Generative AI (GenAI) presents many opportunities for organizations. It is particularly suited for process optimization of highly repeatable and data-centric tasks and tasks related to product development, customer experience enhancement, and predictive analytics. One key to assessing what opportunities may be available to your organization is to (1) understand how your company goes about doing its business; (2) identify tasks in those key workflows that are amenable to AI optimization; (3) assess the potential risks associated with those use cases; and (4) if those risks can be managed within your organization’s risk tolerance, implement AI in a safe, reliable, and compliant manner.

Many of the risks associated with AI are not unique. For example, the use of GenAI poses sustainability, data privacy, and security risks, to name a few. With that said, the National Institute of Standards and Technology (NIST)—the organization responsible for promoting innovation and industrial competitiveness by advancing measurement science, standards, and technology—finds that “AI systems also bring a set of risks that are not comprehensively addressed by current risk frameworks and approaches” [emphasis ours].¹ NIST and others have identified more than a dozen risks unique to AI or uniquely intensified by AI.

Categories of GenAI risk vary based on the industry and specific use case, but can include regulatory uncertainty, product liability, fraud/misrepresentations, limited AI fluency and unharmonized terminology, fragmented internal safeguards, intellectual property, confidentiality, AI systems quality concerns, data privacy, cybersecurity, lack of accuracy, unfair bias, insufficient contractual protections, unclear procurement standards, and reputational harm.

Other Generative AI topics to explore

Learn about other areas of Generative AI and how it impacts CLOs and their teams. From the basics to the more complex challenges, these resources are designed to help you navigate GenAI’s legal implications and risks with ease. 

¹ National Institute of Standards and Technology (NIST), Artificial Intelligence Risk Management Framework (AI RMF 1.0), January 2023.
² Deloitte, Proactive risk management in Generative AI, 2023.
³ Ibid.
⁴  Jeff Loucks, “Deepfakes and AI,” October 26, 2018; Ali Swenson, “FEC moves toward potentially regulating AI deepfakes in campaign ads,” Associated Press, August 10, 2023. 
⁵ Richard Torrenzano, “Generative A.I. has supercharged the speed at which false information spreads. Can our reputations survive the ‘two-hour internet day?’,” Fortune, July 18, 2023.