AI is transformational, but exposes organizations to security, ethical, and operational risks. The pace of AI innovation and emergence of large language models (LLMs) and generative AI only exacerbates the problem.
In most organizations today, AI is a source of unmanaged risk which requires a new paradigm to address and meet regulatory requirements. AI risk management frameworks have emerged to help organizations approach these new challenges.
The NIST AI Risk Management Framework (AI RMF) is considered by many to be the most comprehensive AI framework developed to date, but getting started can feel daunting. In this primer, we cover:
- An overview of the AI RMF and its components
- Common implementation challenges
- Best practices for applying the AI RMF
- How Robust Intelligence can help