NIST AI RMF Alignment
For trustworthy, secure AI

Delivered by a cybersecurity firm, not a compliance shop.
Led by senior cybersecurity practitioners.
AI Inventory. Gap Assessment. Governance. Testing. Independent Assessment.
AI RMF basics

What is the NIST AI RMF?

The NIST AI Risk Management Framework (AI RMF) is the U.S. framework for managing the risks of designing, developing, deploying, and using AI systems. Released by the National Institute of Standards and Technology in January 2023, it is voluntary, technology-neutral, and built to work for organizations of any size.
NIST has since added a Generative AI Profile (NIST AI 600-1) and is revising the framework under the White House AI Action Plan. It is not a certification: organizations align to it and demonstrate that alignment through documentation and independent assessment.
Why it matters

The framework U.S. buyers and regulators point to

Customer trust

Answer AI risk questions with a recognized framework
Customers and partners increasingly ask how you manage AI risk. Mapping your program to the AI RMF gives them an answer they recognize.

A common language

Get leadership and engineering on the same page
The AI RMF gives your board, legal, product, and engineering teams shared terms for AI risk and who owns it.

Regulatory readiness

Prepare for AI rules built on the same ideas
Federal guidance and several state AI laws point to the AI RMF as a recognized framework, so aligning now prepares you for what comes next.

Path to certification

Build a foundation for ISO 42001
An AI RMF-aligned program covers much of the groundwork for ISO 42001 if your customers later ask for a certificate.
Inside the framework

Four functions. Seven traits of trustworthy AI

The AI RMF defines trustworthy AI as valid and reliable; safe; secure and resilient; accountable and transparent; explainable and interpretable; privacy-enhanced; and fair, with harmful bias managed. Its four functions are how you get there.
Govern

Culture and accountability

Policies, roles, and oversight that make AI risk management part of how the organization works. It applies across the other three.
Map

Context and risk

Understand each AI system: its purpose, users, data, and the ways it could cause harm or fail.
Measure

Testing and tracking

Analyze, test, and monitor AI risks and trustworthiness with methods and metrics suited to each system.
Manage

Prioritize and respond

Treat the risks that matter most, respond to incidents, and keep improving as systems and threats change.
NIST AI RMF and ISO 42001

NIST AI RMF or ISO 42001: which do you need?

They work well together. The AI RMF tells you how to think about and manage AI risk; ISO 42001 gives you a certifiable management system to prove it.
Area
NIST AI RMF
ISO 42001
Type
Voluntary risk management framework
Certifiable management system standard
Published by
NIST, a U.S. federal agency
ISO and IEC, international standards bodies
Structure
Four functions: Govern, Map, Measure, Manage
Management system clauses plus 38 Annex A controls
Generative AI
Dedicated Generative AI Profile (NIST AI 600-1)
Covered through AI risk and impact assessments
How you prove it
Documented alignment and independent assessment
Certificate from an accredited certification body
Best fit for
Building a flexible, U.S.-recognized AI risk program
Giving customers certifiable proof of AI governance
Our AI RMF approach

Cybersecurity at our core. Compliance built on it

Compliance should validate good cybersecurity, not substitute for it.

InfoGuard brings 30+ years of cybersecurity leadership and deep experience with NIST frameworks to AI risk, so your program reflects how AI systems are actually built, attacked, and used.

AI security expertise

Risk management that covers how AI actually fails
We address model, data, and pipeline risks such as poisoning, prompt injection, and data leakage alongside governance.

NIST framework depth

Practitioners who know NIST frameworks inside out
Years of work with NIST SP 800-53, SP 800-171, and the Cybersecurity Framework mean we apply the AI RMF the way NIST intended.

Hands-on senior leadership

Senior experts on your engagement, start to finish
Senior practitioners work alongside your product, data, and engineering teams, not a junior analyst running a checklist.

One effort, multiple frameworks

Do the work once, reuse it for ISO 42001 and more
We build one program that maps to the AI RMF, ISO 42001, ISO 27001, and the 2026 SOC 2 AI requirements, sharing policies and evidence.

Your compliance investment should deliver more than checklists and documentation.
It should improve your cybersecurity as well.

How we help

From AI inventory to an independent assessment, and beyond

01

AI Inventory & Context

We identify the AI systems you build, buy, or use, along with their purpose, data, users, and potential impacts.
02

Gap Assessment

We assess your current practices against the AI RMF functions and, where relevant, the Generative AI Profile, and document your current profile.
03

Target Profile & Roadmap

We define the target profile that fits your risk tolerance and business goals, with a prioritized roadmap to reach it.
04

Governance & Controls

We put in place the AI policy, roles, oversight, and technical safeguards your roadmap calls for, written to match how your teams work.
05

Measure & Test

We help you define metrics and testing for reliability, security, privacy, and bias, so AI risks are tracked rather than assumed.
06

Assess & Sustain

An independent assessment documents your alignment for customers and leadership, and ongoing reviews keep it current as systems change.
FAQ

NIST AI RMF questions, answered

The framework

No. The AI RMF is voluntary. Its value comes from customers, partners, and regulators recognizing it as a sound way to manage AI risk, and from federal guidance and state laws that point to it.
No. There is no official AI RMF certification. You demonstrate alignment through documentation and an independent assessment. If customers need a certificate, ISO 42001 is the certifiable standard and builds on the same groundwork.
No. The core approach of governing, mapping, measuring, and managing AI risk is not going away, and the work you do now carries forward. We track the revision and update your program when it is published.
NIST AI 600-1, published in July 2024, applies the AI RMF to risks specific to generative AI, such as confabulation, data privacy, information security, and harmful content, with suggested actions for each.

Scope, timing, and cost

Yes. The AI RMF covers AI you use as well as AI you build, including third-party models and AI features inside the software you buy.
Many organizations start with the AI RMF to build a flexible program, then pursue ISO 42001 when customers ask for a certificate. We plan the work once so it serves both.
It depends on how many AI systems are in scope and how mature your governance is today. Most organizations can reach a documented current and target profile in weeks, with implementation over the following months.
Cost depends on the number of AI systems, their risk, and how much needs to be built. There is no flat fee. We provide a firm quote after an initial gap assessment.
Cybersecurity first

A checkbox compliance provider won't cut it

You need real cybersecurity expertise to manage AI systems that can be attacked, misused, or fail in new ways, not just a policy that says you do.
Next step

Tell us where you stand

Tell us how you build or use AI. We’ll reply with next steps, whether that’s an AI inventory, an AI RMF gap assessment, or a plan that covers ISO 42001 as well.