From Compliance and regulatory affairs into AI governance

What you already carry

Credit before a single lesson. A work product counts as shown; experience you would describe counts as a claim. Neither is proof yet, and the graded path turns them into proof.

• Regulatory change management (shown by a work product)

  Regulatory change logs and applicability decisions are your work product.

• Control design and operating-effectiveness testing (shown by a work product)

  Control mapping and testing evidence exist in your files.

• Evidence collection and audit-ready documentation (shown by a work product)

  Audit-ready documentation is what you produce.

• AI policy and standards writing (described, not yet shown)

  Policy drafting is usually in the role, described rather than shown.

• Cross-functional facilitation and influence (described, not yet shown)

  Sitting between legal, business and IT is the daily job.

Roles this background reaches

• AI Compliance Manager

  Which obligation maps to which control, who owns it, and whether an exception may be granted.

  29% from this background alone
• AI Governance Analyst

  The draft risk tier of a use case and the evidence package that goes to the reviewer.

  24% from this background alone
• AI Risk Manager

  Which risks need strong controls, which can be accepted, and when a use case should pause.

• AI Vendor Risk Manager

  The risk tier of a vendor and use, what evidence is required, and whether to approve, condition, pilot, defer or reject.