Managing AI risk with governance approaches to legal and cybersecurity challenges
Productivity, insight, and scale can all be amplified through artificial intelligence, though businesses and investors face distinct risk categories as a result. Operational failures, legal and regulatory exposure, ethical harm, cybersecurity vulnerabilities, financial misstatements, and reputational damage represent key concerns. What sets AI risk apart from conventional technology risk is that models may behave in unpredictable ways, absorb bias from their training data, and undergo changes over time independent of direct human oversight.Effective governance practices do not aim to eliminate AI risk, which is unrealistic, but to identify, measure, monitor, and control it in a way that aligns with corporate…
