A data-backed approach to assess AI readiness, from use case identification to data quality to technical infrastructure
A Faster Way to Know What to Tackle First
Assess your readiness across five pillars with a simple 0 to 5 scoring method
Set targets that fit. Not for best practices, but fit-for-purpose for your company
Assign ownership with goals for teams like IT and HR, so readiness is shared
Track progress with a sample dashboard showing holistic progress
BONUS: Unlock our larger suite of Future of Work frameworks
Why AI Readiness Comes First
Stop Guessing at Readiness
"Are we ready for AI?" is hard to answer without a shared yardstick. This framework gives you a score, target, and plan.
Fix the Foundation. Not Just the Model
Data quality is one of five pillars here. The framework shows where it sits next so you invest in the right place.
Make AI Everyone's Responsibility
AI is no longer a niche IT project. Set shared goals across teams so progress doesn't stall in one department.
By 2027, 60% of organizations that fail to prioritize data and analytics governance will also fail to govern AI successfully. This includes the cultural mindsets, actions and team norms that influence how governance is integrated and ultimately sustained across the business over time.
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