Foundation Readiness Check

Confirm your organization is ready to scale AI safely across seven foundation domains.

Related guides: Pre-Flight Prerequisites · Implementation Guide

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Scoring Method

1. Score each item as Yes or No.
2. Count total Yes results.
3. Use the interpretation table below.

Score	Interpretation	Recommended Action
0–17	High readiness risk	Fix core gaps before production AI deployment
18–27	Partial readiness	Start only with low-risk, supervised use cases
28–34	Strong readiness baseline	Proceed with controlled scale-up

1. Process Maturity

Documented, owned, and measurable workflows.

• Key processes are documented with steps and decision points.
• Process owners are assigned and accountable.
• Performance baselines exist (time, error, cost).
• Exception paths are mapped beyond the happy path.

Deep dive: Domain 01 Guide

2. Data Foundation

Trusted data inventory, quality, lineage, and ownership.

• Data inventory is complete for major datasets.
• Classification scheme is defined and applied.
• Data quality standards are defined per dataset.
• Lineage is documented for critical datasets.
• Dataset ownership is assigned.

3. Information Security

Security policy, access control, and incident readiness for AI.

• Security policy is documented and approved.
• IAM and RBAC follow least privilege.
• Secrets management is in use for credentials and keys.
• Secure engineering practices apply to AI components.
• AI-related incident response plan is tested.

4. Privacy and Compliance

Legal basis, regulation tracking, and privacy-by-design controls.

• PII is mapped with legal basis and purpose.
• Applicable regulations are identified and tracked.
• Privacy-by-design controls are applied by default.
• Legal review is required before deployment.
• Retention and deletion policies cover AI training data.

5. Technology Baseline

Platform, integration, identity, and delivery standards.

• Cloud and AI platform standards are defined.
• API standards and service catalog exist.
• Identity and SSO integration is available.
• Observability standards are enforced.
• CI/CD includes test, security, and approval gates.

6. People and Change

Sponsorship, literacy, reskilling, and adoption feedback.

• AI literacy baseline exists for employees.
• Executive sponsors are named and active.
• Change management capability is in place.
• Reskilling paths exist for impacted roles.
• Feedback channels exist for AI adoption issues.

7. Ethics and Principles

Adopted principles, bias checks, explainability, and appeal paths.

• AI principles are formally adopted.
• Ethics owner or committee is assigned.
• Bias assessment process is defined.
• Explainability standards exist for high-impact decisions.
• Override and appeal paths are documented.

Summary

Domain	Total Items	Yes	No
Process Maturity	4
Data Foundation	5
Information Security	5
Privacy and Compliance	5
Technology Baseline	5
People and Change	5
Ethics and Principles	5
Total	34