Savant Report Uncovers Finance AI Automation Gap as 76% Plan Investment, Only 6% Deliver Advanced Implementation

Execution lags ambition for AI automation in finance, with governance the barrier to adoption

Savant Labs, a leader in AI-powered analytics automation, announced the release of its 2026 Trends Report on Agentic Automation in Finance, Tax and Accounting, a research study examining how enterprise leaders are approaching AI and automation as they plan for the year ahead.

The report surveyed senior finance, tax, and accounting leaders at North American enterprises across 22 industries to assess the current state of agentic automation across their organizations.

While 76% of respondents overwhelmingly cite 2026 as the year for investment in strategic agentic automation and generative AI, only 30% have functional pilots underway, suggesting their aspirations are lagging AI execution. The research identified a pronounced governance gap as the most significant barrier to execution, with 37% of leaders reporting persistent concerns around the ability to govern, audit, and control AI automation workflows. Integration with core ERP and legacy systems is the next biggest concern at 24%.

“Enterprise teams are aligned on the expected benefits of agentic automation, but many companies are struggling to operationalize it,” said Chitrang Shah, CEO and Co-Founder of Savant Labs. “Their uncertainty around governance, auditability, and risk is holding back confident scaling – which can be addressed with the advancements of agentic automation platforms like Savant.”

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The findings also challenge common assumptions about agentic automation’s impact on the workforce. More than 80% of leaders expect no net change in headcount in 2026, signaling that AI is primarily viewed as a productivity multiplier rather than a workforce reduction tool. Only 3% of respondents anticipate net job growth, suggesting increased pressure on existing teams to deliver more output with the same resources. This dynamic is accelerating interest in agentic automation initiatives designed to absorb repetitive, error-prone work while preserving human judgment for higher-value responsibilities.

Additional findings from the report include:

● Ambition outpacing execution: Only 6% of leaders have an advanced strategy with broad-scale implementation across their teams, with the majority of respondents citing their organizations’ adoption remains limited to isolated pilots or individual single-function use cases.

● Governance and trust as primary blockers: Over 60% of the leaders ranked data governance and security, along with ERP integration concerns, as the primary blockers to widespread adoption. These concerns ranked over three times higher than ‘cost and ROI’ and three times higher than concerns over quality control and lack of team skills combined.

● Uneven adoption across functions: Early success is surfacing with accounting and finance operations teams who are embracing agentic automation to tackle high-volume, repeatable workflows, while tax teams remain more cautious, given regulatory exposure.

The report also highlights growing competitive risk for organizations that delay action. In tightly connected finance and tax ecosystems, early adopters are beginning to standardize on governed approaches to AI. As those standards take hold, organizations that fail to close the governance gap may struggle to keep pace with peers that are already operationalizing agentic automation and AI at scale.

To help leaders move forward, the report concludes with a blueprint and immediate recommendations on how to best operationalize agentic automation while addressing the governance gap.

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