FloQast study finds AI leaders close books two days faster

FloQast has published research showing that finance teams with the most advanced use of artificial intelligence close their books two days faster than those at the earliest stage of adoption, pointing to a widening gap in accounting operations.

The State of Accounting AI 2026 report found that the most AI-mature teams complete the monthly close in 6.7 days, compared with 8.7 days for the least mature. It also found that the most advanced teams spend 34% of their time on manual work, versus 63% for teams just starting to use AI.

The survey covered accounting and finance professionals in the UK and US and grouped respondents into five levels of AI maturity. Only one in 10 finance teams reported extensive use of AI across accounting workflows, even though 85% said leadership views AI as a strategic priority.

That disconnect runs through several parts of the research. While 92% of finance decision-makers expect AI investment to rise over the next two years, only 17% believe their teams are ready to use that investment effectively.

Account reconciliation stood out as the area where finance leaders see the biggest opening for AI. Some 55% of respondents identified it as the main opportunity, yet only 5% reported a high level of automation in that process.

The report suggests a small group of organisations is moving beyond pilot projects and isolated uses of AI. Among the most advanced organisations, 69% are actively executing an AI roadmap and 95% are already embedding AI into the month-end close.

By contrast, many teams still appear to be working with weak process foundations. The research found that 51% of finance teams said their financial controls are either informal or inconsistently applied across the close process.

Process gap

The difference between leaders and laggards is not just access to software. The report argues that stronger performers are documenting workflows, applying governance and introducing AI into repeatable accounting processes rather than layering tools onto existing routines.

That distinction matters because the monthly close remains one of finance's most time-sensitive responsibilities. Any reduction in manual effort can affect staffing demands, reporting timetables, and the time available for review and analysis.

Hugh O'Neill, Principal, Accountant in Residence at FloQast, said finance teams have moved past the question of whether to adopt AI.

"For the past few years, the conversation has centred on whether finance teams should adopt AI, but that question is now largely settled. The real issue is that most organisations still haven't figured out how to use it effectively.

"A small group have already changed the way they work and are seeing clear gains in speed, efficiency and capacity. Too many organisations, however, are simply layering AI onto existing processes instead of redesigning those processes around what AI can do. That limits the impact they're able to achieve.

"That gap is no longer theoretical. It's already showing up in how quickly teams can close, how much manual work they're doing, and ultimately how much value finance teams can create."

Adoption hurdles

The findings add to a broader debate over whether corporate AI spending is producing measurable changes in back-office functions. Finance has often been seen as a practical test case because so much of the work depends on structured processes, regular deadlines and auditable records.

Yet the data suggests many organisations have not built the controls and standardisation needed to support wider use. Teams in the early stages of adoption are more likely to be dealing with inconsistent workflows, making it harder to apply AI tools across the close process.

The report recommends that those organisations first document and standardise workflows, strengthen financial controls and establish clearer governance. For more advanced teams, it points to redesigning additional workflows around AI while maintaining human oversight and traceability.

One FloQast user described the operational effect of that approach in practice.

"AI isn't something you buy your way into - it's something you build toward," said Jonathan Mears, VP of Finance and Accounting at Liquid AI.

"We made thinking about AI our default way of working, and with FloQast, that mindset snowballed into massive time savings through thoughtfully documented processes and reliable change management. The result is a faster, more consistent close, far less manual prep, and a team that spends its time reviewing and analysing instead of preparing. It elevated our accountants; it didn't replace them."