Navigating the NIST AI RMF

Artificial intelligence has revolutionized industries, changed the way we work, and created limitless new possibilities—however, as its capabilities continue to grow, so do the risks.

The National Institute for Standards and Technology (NIST) introduced the Artificial Intelligence Risk Management Framework (AI RMF) in 2023 to offer guidance on how to responsibly create, work with, and use AI. It’s a voluntary framework that any organization can (and should) adopt. Below is a breakdown of the NIST AI RMF and how to utilize it.

AI RMF Core

The AI RMF Core outlines what a trustworthy AI system looks like—which includes being secure, accountable, and unbiased. Keep these characteristics in mind when designing, evaluating, and using AI products or services.

Organizations should regularly evaluate any AI system’s risk management effectiveness for continual improvement. The AI RMF Core offers four key ways to do this—Govern, Map, Measure, and Manage—with recommendations that can be tailored to your company.

Govern – Develop and cultivate a culture of risk management.

Map – Identify all AI systems and employees that use AI within your organization to get a complete picture of the associated risks. 

Measure – Test, analyze, and track all identified risks to ensure security and trustworthiness.

Manage – Prioritize and address the risks associated with AI to maximize the technology’s benefits and minimize negative impacts.

AI RMF Playbook

Working off the four key functions in the AI RMF Core, the Playbook offers practical guidance on how to implement each within any organization.   

Since the suggestions are all voluntary, you can pick and choose the actions that make sense to implement within your company. This direction can be leveraged to establish policies and accountability structures that ensure any AI system is created and deployed safely while taking advantage of all its possibilities. 

AI RMF Roadmap

Since AI is continuously developing and advancing, the Roadmap details how NIST will maintain the AI RMF to stay useful and relevant. It identifies ways NIST can advance the AI RMF whether in collaboration with public and private organizations or independently.

The Roadmap explains how NIST will align with international standards and develop standardized methodologies to assess risks and trustworthiness within AI systems. It also includes guidance on human factors for those who work with AI, methods for developing reasonable risk tolerances around the technology, tutorials, and other resources. 

AI RMF Crosswalks

Alongside the International Standards Organization (ISO), NIST developed the Crosswalks tool to show how applying the AI RMF’s standards will help organizations meet parallel standards required by other countries or regions. 

Use-Case Profiles

Finally, NIST offers tailored examples of how the AI RMF can function and work in the real world, catering to various sectors on a case-by-case basis. These two types of use-case profiles show how AI risk can be managed throughout the technology’s lifecycle in different sectors, technologies, and applications.

Current Profiles – The current state of AI management and its known risks.

Target Profiles –  The desired outcomes for reaching specific AI risk management goals.

Final Thoughts 

As AI continues to proliferate into more facets of business, the AI RMF can offer a customizable and actionable plan to minimize risk while promoting the technology in a safe and responsible manner.
If your organization is looking to adopt the NIST AI RMF, don’t hesitate to contact us. Zaviant is heavily involved in the AI space, and has even worked alongside a consortium of industry leaders to help shape the future of AI’s place in business and society through Meta’s Open Loop program.

Zaviant understands the increasingly pivotal role that artificial intelligence (AI) is playing in shaping industries, policy, and society at large, and our goal is to empower our clients to harness its full potential while upholding security, ethical standards, regulatory compliance, and stakeholder trust.