Sage releases IDC whitepaper: Emerging Economics of AI in Finance

Sage, uniquely positioned to define what robust governance and 'glass box' AI looks like in practice, is striving to ensure finance leaders can confidently stand behind AI and realize the true ROI of responsible automation.  

Accordingly, Sage sponsored the Jun 2026 IDC white paper titled, The Verification Tax: The Emerging Economics of AI in Finance, which is based on a survey of 2,275 senior finance decision-makers across North America and EMEA. The research demonstrates that the defining challenge for finance AI is no longer model capability but rather the human effort required to trust AI outputs enough to act on them.

Trust, not capability, is the primary constraint; not what the model can do, it's the human effort required to trust outputs enough to act on them with confidence. The report also cites that verification (of AI) is expensive, in some cases AI creates more work than it saves. Transparency is at a premium, transparency and traceability into the logic behind its (the AIs) outputs, opposed to an opaque Black Box, is critical to adoption. The result is that many organizations find it necessary to build an operational layer within finance focused not on generating AI outputs but on managing trust in those outputs. 

In announcing the study's release, Aaron Harris, CTO at Sage said, "In finance, almost right has always been wrong. As AI takes on more complex financial workflows, the cost of uncertainty is simply too high," Harris went on to say, "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 within the whitepaper include:

• Finance leaders spend an average of nearly 13 hours per week validating AI-generated outputs

• 71% would reject a 99%-accurate AI tool that could not produce a human-readable reasoning trace

• 74% treat Glass Box transparency as mandatory or context-dependent for high-risk decisions

• 44% state Glass Box transparency is a non-negotiable for deployment of AI solutions

• 69% agree: "By 2030, a CFO who cannot explain their AI's reasoning will be as unemployable as a CFO who cannot read a P&L"

• Risk, Governance & Decision Judgment is now the #1 hiring priority for finance leaders (valued nearly twice as highly as deep technical accounting)

 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.

Kevin Permenter, Research Director, Financial Applications at IDC, that prepared the report said, "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.”  

Perhaps the most significant takeaway can be found in these two sentences from the report, "In a market where AI capability is rapidly commoditizing, the durable differentiator is not what an organization's AI can do. It is what the organization has built to govern what its AI does."₁

_{For more information see the official Whitepaper Here.} 

Disclosures and Footnotes: 

Content within this feature, including the headline feature image, has been adapted by the author from source materials provided by Sage (USA). Referenced source materials and content appearing within Insightful Accountant are used with permission and are provided solely for educational and informational purposes.

 ₁ - About the research: The whitepaper was produced by IDC Custom Solutions, it is based on an Agentic AI Finance Survey conducted with Sage in February 2026, combined with executive interviews, enterprise finance practitioner discussions, and ongoing IDC market analysis. The research was conducted under the leadership of Kevin Permenter, Research Director, Financial Applications at IDC. Kevin provides insights and analysis across multiple Fintech market segments including accounting, revenue management, corporate tax, accounts payable, accounts receivable, treasury and enterprise payment management. Kevin’s research includes a particular emphasis on the interplay, challenges, and trends driving financial application deployment and its role in the evolution of the complex financial technology ecosystem.

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About Sage: Sage exists to knock down barriers so everyone can thrive, starting with the millions of small and mid-sized businesses they serve, along with our partners and our accountants. Customers trust our finance, HR, and payroll software to facilitate work and money. By digitizing business processes and relationships with customers, suppliers, employees, banks, and governments, their digital network connects SMBs, removing friction and delivering insights. Knocking down barriers also means they use their time, technology, and experience to tackle digital inequality, economic inequality, and climate crises.

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