Cybersecurity
What executive teams must govern now — AI is changing both sides of the security equation at once.
Lori Priller · 4 min read
AI is not just another category on the enterprise risk register. It expands the attack surface — through the data pipelines that feed models, the third-party APIs many AI tools depend on, and employees pasting sensitive information into consumer AI tools that were never sanctioned or reviewed — while simultaneously offering real gains in detection and response, if governed properly. Executive teams that treat it as one-sided in either direction are exposed.
Long before an enterprise rolls out sanctioned AI tools, employees are already using unsanctioned ones — and often routing sensitive data through them in the process. Most organizations don't have visibility into how widespread that is, let alone a policy that employees have actually seen. Closing this gap is rarely about banning tools outright; it's about giving people a sanctioned path that's good enough that the unsanctioned one stops being tempting.
Prompt injection, data leakage through model outputs, and adversarial manipulation of AI-driven decisions don't map cleanly onto existing security playbooks. If no one owns these risks by name, they default to being no one's responsibility until an incident forces the question. Executive teams should be able to answer, today, who owns each of these categories.
Three things worth resolving before they get raised as a question in an audit: an inventory of where AI is actually touching sensitive data (sanctioned or not), clear ownership for AI-specific security risk, and a policy employees have actually been trained on, not just emailed.
This is the focus of our AI-Powered Cybersecurity advisory work, and of our executive training curriculum.
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