What’s Your Enterprise AI Readiness Score?
- Staff
- Aug 3
- 3 min read
Instructions
Answer each question based on your organization’s current reality, not future goals.
Each response has a point value.
At the end, total your score to identify your SAAF stage.
Your result includes a next step and toolkit recommendation.
Find out where your organization stands—and what to do next.
Our organization has conducted an AI readiness or maturity assessment.
Never (0) | Planning to (1) | In progress (2) | Completed recently (3)
We’ve identified and prioritized AI use cases that align with strategic goals.
No (0) | Vaguely (1) | A few departments (2) | Org-wide, mapped in Confluence (3)
We have a defined AI governance board or responsible decision-making body.
No (0) | Drafted (1) | In progress (2) | Fully established (3)
AI projects must pass a basic ethical or risk assessment before launch.
Never (0) | For some (1) | For most (2) | Required org-wide (3)
Each role or department has a defined enablement plan for working with AI.
No (0) | In development (1) | Partial rollout (2) | Fully mapped by role (3)
We’ve scoped the technical workflows and system integrations needed for AI adoption.
No (0) | Some systems (1) | Most systems (2) | Fully mapped / linked in ticketing system (3)
We’ve run pilots to test AI in production-like environments.
No pilots (0) | 1–2 pilots (1) | A few teams (2) | Org-wide experimentation (3)
Pilots include feedback forms, retrospectives, and performance monitoring.
Not at all (0) | Occasionally (1) | Frequently (2) | Always (3)
We’ve rolled out AI tools to multiple teams with training and support.
No (0) | Pilots only (1) | Some departments (2) | Org-wide rollout (3)
We track usage, errors, and support requests for scaled AI tools.
No tracking (0) | Manual (1) | Partial dashboard (2) | Centralized dashboard (3)
We review AI outcomes regularly for model drift, bias, or user trust issues.
Not yet (0) | Some efforts (1) | Regularly for key tools (2) | Org-wide review cycle (3)
Feedback from users and governance teams is incorporated into AI improvements.
Rarely (0) | Sometimes (1) | Often (2) | Always, with documentation (3)
Scoring Guide
0–6: Stage 1 – Discovery & Alignment
→ Start by assessing readiness and aligning AI use cases with strategy. Use the AI Maturity Index and Use Case Scoring Model.
7–13: Stage 2 – Governance & Investment
→ Formalize your governance structure and evaluate ethical risks. Use the AI Adoption Charter and Ethical Risk Pre-Assessment.
14–20: Stage 3 – Planning & Enablement
→ Design enablement plans by role and scope workflows across tools. Use Role-Based Enablement Maps and the AI Initiative Blueprint.
21–27: Stage 4 – Execution & Experimentation
→ Launch pilot sprints and collect performance, risk, and feedback data. Use the AI Agile Sprint Backlog and Bias Audit Checklist.
28–34: Stage 5 – Validation & Activation
→ Evaluate pilot value and make go/no-go decisions before scaling. Use the Business Value Scorecard and Ethical Go/No-Go Gate.
35–41: Stage 6 – Transition to Scale
→ Prepare for enterprise rollout with support, tracking, and training. Use the Production Readiness Checklist and Deployment Runbook.
42–48: Stage 7 – Optimization & Governance
→ Monitor AI in production and evolve governance with feedback cycles. Use the Model Drift Dashboard and Ethical Oversight Logs.
Next Step
Use your result to locate your organization’s SAAF stage and activate the matching resources. Retake the quiz quarterly as you scale or support new departments.
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