Front-Vermicelli-217
Originally posted by u/Front-Vermicelli-217 on r/ArtificialInteligence
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