Map the real process, test root causes, remove avoidable work, and preserve necessary controls before choosing automation. This governed prompt connects evidence, SOP design, exception handling, pilot results, and measurable outcomes.
TL;DR AI adoption data is not the same as productivity evidence. Licenses assigned, active Copilot users, prompts submitted, tokens consumed, suggestions accepted, and lines of code generated can show that a tool is available and being used. They do not prove that the organization improved revenue, customer experience, end-to-end cycle time, quality, operating margin, or … Explore: The AI Productivity Measurement Trap: Why Token Counts,…
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