MACHINE LEARNING (ML) TO EVALUATE GOVERNANCE, RISK, AND COMPLIANCE (GRC) RISKS ASSOCIATED WITH LARGE LANGUAGE MODELS (LLMs)

In today’s AI-driven digital world, Governance, Risk, and Compliance (GRC) has become vital for organizations as they leverage AI technologies to drive business success and resilience. GRC represents a strategic approach that helps organization using Large Language Models (LLMs) automation tasks and enhances customer service, while maintaining the regulatory complexity across various industries and regions. This paper explores a machine learning approach to evaluate Governance, Risk, and Compliance (GRC) risks associated with Large Language Models (LLMs). It utilizes Azure OpenAI Service logs to construct a representative dataset, with key features including responseₜimeₘs, modelₜype, temperature, tokensᵤsed, isₗogged, dataₛensitivity, complianceflag, biasₛcore, and toxicityₛcore. These features are used to train a model that predicts GRC risk levels in LLM interactions, enabling organizations to improve efficiency, foster innovation, and deliver customer value, while maintaining compliance and regulatory requirements.