AI in Finance Report 2026: Rillion Study Reveals AI Adoption Gaps and Trust Deficit

A new study from Rillion reveals a significant trust gap in U.S. finance departments, where 68% of teams use AI daily but only 39% of CFOs trust the technology to operate without human oversight. This disconnect suggests that while adoption is high, manual intervention remains a critical bottleneck for fintech leaders seeking true automation.

What was announced

Rillion released its 2026 AI in Finance Report, a study conducted in collaboration with Sapio Research that surveyed 250 CFOs and finance leaders across the United States. The report identifies four primary friction points—trust, skills, automation, and transformation—that are currently preventing widespread AI adoption from translating into genuine operational change.

The data highlights a persistent reliance on manual processes, particularly within accounts payable. Despite the proliferation of AI-driven tools, nearly nine in ten CFOs reported shortcomings with their current invoice capture and data extraction solutions. Furthermore, 45% of respondents confirmed that human review is still required after invoices have been processed, indicating that automation often remains a hybrid process rather than a fully autonomous one.

The report also identifies a potential skills blind spot within the industry. While 60% of finance leaders believe that proficiency with AI tools will become one of the most important skills in finance, only 21% currently view a lack of internal AI expertise as a major barrier to adoption. Interestingly, the study found that teams already using AI widely are more than three times as likely (51% vs. 16%) to expect the technology to transform most finance processes compared to those at the beginning of their journey. The research includes perspectives from experts at several major organizations, including GitHub, Meltwater, Docusign, Foxit, Joe & The Juice, and the CFO Alliance, to provide a broader view of how these gaps manifest across different sectors.

"AI has moved incredibly quickly from something finance leaders were experimenting with to something many teams now use every day. But adoption alone doesn't mean transformation. The interesting part of this research is the gap between how ready finance looks on paper and what's happening underneath. Trust, skills and manual work are still holding many organizations back."

Daniel de Sousa, CEO of Rillion.

The companies involved

Rillion is a Stockholm-headquartered provider of AI-powered accounts payable (AP) automation and payment solutions. With more than 30 years of experience in the AP automation space, the company supports over 30,000 organizations globally, maintaining operations across the United States and the EMEA region. Rillion’s core product suite focuses on streamlining the entire financial lifecycle from initial invoice capture through to final approval and payment. The company’s leadership includes CEO Daniel de Sousa and Chief Marketing Officer Frida Ahrenby.

The report features contributions from a diverse group of market participants, reflecting the cross-industry nature of AI integration. These include GitHub, the software development platform; DocuSign, a leader in electronic signature and agreement management; and Meltwater, a global provider of media and social intelligence. Other contributors include Foxit, the PDF and e-signature software provider, and JOE & THE JUICE, the international juice bar and coffee chain. The research was executed by Sapio Research, a specialist market research agency, and includes insights from the CFO Alliance, a professional network for senior finance executives. This collaborative approach combines quantitative survey data with qualitative insights from leaders who are actively implementing these technologies in high-volume environments.

What FF News has reported before

FF News has recently covered several developments in the AI and fintech space that mirror the trends identified in Rillion's report. This includes the launch of Ant International Launches FalconTST 2.0: A New SOTA Benchmark for Predictive AI in Finance, which addresses the need for more accurate predictive models in the sector. Additionally, the industry has seen warnings about the practicalities of implementation, such as when FinregE Research Warns Regulated Firms Against the Hidden Costs of In-house AI Infrastructure. Security remains a parallel concern for finance leaders, highlighted by the release of Prem AI Launches CyberScan: Continuous AI Security Audits for Bitcoin Infrastructure. Finally, the scale of investment in the sector continues to grow, as seen when Socure Hits $5.2B Valuation with Strategic Investment and Fravity Acquisition.

What this means

The findings suggest the fintech sector is entering a plateau of productivity where the novelty of AI has worn off, leaving finance leaders to grapple with the unglamorous reality of data accuracy and workflow integration. The 45% manual review rate for "automated" invoices is a damning indictment of current legacy-plus-AI solutions; it puts pressure on pure-play AI vendors to prove their reliability beyond simple pilot programs. For the wider industry, the real competition is no longer about who has AI, but who can build enough trust in their models to remove the human-in-the-loop requirement that currently prevents true scalability in the back office.