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Finance Leaders Demand AI Transparency as 71% Reject Unexplained Decisions

New white paper commissioned by Sage reveals that seven in 10 finance leaders will reject AI outputs they cannot explain, highlighting the need for more transparent, accountable AI

ATLANTA (July 6, 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 organizations seek greater confidence, control and accountability over AI-generated outputs. 
 
Based on a global survey of more than 2,000 senior finance decision-makers, including 832 respondents in the U.S., the research found that more than half of organizations 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 organizations 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 their outputs, so they can execute with absolute confidence.” 
 
Key findings from the research include: 

  •  The rise of the "Verification Tax": Finance professionals spend nearly 13 hours every week reconstructing, validating and defending AI outputs. In the U.S., nearly half (49%) spend 15 or more hours a week on verification, while almost one in five (19%) spend 30 or more hours. 
  • Accuracy alone is not enough: 71% of finance leaders would reject a 99%-accurate tool if it could not explain its answers, signaling that auditability and reasoning traces are becoming essential in high-stakes finance workflows. 
  • Finance teams are becoming AI’s trust layer: When asked what skills mattered most for a finance leader hired today, U.S.-based respondents placed risk, governance and decision judgment first (32%), valuing it nearly twice as highly as deep technical accounting (17%).  
  • Transparency is becoming a vendor selection factor: More than half of organizations (54%) would pay a premium for AI that provides greater visibility into how outputs are generated, signaling that explainability is becoming a procurement requirement, not just a product feature. 


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, toward more transparent glass box approaches that provide visibility into the reasoning, sources and logic behind AI-generated recommendations. 

This shift is becoming a business requirement, not just a technical preference. Seventy-one percent of finance leaders say a vendor’s shift to Glass Box design principles would strongly or critically elevate its 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 organizations 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. Organizations have a choice: act early to operationalize trust or risk becoming overwhelmed by verification overhead.” 
 
To read the full IDC White Paper, sponsored by Sage, visit "The Emerging Economics of AI in Finance". 

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 (video 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.   

Media contacts 

Sage 
Jordan Kercheval
External Communications Manager, Sage North America 
[email protected] 
 
Sage PR 

John Patricolo  
Account Manager  
[email protected]