Diagnose AI Adoption Value Leakage

Required inputs

Have these details available before following the usage instructions.

• Approved value case, expected value flow, baseline, benefit assumptions, and owners
• Adoption by user and task, workflow integration, throughput, quality, review, rework, exception, and queue evidence
• Policy, incentive, training, data, system, control, and downstream-capacity constraints
• Realized benefit evidence, measurement definitions, comparison period, and known operating changes
• Decision horizon, intervention authority, and acceptable risk

How to use this Skill

When to use:
- AI quality or usage appears promising but realized operational or financial value is weak.
- Teams need to distinguish adoption symptoms from workflow, quality, control, capacity, or measurement mechanisms.

When not to use:
- Generic change-management planning before any operating evidence exists.
- Assuming low usage is the root cause or that more automation necessarily creates value.

Reusable diagnostic method:
1. Map expected value from capability through eligible tasks, use, integration, accepted output, downstream completion, and benefit capture.
2. Attach observed evidence, assumptions, and missing data to every handoff.
3. Reconcile expected and actual volume, mix, cycle time, quality, review, rework, exceptions, capacity, risk, and measurement effects.
4. Separate symptoms from mechanisms and quantify or bound loss where evidence permits.
5. Compare competing mechanisms and specify a discriminating signal for each.
6. Design the smallest intervention hypotheses with owners, guardrails, and observable recovery checks.
7. Decide recover, redesign, hold, stop, or gather evidence without implying implementation.

Expected output:
A value-flow map, leakage-mechanism ledger, evidence-backed loss bridge, competing hypotheses, owner-specific recovery tests, risk controls, and decision view.

Boundaries:
Do not invent adoption, labor, quality, financial, or causal evidence. Process and product owners verify workflow mechanisms; finance verifies benefit and cost interpretation; security, privacy, legal, or compliance reviewers retain authority for consequential controls. Source grounding: AMO-P-000281. Applicable Workflow: AMO-W-000015.

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AI Adoption Value Leakage Diagnosis

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Completion criteria

Complete when the value flow has evidence at each material handoff; symptoms and mechanisms are separated; competing causes and uncertainty are recorded; material leakage is quantified or bounded; and each intervention has an owner, test, guardrail, and decision trigger.