AI Readiness Self-Assessment

Most healthcare and life sciences organizations know AI matters. Fewer know where to start, what's actually ready, or what will break when they try to move from pilot to production.

This self-assessment is a practical diagnostic for executive leaders. It covers the areas where AI initiatives most commonly stall, and helps you identify specific gaps before they become expensive problems.

The assessment covers:

• Use-case clarity and prioritization

• Data readiness and context gaps

• Workflow fit and integration risks

• Decision governance and boundary awareness

• Decision auditability and defensibility

• Production reliability and decision monitoring

Most organizations find the first three sections manageable. Sections 4 through 6 surface the gap that almost no one has examined: whether the decisions your AI produces are governed, auditable, and defensible — not just whether the model performs well.

After completing the assessment, you're eligible for a free 1-hour review with Dr. Amit Shah to walk through your results and identify practical next steps.