Assessments Overview
Key takeaway
Data and AI assessments are structured evaluations that baseline current-state maturity, prioritize improvements, and reduce execution risk. The section includes an AI readiness assessment covering six dimensions from strategy to MLOps, and a broader data and AI readiness assessment. Both use a 1 to 5 scoring scale to show which low-maturity areas to address first.
The Assessments section provides practical evaluation tools to understand current-state maturity, prioritize improvements, and de-risk execution.
Featured Assessments
Next Steps
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Frequently asked questions
What is the difference between the AI readiness assessment and the data and AI readiness assessment?
The AI readiness assessment focuses on whether an organization can move from AI ideas to reliable business outcomes, scoring six dimensions from strategy to MLOps and monitoring. The data and AI readiness assessment takes a broader baseline across business alignment, data foundation, governance, platform, analytics, and operating model. Both use 1 to 5 scores.
Why run a maturity assessment before investing in AI?
Run a maturity assessment before investing in AI to find the foundational gaps that would undermine results. Low scores in areas like data ownership, quality, or governance should be addressed before scaling AI. A baseline also lets you prioritize the highest-value improvements and measure progress when the assessment is repeated.
