TL;DR
- Regulated industries need AISPM to produce evidence, not just findings.
- Anchor the program in NIST AI RMF and ISO/IEC 42001 governance patterns.
- If EU AI Act applies, risk management must be continuous across the lifecycle for high-risk systems.
- For healthcare, HIPAA Security Rule expects reasonable administrative, physical, and technical safeguards for ePHI. Rule summary
The core truth about regulated AISPM
In regulated environments, the question is rarely “did you find risk.” It is:
- Did you implement controls
- Can you prove they work
- Can you show continuous improvement
ISO/IEC 42001 explicitly frames an AI management system as something established, implemented, maintained, and continually improved, which maps naturally to AISPM operating models.
How to map AISPM to NIST AI RMF
NIST AI RMF organizes AI risk management into Govern, Map, Measure, Manage. Use it to structure your AISPM program and reporting.
GOVERN
- define policies, roles, approvals, and exception handling
- set risk thresholds and ownership
Evidence: policy docs, approvals, training, exceptions log
MAP
- inventory AI assets, data flows, identities, dependencies
Evidence: system maps, inventories, data lineage, tool catalogs
MEASURE
- assess controls, evaluate outcomes, test for failure modes
Evidence: assessments, tests, evaluations, red team results
MANAGE
- remediate, monitor, and improve continuously
Evidence: tickets, SLAs, closure metrics, control improvements
EU AI Act alignment
For high-risk systems, the AI Act requires a risk management system that is a continuous process across the lifecycle, regularly reviewed and updated. Article 9 specifies the details on this act. AISPM is how many teams operationalize that expectation.
HIPAA alignment for healthcare
HIPAA Security Rule requires reasonable administrative, physical, and technical safeguards to protect ePHI. AISPM helps you demonstrate:
- access controls to AI systems that handle ePHI
- audit controls and logging
- integrity controls over AI pipelines and outputs
Control families that matter most in regulated AISPM
- identity and access management
- audit logging and retention
- data minimization and redaction
- change control and approvals
- vendor and third-party oversight
- incident response readiness
NIST SP 800-53 is a widely used catalog of security and privacy controls that can guide how you describe and implement controls across systems, including AI-related services.
Building an evidence pack
Regulated AISPM should produce an evidence pack with:
- AI asset inventory, ownership, and criticality
- data classification rules for prompts, retrieval, and outputs
- access and scope mapping for agents and MCP servers
- logs for tool calls and model invocation
- risk assessments and test results
- remediation SLAs and closure metrics






