A practical framework to select, run, and evaluate AI pilots using a value hypothesis, risk assessment, data readiness checklist, governance guardrails, and scaling criteria.
Data Readiness Checklist for AI Pilots. Short, actionable items to confirm you can run a timeboxed pilot. Data sources identified: List each source and owner. Access path: Confirm where data will be extracted from and who grants access. Sample availability: Can you get a representative sample (weeks of data) within...
Interactive checklist and rubric to select, assess, and record readiness for AI pilots across value hypothesis, data readiness, risk, governance, operational feasibility, and scaling criteria.
Interactive checklist to assess value hypothesis, data readiness, deployment pathways, governance, owners, and scaling readiness before launching an AI pilot. Capture evidence, owners, and a simple readiness score to support decisions and follow-up.