| name | aipom-initiative-readiness-review |
| description | Review one AI initiative across value, economics, dependencies, workflow, context, evaluation, governance, controls, capability, and recovery before a material decision. |
| type | workflow |
| category | cross-category |
| phase | 3 |
| status | active |
| operating_level | ["portfolio","product-team","initiative"] |
| audience | ["CPO","CTO","Product Operations","Product Manager","Team Lead","Engineering","Finance","Operations","Legal","Privacy","Security","Risk","AI Governance"] |
| best_for | ["Launch or scale decisions","Increasing autonomy or sensitive-data use","Resolving conflicting readiness claims"] |
| evidence_required | ["Bet outcome and economic evidence","Architecture context data and evaluation artifacts","Accountability controls and incident readiness","Adoption capability and operating evidence"] |
| produces | ["Initiative readiness profile","Critical gaps and constrained decisions","Proceed constrain remediate pause or stop recommendation"] |
| assessment_questions | ["STR-02","STR-03","STR-04","POR-02","POR-03","POR-04","WFL-03","WFL-04","WFL-05","CTX-01","CTX-02","CTX-03","CTX-04","CTX-05","EVAL-01","EVAL-02","EVAL-03","EVAL-04","EVAL-05","GOV-01","GOV-02","GOV-03","GOV-04","GOV-05","CAP-01","CAP-02","CAP-03"] |
| maturity_move | {"from":"emerging","to":"repeatable"} |
| estimated_time | 2-4 hours across preparation and review |
| group_size | 5-14 |
| depends_on | ["aipom-bet-charter","aipom-economic-case-builder","aipom-platform-dependency-audit","aipom-evaluation-strategy-advisor","aipom-accountability-charter","aipom-risk-control-incident-playbook"] |
| combine_with | ["aipom-investment-stage-gates","aipom-operating-model-design-sprint","aipom-production-evidence-review"] |
| sources | ["https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-ai-rmf-10","https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence"] |
AIPOM Initiative Readiness Review
What Is It
Integrate evidence for one AI initiative before a material decision such as validation, limited operation, launch, scale, sensitive-data use, or increased autonomy. Keep initiative readiness separate from organization-wide maturity.
Why Use It
Strong model results or a completed governance checklist can conceal weak economics, context, workflow, recovery, or accountability. This review applies profiles and critical-gap logic rather than a compensating average.
When to Use It
Use at material investment gates and after significant model, data, workflow, vendor, autonomy, incident, or jurisdiction changes. It supports accountable decisions; it is not legal, safety, security, privacy, or regulatory certification.
What It Produces
- Scope, decision, evidence, and confidence ledger
- Readiness profiles across value, dependencies, workflow, context/data, evaluation, governance/controls, and capability/operation
- Critical gaps, disagreements, and constrained decisions
- Proceed, proceed with constraints, remediate and re-review, pause, or stop recommendation
- Owners, evidence conditions, expiry, and next review
Who Should Participate
Include the accountable decision owner, Team Lead, Product Manager, Product Operations where present, technical and operational owners, finance, affected-user or domain representation, and legal, privacy, security, risk, or governance specialists proportionate to consequence.
Evidence to Bring
Bring bet and outcome evidence, economics, dependencies, workflow measures, context and data readiness, behavior contract, evaluation set and scorecard, accountability, autonomy boundaries, controls, incidents, adoption, capability, and rollback evidence.
How to Do It
- Define the exact decision, scope, population, environment, autonomy, jurisdictions, and consequence.
- Separate the decision under review from any lower-exposure interim motion that may continue while prerequisites are remediated.
- Load supplied artifacts into a context ledger; ask only for decision-changing gaps.
- Profile strategic value and economics, including alternatives and uncertainty.
- Profile platform, data, context, workflow, and operating dependencies.
- Profile behavior, evaluation coverage, thresholds, production signals, and uncertainty.
- Profile accountability, authority, controls, escalation, rollback, incident response, and specialist decisions.
- Profile user adoption, operator capacity, role competence, support, and change readiness.
- Preserve disagreements and distinguish evidence, assumptions, and required approvals.
- Identify critical gaps and state which actions they constrain before any summary.
