// free audit · 4 min

AI Readiness Assessment

Most AI projects stall between the demo and production — on data access, evaluation and ownership, not the model. Answer 12 questions and see what would block yours.

Progress0 / 12 answered

Use-case clarity

1.Do you have a specific workflow you want AI to improve?

2.Can you measure what that workflow costs today (time, errors, tickets)?

3.Has leadership agreed on what success looks like?

Data readiness

4.Where does the information the AI needs live?

5.Can engineers query that data programmatically today?

6.Do you know which data is sensitive (PII, PHI, financial)?

Team & skills

7.Has anyone on your team shipped an LLM feature to production?

8.Who would own the AI feature after launch?

9.How much roadmap capacity could go to AI in the next quarter?

Evaluation & governance

10.How would you test whether AI output is correct?

11.Do you have a policy for which AI tools and models staff can use?

12.Can you trace and log what an AI feature did for a given user?

Where should we send your report?

Press submit to see your score, your fixes in priority order, and book a free 30-minute walkthrough with a senior engineer.

Answer all 12 questions to submit (12 left).