A year ago, "AI in the boardroom" mostly meant a chatbot that drafted minutes. That conversation has moved on. Agentic AI — systems that plan, decide, and take actions with limited human involvement — now accounts for roughly 27% of all generative-AI automation, up from about 4% a year earlier. When software starts acting on its own, governance stops being a model-quality question and becomes an accountability question.
Boards have noticed. Among large companies, the share citing AI risk explicitly in their oversight remit roughly tripled in a single year.
The accountability gap
The problem is that oversight has grown faster than the controls underneath it. Most organisations have not written down how their agents are allowed to behave, who owns them, or what happens when one acts outside its lane.
Traditional AI governance asks whether a model is accurate and fair. Agentic governance has to answer a harder set of questions: what is this agent allowed to do, what is it allowed to touch, and who is responsible when it does something nobody intended? The answer has to be defined, inventoried, owned — and auditable.
Why the Gulf is ahead of the question
The Gulf is not waiting for this to become a Western compliance story. Saudi Arabia declared a Year of AI, and its regulator has been busy.
That raises the bar for assurance. A board that has to show human oversight needs a function that can independently confirm it exists — not a slide that asserts it.
What internal audit should do now
This is squarely internal audit's territory. The function that gives the board independent assurance over everything else is the natural place to assure the organisation's agents. In practice that means:
- Inventory the agents. You cannot govern what you have not listed. Maintain a register of autonomous systems, what they can access, and who owns each.
- Define the guardrails. Goal alignment, scope limits, and a clear answer to "what is this agent never allowed to do."
- Keep a human in the loop. Audit trails on agent actions and a human override on consequential decisions — and evidence that both are real.
- Assure, don't just advise. Periodically test that the controls operate, and report coverage and gaps to the committee.
The pattern that holds up
The organisations getting this right apply one principle consistently: let AI do the work, but never let it make the call that requires accountability. That is the same logic behind VistaAssist, the AI layer in ControlVista — it drafts across the audit lifecycle, runs inside your perimeter, and never decides, signs off, or acts on its own.
Agentic AI will keep getting more capable. The governance frontier is not the model — it is the boundary you draw around what it is allowed to do without a human.