Balancing the Use of Generative AI: Considerations for Audit, Risk, and Compliance
Midway through 2024, generative AI continues to dominate discussions with contrasting narratives about its transformative potential and inherent risks. Is it a revolutionary game-changer or an overhyped, risky technology? We are at a crucial juncture in understanding and leveraging generative AI, and the truth lies somewhere between these extremes.
Audit, risk, and compliance professionals are pivotal in navigating this landscape. They serve as both guardians of governance—ensuring AI adoption doesn’t expose organizations to undue risks—and as enablers, helping to harness its potential. This dual role presents a unique opportunity to balance the promise and perils of generative AI. Achieving this balance requires close collaboration with business leaders to chart an optimal digital risk path, recognizing AI’s potential impact within the broader context of digital risk realities.
To aid organizations in navigating the complexities of generative AI, two frameworks can help distinguish hype from reality and provide a structured approach to understanding and managing risk. The first framework is Gartner’s Hype Cycle, an invaluable tool that depicts the various stages that occur as new technologies are brought to market. This cycle helps organizations determine when to manage deployment within their specific business and industry context.
The Hype Cycle provides valuable insights but leaves risk considerations needing to be addressed. To address this, the Digital Risk Cycle offers a practical roadmap in five phases to trace the optimal digital risk management path. This is designed to help organizations better understand the challenges they face when creating or implementing new digital products and services.
To read more about these two tools, as well as upcoming AI legislation in Europe and how to address AI risk via a more integrated approach, get your copy of How Audit, Risk, and Compliance Can Bridge the Promise and Perils of Generative AI today.
White Paper from 