As AI rapidly proliferates in enterprise environments, finance leaders face pressure to adopt tools that boost productivity and efficiency. Although agentic AI has the potential to transform financial workflows, faster output is not the CFO's only priority—they are also accountable for decisions, control, and consequences.

This makes trust a defining requirement for AI adoption in finance. CFOs need to know not only what AI produces, but also how it arrives at results, whether those results can be verified, and who is ultimately responsible for decisions.

How AI drives productivity and efficiency in finance teams

AI's ability to replace manual data entry presents a significant opportunity to streamline financial workflows. In particular, AI models can read, understand, and classify information in financial documents at remarkable speed. Aaron Harris, CTO of Sage, says, "AI may not be as accurate as humans, but it is always more efficient than humans."

Finance teams are increasingly exploring AI to support functions such as reconciliation, forecasting, and anomaly detection. AI can also help fill hiring gaps caused by talent shortages in the accounting profession in recent years.

Advanced AI solutions and agentic capabilities have already helped finance teams accelerate key processes. According to Harris, an agricultural business in Maine reduced invoice processing time by one-third to one-half after implementing Sage's AI solutions. The company also uses AI to better understand supplier performance and relationships.

For CFOs, these benefits are significant. But they also raise a critical question: How can finance teams move faster without sacrificing the accuracy, control, and accountability their work requires?

Trust is paramount for CFOs

Accounting systems contain audit trails that allow reviewers to discern who performed the work, and human professionals can explain how they arrived at final figures and conclusions. General-purpose AI models do not offer this transparency or explainability.

This lack of transparency has created friction. New research from Sage and IDC finds that 71% of finance leaders would reject AI outputs they cannot explain, even if those outputs are accurate. Finance professionals spend an average of 12.9 hours per week reconstructing, verifying, and defending AI outputs, while 26% of potential AI time savings is spent on verification, explanation, and reconstruction. In other words, opaque AI does not eliminate work for finance teams—it simply shifts the work to verification and explanation.

Given the high stakes of the work, CFOs should lean toward keeping humans involved in reviewing AI outputs. "AI will never be 100% accurate," Harris explains.

Additionally, CFOs need to ensure that the financial data fed into AI models remains private and secure. In other words, CFOs needAI they can trust: systems that are explainable, governed, auditable, and built for financial realities.

What is finance-grade AI?

For finance leaders, the goal is not just more powerful AI, butmore transparent AI: moving from "black box" systems to "glass box" AI, where outputs can be explained, verified, and challenged before teams act on them. Finance-grade AI has three pillars:

  1. Confidence:Results are explainable, verifiable, and can be challenged.
  2. Control:Humans remain in charge, and key actions require approval.
  3. Accountability:Every action is traceable, including who initiated it, what the agent did, who approved it, and what changed.

"When humans make mistakes, they make them at human speed. When agents make mistakes, they make them at AI speed. And things can go wrong very, very quickly," Harris says. Therefore, all the governance and controls that apply to human users must also apply to AI agents.

Adopting finance-grade AI also requires a shift in how human team members work. "Not every employee has to become a data scientist," Harris says. Instead, professionals should receive foundational training on how AI models work, the potential risks of using them, which tasks are best suited for AI, and how to prompt and interact with agents to achieve optimal results.

As AI becomes increasingly embedded in financial workflows, professionals will increasingly move from manually executing every step to reviewing, verifying, and guiding the work. This shift does not reduce accountability—in many ways, it increases it. As this dynamic technology evolves, CFOs who prioritize balancing speed with trust will be able to succeed in the AI era.