Applying NIST’s AI RMF to Third-Party AI: Why Your Vendors Are Your Risk Surface
Key Takeaways
- The NIST AI Risk Management Framework (AI RMF) sets the standard for building trustworthy AI, and it applies to vendor systems as much as your own.
- Third-party AI introduces unique risks including opaque models, inconsistent controls, and auditing challenges.
- Cranium operationalizes AI RMF across the supply chain to Govern, Map, Measure, Manage third-party AI through an AI Governance and Security platform
- With Cranium, enterprises can govern AI consistently, prove compliance, and manage vendor risks at scale.
Extending NIST AI RMF to Your Vendors
The NIST AI Risk Management Framework (AI RMF) has become the gold standard for building trustworthy AI. It isn’t optional—it’s a requirement; and in today’s world, vendor-supplied models and AI services make up a growing share of your ecosystem. That means every third-party system is part of your risk surface, and your governance strategy has to extend beyond your firewall.
What the Framework Really Means for Vendor AI
The AI RMF is organized around four core functions—Govern, Map, Measure, Manage. These aren’t abstract principles; they apply directly to vendor AI:
- Govern requires enterprises to establish policies and accountability frameworks that extend to vendors, not just internal teams.
- Map calls for visibility into where and how vendor systems are being used, their intended purpose, and the stakeholders involved.
- Measure demands consistent risk metrics, even when vendors provide only black-box models.
- Manage ensures that remediation and incident response processes are prepared for risks that originate in vendor systems.
In short: compliance doesn’t end with your own models. It must stretch across your entire supply chain.
Why Vendor AI Is So Challenging
This is where theory meets friction. Vendor AI introduces risks that complicate even the most diligent governance programs. Vendors rarely provide transparency into training data or risk methodologies, making it difficult to evaluate compliance. Their security and governance practices often don’t match your internal standards. And auditing multiple vendors quickly becomes a manual, resource-intensive process that doesn’t scale.
Without the right tools, what should be a business enabler turns into a compliance liability.
How Cranium Brings Order to Vendor AI
That’s why Cranium built the only platform designed to operationalize the AI RMF across both internal and third-party systems. Our six core capabilities create a unified approach to governance across the supply chain:
- Discover & Inventory: Detect AI identifies both internal and vendor systems, generating AI Bills of Materials (AI BOMs) for full visibility.
- Verify & Document: AI Card creates standardized profiles with compliance posture and risk scores, shareable with auditors and regulators.
- Measure & Test: Arena automates red-team testing using real-world adversarial libraries aligned to NIST AI RMF and global frameworks.
- Manage & Remediate: AutoAttest continuously scores compliance and generates attestations, while Shield applies and verifies fixes.
- Community & Trust: Through Trust Hubs, teams securely share governance artifacts with vendors, regulators, and peers—improving transparency across the supply chain.
Together, these capabilities translate the AI RMF’s four functions into a practical, automated system. They ensure governance doesn’t stop at your perimeter but travels with every AI system you depend on. The Takeaway.
If your vendors use AI, they expand your risk footprint. The question is whether you’re managing that risk—or leaving it unchecked. Cranium standardizes vendor AI evaluation and turns NIST AI RMF principles into action across your extended ecosystem.
