What's Next: New Assessments

Phase 1 identifies your landscape. Phase 2 asks if you're equipped to respond.

Phase 1: The Landscape

Our three current assessments map where you stand: how exposed your work is to AI, how your organization is adopting it, and what structural barriers prevent you from using it effectively.

Phase 2: The Response

Three New Assessments

Phase 2 shifts from diagnosis to action. These assessments measure whether you and your organization have what it takes to respond to what Phase 1 revealed.

Coming Soon
Am I Set Up to Succeed with AI?

Do you have the tools, knowledge, permissions, and support to act on AI? This assessment measures the gap between AI ambition and organizational enablement.

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Coming Soon
Are We Deploying AI Too Fast?

Is your organization's AI deployment speed calibrated to actual risk? This assessment surfaces the tension between velocity and governance readiness.

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Coming Soon
Is My Data Ready for AI?

Can you access and trust the data AI needs to work? This assessment evaluates data quality, access patterns, and governance fitness for AI consumption.

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The Complete Picture

Phase 1 tells you where you stand. Phase 2 tells you whether you can move. Together, they create a complete diagnostic of your AI readiness.

Phase 1 Finding Phase 2 Question Combined Insight
Phase 1
"Your role is highly exposed to AI automation"
Phase 2
"Do you have the tools and training to adapt?"
High exposure with low enablement signals urgent organizational intervention. High exposure with strong enablement suggests successful transition is underway.
Phase 1
"Your organization's AI adoption is outpacing peers"
Phase 2
"Is that speed calibrated to risk?"
Fast adoption with poor speed calibration means accumulating governance debt. Fast adoption with strong calibration means competitive advantage through responsible velocity.
Phase 1
"Knowledge friction is your primary barrier"
Phase 2
"Is your data ready for AI to use?"
Knowledge friction combined with poor data readiness reveals a systemic information architecture problem. Knowledge friction with strong data readiness points to a training and tooling gap instead.

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We'll send exactly one email when these launch.