Sweat the small stuff: Data protection in the age of AI

With rising concerns over AI security, risk, and compliance, finding practical solutions can feel frustratingly elusive. The recent release of the NIST-AI-600-1, also known as the Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, on July 26, 2024, is just the start for many organizations. Most are still wrapping their heads around its insights and taking preliminary steps toward solid AI governance by establishing internal AI Councils. As AI reliance and the associated risks grow, it’s crucial to understand why even the minutiae matter and where our collective journey leads us.

Protecting Data in the AI Era

Recently, I had the opportunity to attend the annual conference of the ACSC, a non-profit dedicated to bolstering cybersecurity efforts across various sectors like enterprises, universities, and government agencies. The conversations were eye-opening, revealing that the primary focus for executives such as CISOs, CIOs, CDOs, and CTOs is on two core issues: safeguarding proprietary AI models from threats and keeping sensitive data from being absorbed by public AI platforms.

Interestingly, while many organizations may not yet grasp the seriousness of the first problem—defending against prompt injection attacks that lead to model drift, hallucinations, or outright failures—those that do recognize this risk are already taking steps to mitigate it. Unlike the infamous 2013 Target breach that consumers still remember, the damage from AI-related vulnerabilities has yet to manifest in a very public way. Much of the current evidence remains in the academic realm. However, firms deploying their own models are increasingly aware of the need to keep their AI’s integrity intact. It’s only a matter of time before a significant breach hits the headlines. When that happens, it can cause irreversible brand damage and even more serious fallout.

Consider this: a small tech startup in your area developed an innovative AI tool that’s gaining traction. One day, they realize that their proprietary model has been tampered with, leading to erroneous outputs that frustrate their users and threaten their reputation. The stakes are high, and as AI technology evolves, organizations must stay ahead of potential threats to protect both their innovations and the data they handle.

As we continue exploring the wild frontier of AI, the need for robust risk management grows ever more pressing. Companies must prioritize training, refine their protocols, and stay informed about the evolving landscape of AI security. This is not just a tech issue; it’s a business imperative that touches every corner of an organization.

The potential for AI is immense, but only if we can secure its foundations. It’s time for organizations of all shapes and sizes to roll up their sleeves and tackle these challenges head-on, ensuring that as we innovate, we do so responsibly.

The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.