The evolving role of AI in finance for 2026

Aqilla's research highlights increasing confidence in AI's role in finance, as manual work bottlenecks reduce through automation and governance.

New research findings from Aqilla, a cloud-native accounting and reporting application company, reveal that finance teams are poised for 2026 with clarity on AI's organisational benefits.

Conducted at Aqilla's recent user conference, the research indicates a shift in perspective: three-quarters of finance leaders are keen on expanding automation, while 83% remain optimistic about AI's positive impact on finance processes. This marks a notable change from 2024, when less than two-thirds saw AI as a means to expedite accounting and reporting tasks.

Understanding AI Improves

Among respondents, only 8% now feel apprehensive about AI, a marked reduction from the prior year where 20% expressed discomfort with the technology. Finance teams seem to be moving past debates over AI's relevance, integrating it more seamlessly into everyday tasks. Indeed, data entry and imports emerge as major bottlenecks for 40% of participants, emphasising the manual workload these teams bear.

The findings suggest that, as AI-related concerns diminish, there's a growing inclination to offload routine, rule-based tasks to AI-enabled solutions. Many finance teams are transitioning from experimental phases to broad, consistent implementation.

Optimising AI Use

While finance professionals like Charis Thomas, Aqilla's Chief Product Officer, maintain cautious optimism, they advocate for AI that relieves repetitive tasks without compromising human oversight. Customers "aren’t ready to hand everything over to AI – and neither should they be at this stage. They’re more discerning. They want AI-enabled solutions that remove repetitive work and improve accuracy," explains Thomas. Finance leaders seek automation that supports decision-making, maintaining transparency and accountability.

Looking ahead to 2026, AI is anticipated to shoulder mundane tasks, such as capturing data or suggesting classifications, while preserving user control to intervene, pause, or reassess processes as needed. The focus is not just on technology, but also on governance and upskilling, ensuring AI deployments bolster decision-making under pressure.

In conclusion, as Aqilla's findings suggest, the equilibrium between automation and human oversight will be pivotal for finance teams scaling AI usage, encouraging responsible applications and beneficial, informed decision-making even when deadlines are tight.

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