AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models

Anthony M. Barrett, Jessica Newman, Brandie Nonnecke, Nada Madkour, Dan Hendrycks +3 more
6/30/2025
cs.AIcs.CRcs.CY

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Abstract

Increasingly multi-purpose AI models, such as cutting-edge large language models or other 'general-purpose AI' (GPAI) models, 'foundation models,' generative AI models, and 'frontier models' (typically all referred to hereafter with the umbrella term 'GPAI/foundation models' except where greater specificity is needed), can provide many beneficial capabilities but also risks of adverse events with profound consequences. This document provides risk-management practices or controls for identifying, analyzing, and mitigating risks of GPAI/foundation models. We intend this document primarily for developers of large-scale, state-of-the-art GPAI/foundation models; others that can benefit from this guidance include downstream developers of end-use applications that build on a GPAI/foundation model. This document facilitates conformity with or use of leading AI risk management-related standards, adapting and building on the generic voluntary guidance in the NIST AI Risk Management Framework and ISO/IEC 23894, with a focus on the unique issues faced by developers of GPAI/foundation models.

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@article{barrett2025riskmanagement,
  title  = {AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models},
  author = {Anthony M. Barrett and Jessica Newman and Brandie Nonnecke and Nada Madkour and Dan Hendrycks and Evan R. Murphy and Krystal Jackson and Deepika Raman},
  year   = {2025},
  eprint = {2506.23949},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.23949v1}
}

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