ANI Consulting Services
Data and AI Readiness Checklist

Use this checklist before starting modernization programs.

1) Strategy and Outcomes
- Are business outcomes defined (cost, speed, reliability, risk)?
- Are KPI owners and decision owners identified?
- Is scope prioritized into 30/60/90 day milestones?

2) Architecture and Platform
- Is current architecture documented (systems, interfaces, bottlenecks)?
- Are environments separated (dev/test/prod)?
- Are failure points and dependencies mapped?

3) Data Foundations
- Are critical data sources identified and classified?
- Are data quality rules defined for key entities?
- Are lineage and transformation steps documented?

4) Security and Access
- Is least-privilege access enforced?
- Are credentials managed securely (no hardcoded secrets)?
- Are audit logs and access reviews enabled?

5) Governance and Compliance
- Is GDPR/privacy impact reviewed for relevant workflows?
- Are retention and deletion policies defined?
- Are data sharing and third-party processor controls documented?

6) Operations and Reliability
- Are monitoring and alert thresholds defined?
- Are incident ownership and escalation paths clear?
- Are backup and recovery expectations validated?

7) BI and Reporting
- Are KPI definitions standardized across teams?
- Is there a semantic model to prevent metric drift?
- Are dashboard consumers and refresh SLAs defined?

8) AI Readiness
- Are high-value use cases prioritized by ROI and risk?
- Are model guardrails and approval criteria documented?
- Is human oversight defined for critical decisions?

9) Delivery and Change Management
- Is there a delivery cadence with weekly steering updates?
- Are assumptions, risks, and decisions logged?
- Is handover documentation prepared for internal teams?

10) Executive Control
- Is there a transformation scorecard with baseline and targets?
- Are monthly value reviews scheduled with leadership?
- Is ownership assigned for each workstream?

Need help implementing this checklist?
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