AI+ Organization · Reference
Readiness Assessment Worksheet
Baseline readiness across the six framework pillars, align stakeholders, and prioritize next actions.
Assessment Metadata
1. Value (Why)
Prompts
- What is your one-sentence AI North Star?
- What are the top three business priorities AI must support?
- Which metrics will prove improvement in efficiency, quality, and capability?
Checklist
- Leadership aligns on value priorities.
- Success metrics are defined and baselined.
- North Star outcome is documented and shared.
- AI investments map to business strategy.
- Finance is involved in value definition.
2. Use Cases (Where)
Use case inventory
| Use case | Type | Owner | Impact | Effort | Risk | Priority |
|---|---|---|---|---|---|---|
Type options: Automation / Augmentation / Generation / Prediction / Optimization
Checklist
- Use case inventory exists.
- Scoring criteria are defined and applied.
- Top 3–10 use cases are selected.
- Owners are assigned to prioritized use cases.
- Intake process exists for new use cases.
3. Operating Model (How)
Human-AI mode selection
| Process area | Assistive | Co-Pilot | Autonomous | Notes |
|---|---|---|---|---|
| Customer-facing | ||||
| Internal operations | ||||
| Decision workflows | ||||
| Data and analytics |
Checklist
- Future-state workflows are mapped.
- Human-AI handoff points are defined.
- Decision ownership is documented.
- Exception and escalation paths exist.
- End users participated in design.
4. Foundation (What Enables It)
Readiness rating
| Area | Not ready | In progress | Ready | Notes |
|---|---|---|---|---|
| Data quality and access | ||||
| Data governance and permissions | ||||
| AI tools and models | ||||
| Platform and infrastructure | ||||
| API and system integration |
Checklist
- Data sources for priority use cases are validated.
- Governance and access controls are active.
- Tools and models are selected or shortlisted.
- Integration requirements are mapped.
- Minimum viable foundation is defined.
5. Governance (Control and Trust)
Control coverage
| Area | Status | Owner | Evidence |
|---|---|---|---|
| Privacy policy and data handling | |||
| Access control and identity | |||
| Bias and accuracy testing | |||
| Legal and regulatory review | |||
| Audit logging and override |
Checklist
- AI privacy policy is defined and communicated.
- Security review is required before deployment.
- Bias and performance thresholds are defined.
- AI risk register is maintained.
- Audit logging and override mechanisms are active.
6. Execution (How It Happens)
Delivery model
- Framework-driven
- Hierarchical (top-down)
- Pragmatic (bottom-up)
- Hybrid
Role assignment
| Role | Assigned person | Team | Status |
|---|---|---|---|
| Explorer | |||
| Operator | |||
| Architect | |||
| Orchestrator |
Checklist
- Delivery approach is selected and communicated.
- Roles are assigned with clear accountability.
- 6–12 month roadmap is documented.
- Change management plan is active.
- Adoption metrics are defined.
- Continuous improvement loop is in place.
Consolidated Summary
| Section | Items | Completed | Notes |
|---|---|---|---|
| Value | 5 | ||
| Use Cases | 5 | ||
| Operating Model | 5 | ||
| Foundation | 5 | ||
| Governance | 5 | ||
| Execution | 6 | ||
| Total | 31 |