# AI Product Requirements Document

| Field | Value |
|---|---|
| Product / feature |  |
| Version / status |  |
| Product owner |  |
| Technical owner |  |
| Project owner |  |
| Risk / operations owner |  |
| Last updated |  |

## 1. Executive decision

- Problem and opportunity:
- Proposed product:
- Decision requested:
- Evidence strength:

## 2. Users and current workflow

- Primary/secondary users:
- Buyer, administrator, beneficiary, and risk owner:
- Trigger, task, steps, handoffs, and outcome:
- Current baseline: time, cost, quality, failure, adoption:
- Research evidence and known gaps:

## 3. Goals and non-goals

### Goals

### Non-goals

### Stop conditions

## 4. Why AI

| Option | Strength | Limitation | Decision |
|---|---|---|---|
| Process redesign |  |  |  |
| Rule/search/traditional ML |  |  |  |
| Generative AI / hybrid |  |  |  |
| Human service |  |  |  |

## 5. Scope and user journey

- In scope / out of scope:
- Happy path:
- Ambiguous input:
- No-answer / refusal:
- Partial failure:
- Correction / undo:
- Human escalation:

## 6. Requirements

| ID | Requirement / user story | Priority | Failure severity | Acceptance | Owner |
|---|---|---:|---:|---|---|

## 7. AI behavior contract

- Allowed inputs and source trust:
- Required context and freshness:
- Expected output schema:
- Evidence / citation behavior:
- Uncertainty and refusal:
- Tool actions and authorization:
- Human confirmation and maximum autonomy:
- Prohibited behavior:

## 8. Data, privacy, and governance

- Data sources, authority, purpose, and owner:
- Sensitive fields and minimization:
- Access, tenant isolation, retention, deletion, and audit:
- Training / feedback use:
- Fairness, transparency, copyright, or domain review:

## 9. Success and evaluation

| Type | Metric | Baseline | Target / gate | Segment | Method |
|---|---|---:|---:|---|---|
| Product outcome |  |  |  |  |  |
| Task quality |  |  |  |  |  |
| Safety guardrail |  |  |  |  |  |
| Reliability |  |  |  |  |  |
| Cost |  |  |  |  |  |

- Evaluation dataset and sampling:
- High-risk / long-tail coverage:
- Online experiment:
- Regression plan:

## 10. Non-functional requirements

- Latency / throughput / availability:
- Capacity and budget:
- Observability and traceability:
- Accessibility / localization:
- Fallback, recovery, and portability:

## 11. Release and operations

- MVP learning goal:
- Phase gates and rollout stages:
- Go/No-Go approvers:
- Monitoring, alerts, and sampling:
- Rollback triggers and mechanism:
- Support, incident, and operations owner:

## 12. Dependencies, risks, and decisions

| Type | Item | Impact | Action | Owner | Due / trigger |
|---|---|---|---|---|---|

## 13. Traceability

| User problem | Goal | Requirement | Evaluation | Release gate | Operating metric |
|---|---|---|---|---|---|

## 14. Appendix

- Confirmed facts:
- Labeled assumptions:
- Open questions:
- Decisions and rejected alternatives: