Create a scale recommendation from pilot evidence rather than adoption anecdotes.
A four-week AI pilot has ended. The team needs a scale recommendation for the steering group, but the evidence is scattered across dashboards, support chat, quality review, and champion notes. Sort evidence by decision: usage, value, risk/quality, friction, then recommend the next scale move. The weak move is to summarize sentiment: "people liked it and usage was high." That ignores whether ordinary users can repeat the workflow safely. Step 1 Usage: 31 of 40 pilot users tried the workflow; 19 used it at least three times. Usage shows exposure and early trial, but it does not prove value or ability.…
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