Two thirds of finance teams are already using or piloting artificial intelligence, but only 10% say it is embedded in their core processes. That divide between widespread experimentation and operational integration is the defining finding of the Yooz 2026 AI in Finance Report, a survey of 500 finance professionals conducted in January 2026 in partnership with the third-party survey platform Pollfish.
The numbers tell a story of a function on the precipice of major change. Adoption is no longer the challenge. The question now is whether finance teams can build on that early momentum to transform how they operate, moving beyond efficiency gains to become a genuine strategic partner to the business.
Efficiency Is Just the Start
For years, the promise of finance technology has been framed primarily around efficiency. Faster approvals and shorter close cycles are only part of the picture. The more compelling opportunity that the Yooz data points toward is what becomes possible when AI is embedded deeply enough to change not just how finance teams work, but what they’re able to do.
The distinction is important. Doing things better means processing invoices faster and catching duplicate payments before they clear. Doing better things means having the real-time cash visibility to advise the CEO on a capital allocation decision, or the fraud intelligence to proactively flag vendor risk before it becomes a loss. Whereas doing things better is an operational improvement, doing better things is a strategic capability.
More than half of respondents — 53% — say they’re more confident using AI than they were a year ago. That growing familiarity is the foundation for the change in perspective. As finance professionals become more fluent with AI tools, the ceiling on what they can contribute to the business rises. The goal isn’t to automate the finance function out of relevance, but to liberate it from the low-value work that has historically consumed its capacity.
Reporting Is a Starting Point, Not a Destination
The survey finds that 43% of finance teams are already using AI in reporting or analytics, making it the most common entry point. Forecasting and financial planning follows at 27%. These are meaningful starting points, but they reflect only a fraction of what embedded AI can deliver.
At the other end of the spectrum, only 19% of teams say they use AI for audit, risk, compliance, or fraud detection. Only 18% are applying it in accounts payable or receivable. These are precisely the areas where AI can do the most to strengthen the finance function’s role as a control center and strategic asset, and where the gap between current adoption and full potential is widest.
Closing that gap requires a broader strategic framework that connects AI deployment to the outcomes finance leadership actually cares about. That means better cash management, stronger controls, faster and more accurate forecasting, and a finance team that spends more of its time on insight and less on reconciliation.
The Barriers Are Internal — and Solvable
What’s holding teams back isn’t primarily cost or regulatory pressure. The survey is clear on this: 26% cite lack of training or education as the top barrier, and 25% point to lack of trust in AI outputs. Budget constraints register at just 10%. Compliance concerns come in at 12%.
This is actually encouraging news because it means the biggest barriers are internal operating conditions. Unlike market forces or regulatory uncertainty, they’re within the organization’s control. Building AI literacy across finance teams, establishing clear standards for how AI outputs are reviewed and applied, and creating governance frameworks that instill confidence in the technology are all achievable with the right investment and commitment.
Finance teams can achieve these goals by treating AI enablement as a strategic priority rather than an IT implementation project. Education should go beyond product training to help teams understand what AI is doing inside their workflows, and how to interpret and act on the insights it provides.
Finance as Strategic Partner
Perhaps the most important evolution the data points toward is a change in how finance leadership thinks about its role. The modern CFO is no longer just the steward of historical data and budget oversight. Finance has the opportunity to be the function that gives the business the clearest, most accurate picture of where it stands and where it’s headed.
That ambition requires a different kind of finance infrastructure. AI should be deeply embedded into the workflows that generate financial data, fraud detection is built into the payment process, and AP automation gives leadership a live view of cash commitments.
Only 13% of respondents say the CFO or VP of Finance is the primary driver of AI adoption in their organization. IT leads at 24%, and 22% say no one in particular is steering it. That needs to change. When finance leadership is actively involved in the AI agenda, it strengthens coordination and helps tie outcomes more directly to business performance.
