As enterprises race to deploy AI across critical operations, especially in highly-regulated sectors like finance, healthcare, telecom, and manufacturing, they face a double-edged sword. AI promises unprecedented efficiency and insights, but it also introduces complex risks and uncertainties. Nearly 59% of large enterprises are already working with AI and planning to increase investment, yet only about 42% have actually deployed AI at scale. At the same time, incidents of AI failures and misuse are mounting; the Stanford AI Index noted a 26-fold increase in AI incidents since 2012, with over 140 AI-related lawsuits already pending in U.S. courts. These statistics underscore a growing reality: while AI’s presence in the enterprise is accelerating, so too are the risks and scrutiny around its use.
Privacy Pioneers: AI as the New Frontier
In our new research paper, we’ll discuss how privacy professionals, and their organizations, can take on AI governance — and what will happen if they don’t. Key findings include:
What to do when AI goes wrong?
AI systems have immense beneficial applications, however they also carry significant risks. Research into these risks, and the broader field of AI safety, hasn’t received nearly as much attention or investment until recently. For the longest time, there were no reliable sources of information about adverse events caused by AI systems for researchers to study. […]