New whitepaper commissioned by Sage reveals that seven in ten finance leaders will reject AI outputs they cannot explain, highlighting the need for more transparent, accountable AI.
London, 6 July, 2026 - Sage, the leader in accounting, financial, HR and payroll technology for small and mid-sized businesses (SMBs), today announced new research revealing that 71% of finance leaders would reject an AI tool that was 99% accurate if it could not explain its answers.
The findings from The Emerging Economics of AI in Finance white paper suggest that explainability is becoming a critical requirement for AI adoption in finance, as organisations seek greater confidence, control and accountability over AI-generated outputs.
Surveying over 2000 senior finance decision-makers globally, the research found that more than half of organisations would be willing to pay more for AI solutions that provide greater visibility into how decisions are made. The findings indicate that explainability is becoming an increasingly important factor in how organisations evaluate AI.
"In finance, almost right has always been wrong. As AI takes on more complex financial workflows, the cost of uncertainty is simply too high," said Aaron Harris, CTO at Sage. "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.”
Key findings from the research include:
From black box to glass box AI
The findings point to a broader shift away from traditional Black Box AI systems, where outputs are difficult to interrogate, towards more transparent glass box approaches that provide visibility into the reasoning, sources and logic behind AI-generated recommendations. Reflecting this trend, 71% of finance leaders say a vendor’s shift to Glass Box design principles would strongly or critically elevate their status as a preferred partner.
In response to growing demand for transparency and auditability, Sage’s approach to AI in finance is built on trust by design – with AI that finance teams can interrogate, govern and rely on, with explainable and verifiable outputs, controlled actions, and complete traceability of every AI-driven decision. By embedding transparency and auditability into its AI capabilities, Sage is enabling finance teams to act with greater confidence, control and accountability.
Kevin Permenter, Research Director, Financial Applications at IDC, added: "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.”
To read the full IDC White Paper, sponsored by Sage, The Emerging Economics of AI in Finance, visit https://sage.com/economics-agentic-ai.
Methodology
IDC conducted a custom survey of 2,275 senior finance decision-makers and influencers across North America (63%) and EMEA (37%) in February 2026. The survey was conducted via CAVI (phone interview) and spans 17 IDC verticals, focusing on companies with 20 to 1,999 employees.
About Sage
Sage exists to knock down barriers so everyone can thrive, starting with the millions of Small and Mid Sized Businesses served by us, our partners and accountants. Customers trust our finance, HR and payroll software to make work and money flow. By digitalizing business processes and relationships with customers, suppliers, employees, banks and governments, our AI-powered platform connects SMBs, removing friction and delivering insights. Knocking down barriers also means we use our time, technology and experience to tackle digital inequality, economic inequality and the climate crisis.
