Most Finance Teams Use AI, but Few Have Built It Into Core Work
Two-thirds of finance teams are using or testing AI tools, but only one in ten have embedded the technology into their everyday processes, according to a survey of 500 finance professionals by software vendor Yooz. The gap between experimentation and operational deployment suggests that finance leaders have significant room to move AI from pilot projects into regular workflows.
The research, released in May 2026, found that 22% of finance teams are not using AI at all. Among those who are, accounts payable automation, fraud detection, and financial reporting are the most common applications.
Reporting and Analytics Lead, But Fraud Detection Is Next
Forty-three percent of finance professionals say their teams currently use AI for reporting and analytics. This early adoption makes sense: outputs are easy to generate and validate quickly. Forecasting and financial planning follow at 27% adoption.
Fraud prevention, audit, risk, and compliance represent an emerging opportunity. Only 19% of respondents currently use AI in these areas, even though AI can flag unusual vendor behavior and spot suspicious transactions in high-volume workflows.
About one-third of survey respondents believe AI is already built into more of their processes than they initially realized, typically running in the background through invoice processing and risk monitoring tools.
Confidence Is Growing, but Trust and Training Lag
More than half of finance professionals-53%-report feeling more confident using AI than a year ago. Forty-two percent describe themselves as "curious but cautious," while 26% say they feel excited and confident.
The biggest obstacles to wider adoption are not cost or regulation. Instead, 26% of respondents cite lack of training and education as the primary challenge, followed closely by concerns about trusting AI-generated results at 25%. Only 12% point to regulatory or compliance concerns, and 10% say budget is the main barrier.
Leadership remains fragmented. IT and technology teams lead AI adoption efforts in 24% of finance departments, compared with just 13% where CFOs or finance executives are driving the work. Another 22% say no one is clearly leading AI adoption.
Embedding AI Into Shared Workflows Builds Trust
Finance teams see the best results when AI is built directly into existing processes rather than treated as a separate tool. When AI flags duplicate invoices or unusual vendor behavior within a standardized approval workflow, every transaction gets screened consistently before payment. This reduces manual review time and strengthens controls.
The report calls this state "Lean Financial Operations"-a condition in which team members spend less time on repetitive tasks like fixing invoice errors, re-entering data, and resolving mismatches. Instead, they focus on oversight and analysis.
Turning curiosity into consistent adoption requires standardizing processes, automating what is repeatable, and building controls into daily operations. Finance leaders should focus on practical operational efficiency rather than AI hype, the research suggests.
For finance professionals looking to build expertise in this area, resources on AI for Finance and the AI Learning Path for CFOs offer structured guidance on implementation and strategy.
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