The organization has AI licenses, experiments, and enthusiastic users, but adoption is uneven and measurable business impact remains limited.
What's actually happening
AI programs commonly measure access and activity while ownership, workflow selection, capability, quality controls, governance, and business measures remain unclear.
The promise
Diagnose the organizational constraint preventing AI from improving a real workflow, output, decision, or customer outcome.
How the tool works
Score the system
Assess business ownership, use-case clarity, workflow integration, human capability, quality/governance, and outcome measurement.
Find the constraint
Identify the weakest enabling condition — not the most visible technology complaint.
Run a proof
Choose one 30-day workflow experiment with an owner, baseline, output-quality standard, and measurable result.
Tangible output
An enablement profile, primary constraint, prioritized workflow opportunity, and 30-day proof plan.
Use it in 10 minutes
Ask six leaders to independently identify the business owner, workflow, quality standard, and outcome measure for the same AI initiative. Compare the answers.
Use it with your team
Score each enablement dimension using evidence, resolve scoring gaps, and select one cross-functional constraint to address first.
Common misuse
Turning the audit into a technology inventory, grading employees, treating all workflows as equally suitable, or promising ROI before establishing a baseline.
Why it matters
- Concentrates investment on the condition actually limiting value.
- Connects AI adoption to workflow and business outcomes.
- Creates a shared agenda for executives, managers, users, and technical partners.
Next step
At a glance
Type: Organizational diagnostic
Family: AI-Enabled Work & Organizational Capability
Status: Free now · Phase 1
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