AI-Readiness Checklist: Is Your Clinical Trial Data Environment AI-Ready?

Preparing for AI in clinical research requires more than new technology — it depends on strong data foundations, clear governance, and thoughtful change management. Many organizations underestimate how much existing workflows, documentation practices, and integration points influence AI readiness. This checklist breaks down the essential components teams should evaluate, from data quality controls and metadata consistency to cross‑functional alignment and training needs. It also helps identify gaps that commonly slow down AI adoption, offering a practical way to assess whether current systems and processes can support reliable automation and model‑driven insights.

Leaders and operational teams can use this guidance to understand where they stand today and what steps will build a more supportive environment for future AI initiatives. Access the full checklist to review each readiness category and plan next actions with greater clarity and confidence.