What it means
Security and compliance for AI is broader than 'is the database encrypted'. It is: access controls, audit logs, data residency, vendor contracts (DPAs, BAAs), incident response plans, retention policies, training records, and the documentation that proves all of these to an auditor.
Most regulated firms (PDPA, GDPR, MAS, HSA, HIPAA) have specific overlays on top of generic security expectations. An AI deployment that ignores those overlays will not pass procurement, no matter how good the model is.
Why it matters
Security and compliance failures kill AI projects in two ways. The first is dramatic: a breach, a regulator letter, a customer incident. The second is quieter: the deployment cannot move to production because legal and compliance keep asking questions that were never planned for.
Building security in from the start is cheaper than retrofitting. Most of the work is documentation and process, not code. The code part is usually the easiest week of the deployment.
Example
A specialty clinic ships an AI clinical assistant under a documented compliance posture: ISO 27001 platforms, signed BAA with the model vendor, EU data residency (because some patients are EU residents), role-based access, 90-day log retention, quarterly review of all permissions. The deployment passes a HIPAA-equivalent review on the first attempt.