When Generative AI burst onto the scene at the end of 2022, users gushed about the automatic content creation, greater productivity, and some funny or disturbing anomalies. Within days, it seemed, people who had not given Gen AI a try were outliers. Few technologies had captured the public’s imagination so quickly.

These developments were closely watched by chief risk officers across diverse industries, given their responsibility to identify, assess and mitigate significant risks to operations. This was especially the case in the insurance industry, where many CROs either took it upon themselves or were tasked by other senior executives and board members to balance the perceived benefits of Gen AI with its opaque risks.

Concerns centered on the accuracy and source of the underlying data used by different Gen AI models to detect commonalities, patterns and anomalies. Biased, inaccurate, fake or copyrighted information can result in compliance violations, intellectual property infringement, breach of contract, erroneous fraud alerts, harmful customer communications, third-party exposures and reputational damage. These risks and others are only half the story, of course.