The figure comes from a whitepaper commissioned by Sage that surveyed over 2,000 senior finance decision-makers globally, including 410 in the UK. The headline finding undercuts the standard AI productivity argument: rather than reducing manual work, AI has shifted it. Finance professionals are not freed from oversight; they are now auditors of AI decisions they cannot always interrogate.
Explainability has become the deciding factor in purchasing. The research found that 73% of UK finance leaders would refuse an AI tool with 99% accuracy if it could not produce a human-readable reasoning trace. More than half — 50.7% — said they would pay more for AI that provides greater visibility into how outputs were reached.
The study identifies a shift in how finance organisations think about AI architecture. Black Box systems, where the output appears without explanation, are losing ground to what the report calls Glass Box alternatives, built with transparency, traceability, and human-readable reasoning. Seventy-one percent of finance leaders said a vendor's adoption of Glass Box design principles would strongly or critically elevate that vendor's standing as a preferred partner.
Aaron Harris, CTO at Sage, said: "This research shows that the next era of AI won't be won on raw model intelligence alone; it will be won on trust infrastructure. Finance teams cannot afford to spend hours playing detective with black box AI outputs. They need solutions that bring transparency, control, and traceability into the systems behind its outputs, so they can execute with absolute confidence."
IDC Research Director Kevin Permenter put it in terms of competitive positioning: "The organisations that will achieve the most durable AI advantage are those that reframe trust infrastructure not as a constraint on AI deployment, but as the foundation on which scalable AI is built. Organisations have a choice, act early to operationalise trust or risk becoming overwhelmed by verification overhead."
One data point from the study captures the stakes: 47.8% of UK finance professionals spend more than 15 hours weekly on verification, and 21.2% spend more than 30 — approaching the hours a part-time employee would log in a week. When AI creates work rather than removing it, the business case for deployment narrows considerably.
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