Evaluate an AI tool before rolling it out: the real-work trial design, the data and privacy checks, and the honest productivity math.
Evaluate this AI tool: {{tool}} (what it claims, for which of our workflows, price, who'd use it). Design: the real-work trial (2 weeks, our actual tasks not demos — the 5 test cases from OUR work, with the current-way baseline timed so the comparison is honest), the quality bar per use case (where must it be right vs where is draft-quality fine — AI tools fail differently than software: confidently wrong; the checking-cost included in the math), the data checks before anyone pastes anything (what goes to whose servers, training-data opt-outs, the client-confidentiality and privacy lines — the not-allowed-in list written BEFORE adoption), the workflow-fit test (does it live where work happens or add an app to visit?), the honest math (time saved minus checking time minus subscription, per user), and the decision: adopt-with-rules / trial extended / pass — plus the usage guidelines one-pager if adopting.
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