Identify AI Data-Readiness Gaps

#CONTEXT:
Create a readiness-gap register for the data needed by the supplied AI use cases. Assess documented evidence only; do not inspect, move, transform, or change live data or access.

#INPUTS:
- Candidate use cases with required inputs, outputs, and decision boundaries: [CANDIDATE USE CASES]
- Documented data sources, locations, formats, lineage, and refresh patterns: [DATA SOURCES]
- Supplied completeness, accuracy, consistency, timeliness, representativeness, and test evidence: [DATA QUALITY EVIDENCE]
- Current access rights, permission records, approved purposes, and access owners: [DATA ACCESS AND PERMISSIONS]
- Applicable privacy, security, classification, retention, and residency requirements: [PRIVACY AND SECURITY REQUIREMENTS]
- Budget, timing, capacity, technical, policy, and regulatory constraints: [CONSTRAINTS]
- Named data owners, stewards, and documented decision rights: [DATA OWNERS]
- Technical, governance, vendor, process, and people dependencies: [DEPENDENCIES]
- Supplied readiness and validation measures, thresholds, and measurement owners: [SUCCESS MEASURES]

#INSTRUCTIONS:
1. For each use case, map every required data element to its supplied source, owner, lineage, quality evidence, access status, approved purpose, privacy classification, security control, retention rule, and dependency.
2. Label missing, conflicting, expired, inaccessible, unmeasured, or unauthorized facts Unknown. Do not treat source existence as proof of quality, permission, suitability, or feasibility.
3. Create a readiness-gap register. Classify each gap as availability, quality, lineage, access, privacy, security, governance, ownership, integration, measurement, or dependency.
4. Give the evidence or source basis, consequence, named decision owner, proposed bounded evidence-gathering step, stop condition, and completion evidence for each gap.
5. Distinguish every value as Supplied, Calculated, or Estimated. For a Calculated value, show the formula, units, and supplied operands. For an Estimated value, show a range, assumptions, uncertainty, and confidence score with rationale.
6. Do not invent, infer, or fabricate ROI or return on investment, time savings, cost, feasibility, data quality, access, permission, consent, owner, lineage, control effectiveness, volume, coverage, or technical capability. Unsupported conclusions remain Unknown.
7. If readiness percentages are requested, use a documented formula such as verified requirements met ÷ total documented requirements × 100. Show counts, inclusion rules, range, assumptions, uncertainty, and confidence score; never imply that a score authorizes use.
8. Make privacy, security, and data-access dependencies explicit. Treat unresolved authorization, purpose limitation, sensitive-data handling, retention, or vendor-control questions as stop conditions.
9. Do not infer authorization from source availability, existing credentials, ownership, or a readiness recommendation. Do not automate, purchase, deploy, alter data or permissions, or change a live workflow.
10. A named human owner must approve prioritization adoption before action. A named human owner must approve purchasing before action. A named human owner must approve deployment before action. A named human owner must approve every data or permission change before action. A named human owner must approve every live workflow change before action.
11. Use only authorized company data in an approved AI workspace or approved AI vendor. Minimize the data; redact or omit unnecessary personal, sensitive, or confidential data. Follow company retention and vendor policy.

#RESPONSE FORMAT:
## Data requirement and evidence map
| Use case | Data requirement | State: Supplied, Calculated, Estimated, or Unknown | Source | Owner | Access | Quality evidence | Privacy and security dependency |
|---|---|---|---|---|---|---|---|

## Readiness-gap register
| Gap | Type | Evidence or source basis | Consequence | Named owner | Bounded next step | Stop condition | Completion evidence |
|---|---|---|---|---|---|---|---|

## Calculations and estimates
| Measure | Formula | Supplied operands | Estimated range | Assumptions | Uncertainty | Confidence score |
|---|---|---|---|---|---|---|

## Privacy, security, and data-access dependencies

## Unknowns and human approvals