Diagnostic

AI Adoption Readiness Diagnostic

Version 0.1. This framework is actively being refined based on real conversations and use. If you have feedback, please send it to hilary@hilarymason.me.

A practical assessment of where your organization is set up to succeed with AI, and where it's most likely to break down.

48% of organizations now call AI adoption a disappointment. The model is rarely the problem. The organization around it is. This diagnostic looks at six dimensions that determine whether AI adoption will succeed or stall. It takes about 5 minutes.

48%

of organizations call AI adoption a disappointment

60%

of AI projects projected to be abandoned by end of 2026

dimensions this diagnostic assesses

Sources: Stanford AI Index 2026, Gartner forecasts.

Explore the framework

Take the diagnostic, or dive into any dimension directly.

Strategic Clarity

Why your organization actually wants AI, and whether leadership agrees.

Data & Infrastructure Readiness

Whether your data foundation can support trustworthy AI outputs.

Operating Model Fit

Which workflows are ready for AI augmentation and which aren't.

Education & Enablement

Whether people are equipped to work alongside AI in their specific roles.

Change Capacity

Your organization's ability to absorb the pace and scale of AI change.

Governance & Accountability

Ownership, guardrails, and feedback loops for AI decisions.

This framework is open source.

The AI Adoption Readiness framework lives publicly on GitHub. Fork it, adapt it, or use it as-is. The interactive version on this site is one rendering of it. The framework itself is meant to be used.

View the framework on GitHub→

Last updated: June 23, 2026