First, the AI Exposure Snapshot shows you exactly where you stand — every system, scored, with a named list of what cannot be signed off. In two to four weeks you have the security map you don’t have today.
What’s live today
What’s running without you
AI didn’t enter your enterprise through a single front door you controlled. It arrived in pieces — a copilot a product team shipped, an agent embedded in a workflow, a vendor model three layers deep in a process. Each one makes or influences decisions. Most of them never crossed your desk.
When the CAIO and Chief Risk move to sign one of these systems off, the security question lands on you: does it hold up under attack, and can we prove it? Right now, for most of these systems, you do not have the answer.
Whose problem this is
Why this is your exposure, not engineering’s
Those are different jobs. A model can function perfectly and still fall to a hostile prompt, a poisoned input, or an unguarded tool call — with no record that anyone ever probed for it. When the Chief Risk officer asks for the security evidence behind a sign-off, “the engineers tested it” is not an answer you can co-sign. You need adversarial proof that exists in a form the rest of the coalition will accept.
Engineering owns whether the system works. You own whether it holds up when someone tries to break it.
The five questions
What you cannot currently defend
For each AI system heading for sign-off, ask whether you could co-sign these tomorrow:
Has anyone tested how it fails — adversarially, not just for accuracy?
Can a person stop it mid-action when an attack is in progress?
Is there a record of the red-team work an auditor would accept?
Are its tool calls, inputs, and escalation paths guarded against abuse?
Is its behaviour watched now, or was it checked once at launch?
How we close it