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AI Readiness Assessment

12 questions across the four dimensions that actually predict whether AI projects ship: data foundations, team capability, process maturity, and strategic alignment. 3 minutes. Tiered score and a specific recommendation for what to do next.

0 of 12 answered

  1. 01

    Data foundations

    How is the data AI would need today stored and accessed?

  2. 02

    Data foundations

    How clean and consistent is your operational data?

  3. 03

    Data foundations

    If a new AI tool needed your product or brand context tomorrow, could you hand over a documented source of truth?

  4. 04

    Team capability

    How comfortable is your team using AI tools for daily work?

  5. 05

    Team capability

    Do you have engineering resources to maintain production AI systems?

  6. 06

    Team capability

    Is there a clear owner on your team for AI initiatives?

  7. 07

    Process maturity

    How well-documented are the workflows you'd want to automate?

  8. 08

    Process maturity

    How repeatable are the workflows you run today?

  9. 09

    Process maturity

    Can you measure the current cost (hours, dollars, error rate) of the workflow you'd automate?

  10. 10

    Strategic alignment

    Is there a specific, prioritized AI opportunity your leadership has aligned on?

  11. 11

    Strategic alignment

    Is budget allocated for AI initiatives this year?

  12. 12

    Strategic alignment

    How is your leadership thinking about AI risk and governance?

12 questions left.

Why these four dimensions

Most AI initiatives fail before they start — not because the technology isn't ready, but because the team or the data or the process or the strategy isn't. We've watched the same four gaps kill engagements again and again, so this assessment measures all four and scores them independently.

Data foundations— where your operational data lives, how clean it is, whether it's accessible. Without this, any AI tool is building on sand.

Team capability — whether your people have the fluency to use, maintain, and extend what gets built. Custom AI tools fail fastest when nobody on the team owns them.

Process maturity— how well-defined and repeatable the workflows you'd automate actually are. You can't automate a process that doesn't exist consistently.

Strategic alignment — whether leadership has a prioritized view of where AI fits. Unfocused exploration eats budget; focused execution compounds.