Gartner Says CFOs Must Pilot Governance First Before Scaling AI Agents

As finance teams begin to deploy AI agents, CFOs face a critical decision between focusing on immediate returns or prioritizing governance and oversight. The risks and opportunities of AI agents are fundamentally different from previous automation waves in finance.

We spoke with Alex Levine, Director Analyst in the Gartner Finance practice, who provided insight on how finance leaders should get started with AI agents.

Journalists who would like to speak with Alex regarding this topic can contact Heather Sabharwal. Members of the media can reference this material in articles with proper attribution to Gartner.

A: AI agents are riskier in finance because they act with greater autonomy. Unlike traditional automation, which follows fixed rules, or GenAI, which generates content, AI agents interpret objectives, plan and execute steps, and interact with multiple systems.

This autonomy means agents can make decisions and take actions that may not be visible or easily explained to humans. It also means errors or misjudgments can propagate quickly if oversight is unclear. Finally, the risk shifts from just the output to the entire process, making governance and traceability essential.

A: The greatest risks and the greatest value lie in establishing oversight, not in chasing quick financial gains. Early pilots are most likely to fail due to unclear controls, not poor technology.

By prioritizing governance, CFOs can surface and address gaps in oversight, traceability, and review processes before scaling to use cases with higher stakes. This approach ensures that future AI deployments are built on a foundation of robust, auditable controls, protecting both the organization and its stakeholders.

A: CFOs should begin with a low risk, contained workflow where errors are visible and reversible. The ideal pilot:

• Involves a process with clear boundaries, repeatable steps, and verifiable outputs
• Avoids high-consequence processes, such as those requiring restatement or regulatory reporting
• Establishes agent boundaries, including data access, allowed actions, and required human review, before any development begins
• Assigns clear ownership across finance, IT, and audit/risk teams
• Operates in a sandboxed environment to observe and learn from agent behavior without operational exposure

This approach allows finance leaders to refine governance frameworks and build confidence before expanding to more critical areas.

A: Success should be measured by governance readiness, not just autonomy or ROI. Key indicators of a successful agent pilot include practical and consistently applied controls and review points and achieving complete traceability of agent actions.

Another critical milestone is maintaining a comprehensive failure log that documents issues and fixes. The finance team should be able to reconstruct what the agent planned, accessed, and produced for every run.

Successful AI agent pilots should deliver templates and training that reduce the risk and cost of future deployments, as well as reusable governance capabilities that enable safe, scalable AI adoption.

Additional Insights Available
Additional information is available to Gartner clients in A CFO’s Guide to Building a Finance AI Agent. Non clients can read The CFO Report.