1. Establish governance
Define accountable leadership, governance roles, decision rights, escalation, policy ownership, and risk appetite.
NIST AI RMF implementation services
Operationalize the NIST AI Risk Management Framework.
Move from framework awareness to a working AI governance program that connects AI inventory, risk decisions, controls, human oversight, evidence, monitoring, and executive accountability.
Implementation approach
Build the framework into your existing business and security processes.
A NIST AI RMF engagement should not end with a document. The goal is a repeatable operating model that your business, security, legal, privacy, data, procurement, and technology teams can actually use.
2. Build the AI inventory
Document AI systems, models, vendors, business owners, users, data, purpose, dependencies, and lifecycle status.
3. Map context & impact
Understand business use, affected stakeholders, data sensitivity, decision impact, autonomy, and external dependencies.
4. Assess & measure risk
Evaluate security, privacy, reliability, legal, model, vendor, operational, and human-impact risks using repeatable criteria.
5. Manage risk
Define controls, approvals, human oversight, testing, remediation, exceptions, residual risk acceptance, and ownership.
6. Monitor & improve
Track evidence, changes, incidents, exceptions, overdue reviews, metrics, and governance maturity over time.
What you can receive
Practical NIST AI RMF implementation deliverables.
AI governance charter
Purpose, scope, ownership, decision rights, committees, escalation, and governance cadence.
AI inventory & classification
Structured inventory fields and a risk-tiering method aligned to business impact and AI risk.
AI risk assessment method
Repeatable assessment questions, scoring logic, risk treatment, evidence, and approval criteria.
Policy & standards
Acceptable use, data handling, human oversight, third-party AI, documentation, and exceptions.
Control & evidence map
Controls and evidence expectations tied to AI risk categories and lifecycle governance.
Implementation roadmap
Prioritized actions, owners, milestones, dependencies, and measurable governance outcomes.
Need the framework overview first?
Review our NIST AI RMF framework page, then return here when you are ready to operationalize it.
Explore the NIST AI RMF overview →
AI governance consulting
Ready to turn NIST AI RMF into a working governance program?
Start with a focused discussion about your AI use, current controls, customer requirements, and governance maturity.