Finance pros boost productivity with AI but face ROI doubts

Research from fintech company Emburse has found that finance professionals in the UK and US are adopting artificial intelligence (AI) with a focus on productivity and business value, while many grapple with how to measure its return on investment (ROI).

The report, ",AI-Powered Finance: New Practices, ROI and Future Outlook", surveyed 1,500 finance professionals and indicated that 66% of organisations have invested in AI, but the majority are still evaluating the most effective way to quantify its benefits.

According to the findings, finance departments report using AI on average 3.7 times per day, with 37% of their daily tasks now driven at least in part by AI. Respondents anticipate that in the next five years, AI will have its greatest impact on processes such as planning and forecasting, with 26% identifying this area as most likely to be transformed.

Marne Martin, Chief Executive Officer of Emburse, commented: "Expense Intelligence is about moving from reactive expense tracking to real-time, strategic visibility. This report confirms what we're hearing from finance leaders every day — they're ready to turn AI into business value. But it requires connecting spend data, automation, and decision-making in a unified way."

While adoption is increasing, finance professionals also cite key concerns associated with AI. Of those surveyed, 24% said data security and privacy risks were their primary worry, followed by the potential for AI to make errors (18%), the impact on finance roles (18%), and compliance and regulatory challenges (10%). Nearly a quarter (23%) of respondents said they would consider leaving their job if they felt their employer was not taking sufficient precautions to manage AI-related risk.

Despite these challenges, the prevailing sentiment is that AI investment is meeting expectations: 74% say that their company's ROI on AI either meets or exceeds what was anticipated. When asked which finance functions AI performs with the highest ROI, respondents cited automating accounts payable and receivable (26%), forecasting or budgeting (26%), and fraud detection (25%).

Adriana Carpenter, Chief Financial Officer of Emburse, stated: "Finance teams aren't hesitant to use AI. They're embracing it cautiously and with the same rigorous, analytical mindset they apply to every strategic initiative. What's transformative is how this mindset is redefining the very notion of value. By focusing on the integrity of how business outcomes are achieved with AI, finance leaders are creating more resilient, data-driven workflows that elevate both business performance and team alignment."

Carpenter continued: "For AI to deliver on its revolutionary potential, it must be designed with the specific needs of finance leaders in mind. That means it should be purpose-built, dependable, and able to drive measurable business impact at scale."

How organisations choose to measure the ROI of AI varies widely. Some companies look to traditional financial metrics such as cost savings, fraud reduction, and revenue growth. Others assess operational efficiency metrics like time savings or increased automation. A further group instead relies on more qualitative indicators such as improved customer or employee satisfaction post-AI implementation.

Among respondents, 81% reported that the process of measuring AI ROI has altered how they assess business costs organisation-wide, from software procurement to vendor partnerships. In particular, 53% now emphasise traditional financial or operational efficiency metrics, 30% focus on long-term strategic impacts, and 27% have adopted real-time, adaptive evaluation frameworks.

The study suggests this shift in evaluation has marked a move from static cost analysis to a more dynamic, ongoing assessment of value—a development that could influence how investment decisions are made across sectors as AI adoption continues.

The survey, conducted by Talker Research between March 24 and 31, 2025, included 1,000 US and 500 UK finance professionals, ensuring a broad perspective on trends and sentiment towards AI in finance.