Finance leaders demand proof and guardrails before AI autonomy expands

Esker's 2026 survey of 338 global finance leaders finds AI overspending and governance gaps are stalling the agentic finance era.

By Disrupts Editorial Team Sat, 10 October 2026 AI level 2 of 5

AI level 2 of 5: drafted by our AI editorial assistant from the company's announcement; fact-checked, edited and signed off by Mark Walker, Editorial Director. What the levels mean

A brightly lit, clean data center features parallel rows of glass-fronted server racks, each flanked by automated robotic systems, with a central track containing several modules leading to a monitor-equipped workstation at the far end.

Esker, the France-headquartered AI automation vendor for finance operations, has published its 2026 Global Finance AI Trust Index, drawing on responses from 338 finance leaders across the US, UK, EU, Australia and Canada, including 137 CFOs. The headline finding: AI is already embedded in finance workflows, but a majority of senior leaders are reluctant to extend its decision-making authority until they see clearer evidence of financial return and tighter governance controls.

The report arrives at a telling moment. Agentic AI, the category of software that takes autonomous multi-step actions rather than merely surfacing recommendations, is the current frontier for enterprise automation vendors. Esker's own product roadmap sits squarely in this space. The survey data, however, suggests enterprise buyers are not yet ready to hand the wheel over: 32% of respondents currently use AI only to recommend actions that humans then execute manually, and a further 29% allow AI to act only with human sign-off at each step.

Overspend and governance gaps are the twin blockers

Cost control is an immediate pressure. Seventy-two per cent of respondents say their organisations spent more than planned on AI initiatives over the past year, a figure that rises to 75% when restricted to CFO-level respondents. Yet the ability to link that spend to measurable outcomes remains elusive: 65% of CFOs say they struggle to connect AI usage to specific business results, compared with 40% of their direct-report peers.

Governance gaps compound the problem. Nearly half the sample, 48%, cite data quality as the primary barrier to expanding AI's role. Forty-two per cent flag insufficient integration between finance systems and AI tooling, a concern that climbs to 58% among CFOs specifically. Perhaps most striking for risk officers: 66% of respondents say they know or suspect that finance employees are already using unapproved AI tools, a shadow-IT pattern that mirrors the early-cloud and early-SaaS eras and carries similar compliance exposure.

"CFOs aren't rejecting greater AI autonomy but considering the guardrails needed to increase their confidence in AI tools," said Scott McDermott, CFO at Esker. "They want evidence of financial value, clarity around how decisions are made, and confirmation that people will remain in control when human judgment matters most."

The convergence read-across: agentic finance meets enterprise AI governance

The survey findings carry implications well beyond the CFO's office. The trust deficit Esker has documented is effectively a demand signal: enterprises are now shopping less for AI capability and more for AI governance infrastructure. That creates a convergence opportunity at the intersection of fintech automation, enterprise software, and the emerging AI audit and compliance layer that regulators in the EU (under the AI Act) and increasingly in the US are beginning to formalise.

For cross-sector investors, the pattern is familiar from prior enterprise technology cycles. Productivity gains register before revenue gains, adoption outruns governance, and shadow usage then forces a compliance consolidation wave. Cloud computing followed this arc through the mid-2010s; cybersecurity spending surged in the aftermath. The current AI overspend dynamic, with 72% of organisations already over budget, suggests the consolidation and governance phase of enterprise AI is arriving sooner than many forecast.

Capital markets are pricing this shift. Infrastructure and middleware vendors that can credibly demonstrate ROI attribution and audit trails for AI decisions are attracting attention from both strategic acquirers and growth equity funds. Esker, which is privately held and backed by Bridgepoint following a 2022 take-private, is competing for that positioning alongside larger players including SAP, Workday, and a growing field of agentic-finance startups. The CFO survey data, self-commissioned as it is, serves a dual purpose: it maps genuine market anxiety and simultaneously positions Esker's governance-first architecture as the answer. Readers should weigh both functions when interpreting the findings.