IL 202 | Enterprise AI Data, Governance & Integration Readiness
Addresses the prototype-to-pilot readiness gap: data rights, security, privacy, identity/access, integration, governance, ownership, and operations: producing an Enterprise AI Readiness Review.
Your next step
IL 202 · Module 1: Data and Data Flow
Curriculum
- Module 1Data and Data FlowInventory data sources and rights, map data flow end to end, and settle retention, deletion, and ownership.
- Module 2Access and IntegrationTest least-privilege access per role, design read-only integrations, and drill failure and revocation scenarios.
- Module 3Incidents and OperationsDrill bad output, tool outages, and out-of-scope requests, and write a runbook that actually works.
- Module 4Readiness ReviewAssemble evidence, gaps, owners, and deadlines across the seven domains into a complete Enterprise AI Readiness Review.
Progress is stored in this browser and does not identify you. It is uploaded only if you join progress sync below.
Practice and assessment
About this course
Outcomes
- Assess data readiness
- Assess security readiness
- Assess privacy readiness
- Assess integration readiness
- Assess governance readiness
- Assess operations readiness
- Assess people readiness and produce a final recommendation
Prerequisites
- IL 101 is recommended first
- IL 201 is ideally completed; mature enterprise teams may run it in parallel
Who it is for
- Technical and governance owners who need to move a PoV toward a pilot
- Security, privacy, and data-governance owners
- IT integration and operations owners
Certificate
Earns a capability certificate (L2).
Requirements to earn it
- Submit a project artifact and pass review
Why this course
A prototype that has already shown value is not the same as being ready for a pilot. IL 202 addresses the readiness gap across data rights, security, privacy, identity/access, integration, governance, ownership, and operations.
Learning and project time planning
| Formal guided hours | 12 hours |
| Estimated independent/applied project time | Not yet determined |
| Suggested real-world project span | Not yet determined |
Enterprise AI Readiness Review
- Data readiness (status: READY / READY WITH CONDITIONS / NOT READY / NOT APPLICABLE)
- Security readiness
- Privacy readiness
- Integration readiness
- Governance readiness
- Operations readiness
- People readiness
- Final recommendation (Proceed to Pilot / Proceed with Conditions / Remediate First / Stop)
Review process
| Each of the seven readiness domains is marked individually | Reviewed by cross-domain and AI/data advisors |
| The final recommendation must carry specific reasons and open conditions | Academic rubric passed |
Completing IL 202 moves the project to Gate 3 (the Readiness Gate): READY, READY WITH CONDITIONS, NOT READY, or STOP.
Certificate
AI Skill Certificate: Enterprise AI Readiness. Requires: the readiness review is completed, the required controls have been assessed, and the academic rubric is passed.
Roles
- Technical and governance owners: lead the readiness review
- Security, privacy, and data-governance owners: contribute judgment on their domains
- IT integration and operations owners: assess integration and post-launch support
- Cross-domain and AI/data advisors: help review and gatekeep
Data and privacy requirements
The readiness review may reference internal enterprise systems, data flows, and security controls: treat it as sensitive: store it only in managed locations and share it only with authorized people.
Related courses and next step
IL 101 is recommended first; IL 201 is ideally completed. Mature enterprise teams may run it in parallel with IL 201.
Depending on the Readiness Gate decision, carry the project into IL 301's pilot and adoption lab, or complete the remediation conditions first.
Course feedback
It takes 2 to 3 minutes and is used to improve the course.