As Chief Information Security Officers, we’ve always had to make tough tradeoffs. Risk versus reward. Speed versus safety. Control versus collaboration. Today, generative AI is pushing those tradeoffs into unfamiliar territory—and faster than many of us would like.

AI is not a hypothetical risk vector on the horizon. It’s already embedded in business operations, decision-making, customer engagement, and cybersecurity defenses. But while AI can help us catch threats earlier and respond faster, it also introduces a new surface area of risk—particularly at the inference layer, where these models actually engage with real-world data and users.

Let’s be clear: we are not dealing with just another technology wave. This is a fundamental shift in how decisions are made and information is handled across the enterprise. And unlike cloud or mobile, where we had years to adapt and develop controls, the pace of AI adoption has far outstripped the maturity of our defensive frameworks.

Too often, security teams are seen as the group that says “no”—the friction in the system. But that mindset doesn’t work in this era. If we slow AI down too much, innovation will happen without us. Whether sanctioned or not, the business will find a way to use these tools. And that leaves us with something worse than risk: blind spots.

We must reposition security not as the barrier, but as the enabler—providing the oversight and guardrails that allow AI innovation to flourish safely. That means saying “yes, and here’s how we do it responsibly.”

While much of the early AI security discussion focused on training data and model development, most enterprises don’t build models from scratch. They consume them—via APIs, off-the-shelf LLMs, or fine-tuned internal deployments.

So the risk has shifted downstream. Prompt injection, data leakage, model exploitation, and inappropriate outputs—all of these occur at the inference layer. This is the point where AI is actually interacting with your people, systems, and data. And it’s where your controls need to live.

The good news is that we can draw on familiar principles here: visibility, access control, anomaly detection, and policy enforcement. The challenge is in adapting these principles to a dynamic, probabilistic technology that was never designed with enterprise-grade security in mind.

There’s no one-size-fits-all answer. The right AI security strategy depends on your industry, regulatory landscape, data sensitivity, and risk appetite. Financial services may prioritize auditability and model behavior controls. Healthcare needs confidence that PHI isn’t leaking through generated outputs. Global manufacturers have to worry about IP theft across jurisdictions.

That’s why CISOs must step into a more strategic role in AI governance. We are uniquely positioned to translate security requirements into business language, help set acceptable use policies, and ensure that oversight mechanisms are in place from the start.

But that requires being in the room early—before pilots turn into production rollouts, and certainly before anything customer-facing goes live.

We talk a lot about AI “hallucinations” and biased outputs, but even the most secure model can’t replace human judgment. AI doesn’t understand intent. It doesn’t understand consequences. It’s pattern recognition at scale.

Security teams need to be involved in establishing thresholds, escalation paths, and intervention protocols. Just like in traditional cybersecurity, AI systems need monitoring—but they also need someone with context and judgment to step in when something doesn’t look right.

This is not just a tooling problem. It’s a cultural one. And that means building awareness across the enterprise—not just within the SOC.

As CISOs, we are being asked to chart a course through uncharted waters. It’s not enough to understand the threats—we need to shape the response. That means:

If we do this right, security becomes the foundation that enables AI—not the bottleneck that holds it back.

The speed of AI innovation isn’t slowing down. Neither can we.