When AI Starts Making Decisions: The Risk CFOs Can't Ignore

Artificial Intelligence has now moved beyond answering questions and generating content pieces. A new generation of AI, called agentic AI, is here. It can now set its own goals, create plans, execute actions, and make decisions inside the live business without any human intervention. Several large enterprises are already testing and training agentic AI to take over customer service, procurement, and internal operations.

According to Deloitte's 2026 State of AI in the Enterprise report, 74% of the global organisations are expected to use AI agents by the year 2027. Yet only 21% of those same organisations have a mature plan ready to manage what those AI agents can do.

Most finance leaders are used to managing risk created by people. Agentic AI introduces a different challenge. For the first time, organisations are beginning to deploy systems that can make decisions, take actions, and interact with business processes without waiting for human approval at every step.

The technology promises efficiency. But it also raises a practical question many organisations are still working through: Who is accountable when an autonomous system makes the wrong decision? That question becomes more important as agentic AI moves from experimentation into day-to-day operations.

Deloitte's CFO Guide to Tech Trends 2026 report has identified an obstacle that is preventing enterprises from realizing agentic AI’s true potential. Most CFOs have spent years building controls around human decision-making. Agentic AI introduces a new challenge: decisions may now be made by systems that operate continuously, at a scale humans cannot easily review. And this is not a technology problem. It is a structural problem and structural risk within the CFO’s remit.

The enterprises and CFOs who will get ahead of this will not be the ones who will slow down their AI adoption. They will be the ones who will treat their governance as a financial discipline, and not just a legal formality.

That means answering some critical questions like:

• What AI decisions will require human sign-off?
• What happens when an autonomous system causes a financial or compliance failure?
• Who in the organisation owns that outcome? 

These questions affect risk management, compliance, and financial accountability across the organisation . Agentic AI has the potential to improve and automate. But the value doesn’t come without cost, and the cost of doing something wrong without a plan, financially, legally, or reputationally, can affect the company's profits. Long-term success will depend not only on AI adoption but also on the governance structures that support it.