Enterprise AI Security Governance Framework

A practical mapping tool that translates AI governance and compliance expectations into enterprise security capabilities and Palo Alto Networks solution areas across users, applications, agents, browsers, endpoints, data, and runtime.

0governance/security references
0Enterprise AI Security Domains
0PANW Capability Areas

Core Message

AI governance should not stop at policies, inventories, and compliance checklists. It must be operationalized through enforceable security controls.

1
Governance intent
NIST AI RMF, ISO/IEC 42001, NIST GenAI Profile, EU AI Act, NIST SP 800-207 Zero Trust Architecture
2
Enterprise AI Security Domains
GenAI access, data, application runtime, model and agent artifact supply chain, agent, endpoint, browser, monitoring
3
Security control plane
Palo Alto Networks portfolio aligned to real-world enforcement points

Interactive Framework Mapping

Showing all mappings

Reference-to-Control-to-Capability Map

Full-width swimlane view: governance framework, regulation, or security architecture reference → Enterprise AI Security Domain → PANW Capability Area.
Click any node to highlight the related governance-to-control-to-capability path and open details.
1. Governance / Compliance / Architecture Reference
Governance, compliance, and security architecture expectations from NIST AI RMF, ISO/IEC 42001, NIST AI 600-1, EU AI Act, and NIST SP 800-207 Zero Trust Architecture.
2. Enterprise AI Security Domain
Enterprise AI security domains that translate governance and compliance expectations into concrete areas of control such as access, data protection, runtime defense, supply chain, endpoint, browser, monitoring, and Zero Trust for AI.
3. PANW Capability Area
PANW capability areas that operationalize AI governance across AI access, browser, endpoint, agent, runtime, data, posture, and SOC layers. Prisma SASE is treated as the underlying Zero Trust delivery architecture, not as a standalone capability node.

Suggested Adoption Journey

Stage 1
Visibility
Discover AI apps, shadow AI, agents, tools, browser workflows, endpoint AI artifacts, and data flows.
Stage 2
Assessment
Classify AI use cases, assess risk, test models and agents, verify identity, and evaluate data exposure.
Stage 3
Enforcement
Apply Zero Trust access, data protection, runtime controls, browser guardrails, and endpoint policy.
Stage 4
Response
Monitor drift, detect misuse, correlate events, automate response, preserve audit evidence, and continuously improve.

Reference Sources Embedded in the Prototype