AI Readiness Assessment • Self-Scoring Checklist

Updated to reflect the latest Leadership Forum: this version adds a dedicated AI governance readiness section and sharper questions around visibility, shadow AI, permissions, approved tools, vendor review, and practical next steps.

Use this self-assessment to see how prepared your organization is to adopt AI safely, strategically, and at scale. Answer each question, calculate your score, and use the results to guide conversations with leadership, security, data, and operational teams about what comes next.

This updated version reflects the latest Leadership Forum discussion, where leaders emphasized that AI is already in most organizations, but governance, oversight, and visibility often lag behind adoption.

Related resources:

Leadership Forum recap: AI readiness, governance, and shadow AI
AI exploration recipes

Total Possible Score: 161 points Readiness Stages: Early • Emerging • Operational • Strategic

1. Organizational Alignment & Executive Readiness

Clarity, ownership, and leadership posture around AI.

Max 25 pts

How aligned is your executive team around AI strategy?

Not aligned Somewhat aligned Generally aligned Strongly aligned

How does leadership currently talk about AI?

Hesitantly Curiously With urgency As transformational

Who currently owns AI decision-making?

No one IT or one department only Emerging task force Cross-functional leadership group

How urgent is your organization’s appetite for AI adoption?

Low urgency Moderate urgency High urgency

How clear are your goals for AI, such as productivity, automation, customer experience, or innovation?

No clarity Some clarity Clear, documented goals

2. Data Foundations & System Readiness

Data quality, classification, integration, and security posture.

Max 25 pts

What is the quality and availability of your data for AI?

Unknown or very poor Limited Good High quality and well-governed

How mature is your data governance, including classification, stewardship, and lifecycle management?

None Basic Established Strong and consistent

How integrated are your core systems, such as CRM, ERP, M365, and cloud platforms, for AI use?

Siloed Partially integrated Well-integrated environment

How strong are your AI-related security controls today?

Not ready Basic safeguards Strong identity, monitoring, and compliance controls

How well do you detect and manage shadow AI or unsanctioned tool usage?

Little or no oversight Some monitoring Well-controlled with policies and tooling

3. Policy & Risk Management

AI usage policy, approvals, data protection, and incident response.

Max 20 pts

Do you have a formal AI usage and governance policy?

None Drafted Approved Enforced and operational

Do you have a review and approval process for new AI tools or copilots?

No process Informal Documented and consistently used

How well do you enforce data protection standards for AI usage?

Weak Moderate controls Strong controls aligned with compliance

Do you have an incident response plan for AI-related issues, including data leakage, hallucinations, or misuse?

None Basic Strong and tested

4. AI Governance Readiness

Visibility, committee structure, permissions, approved paths, and vendor oversight.

Max 26 pts

How mature is your AI governance structure today?

No governance structure One team informally handles it Cross-functional group is forming Formal governance committee is active

How much visibility do you have into where AI is already being used across the organization?

Very little visibility Some anecdotal visibility Visibility into major tools and teams Strong visibility through process, dialogue, and tooling

How ready are your permissions, security trimming, and role-based access controls for AI-assisted search and retrieval?

Not ready Partially reviewed Mostly aligned Strongly aligned and regularly audited

Do employees have a supported path to request, pilot, and evaluate new AI tools instead of going around policy?

No, people are largely on their own Some path exists, but it is inconsistent Yes, there is a defined and practical path

How mature is your process for reviewing embedded AI in vendor platforms and other third-party tools?

Rarely reviewed Reviewed case by case Standardized as part of vendor governance

5. Culture, Skills & Workforce Readiness

AI fluency, training, communication, and internal champions.

Max 20 pts

What is the current level of AI fluency across your workforce?

Very low A few individuals are fluent Moderate fluency High fluency and active training

How does your team typically respond to AI ambiguity?

Avoids it Waits for direction Experiments independently Experiments and shares what works

What training programs currently support AI adoption?

None Sporadic or departmental Formal and consistent training

Is your organization ready to support internal AI champions or enablement roles?

No Possibly Yes, actively planning or already doing it

How strong are your internal communication channels for AI knowledge-sharing?

None Limited Active and cross-functional

6. Use Case Maturity & ROI Orientation

Practical use cases, pilots, measurement, and innovation culture.

Max 25 pts

How clear are your high-value AI use cases?

Not defined A few ideas Well-defined and documented

How do you measure AI outcomes and ROI?

No measurement Informal observation Usage data and feedback Fully integrated KPIs

How well do teams collaborate across functions on AI initiatives?

Not at all Some collaboration Strong collaboration

How would you describe your innovation culture?

Late adopter Follows once proven Iterates quickly Inventive and experimental

How effectively do you balance innovation with risk management?

No guardrails Some guardrails Strong governance with flexibility

7. Scaling Readiness

Training, enablement, documentation, production rollout, and vendor governance.

Max 20 pts

How many employees will be trained on AI within 12 months?

Fewer than 10 10–50 50–200 200+

Do you have an internal AI enablement model, such as champions, playbooks, or workflow libraries?

None In development Active and used

How well documented are your AI processes, governance, and use cases?

Not documented Partially documented Well-documented and maintained

Are you able to scale successful AI pilots into production?

Not yet Sometimes Consistently

How mature is your vendor and tool governance across platforms like Copilot, OpenAI, Gemini, Claude, or custom solutions?

Not mature In progress Mature and standardized

All questions are required for an accurate score.

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AI Readiness In-Depth

Turn this self-assessment into a concrete action plan. Atomic Data’s AI Readiness Assessment engagement combines security, data, governance, and executive alignment to help you move from scattered experimentation to responsible, scalable AI.

Get a tailored maturity scorecard, prioritized use cases, and a phased roadmap aligned to your environment.

Talk to an Expert

AI Readiness Assessment: Assess Your Organization’s AI and Governance Readiness

1. Organizational Alignment & Executive Readiness

2. Data Foundations & System Readiness

3. Policy & Risk Management

4. AI Governance Readiness

5. Culture, Skills & Workforce Readiness

6. Use Case Maturity & ROI Orientation

7. Scaling Readiness

AI Readiness In-Depth