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AI readiness report: Half of finance teams globally are stuck in the “middle” on AI maturity

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AuthorPayhawk Editorial Team
Read time
2 mins
PublishedFeb 11, 2026
Last updatedFeb 11, 2026
New Research: 50% Of Finance Teams Are 'Stuck' Regarding AI Maturity
Quick summary

New research finds that half of finance teams are stuck in the middle of the AI maturity spectrum. They’re experimenting with AI, but haven’t embedded it safely into core finance workflows.

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This article first appeared as a Press release.

The news:

New research from Payhawk reveals that AI adoption in finance is no longer “early,” but it is deeply uneven.

Based on a global survey of 1,520 finance and business leaders, Payhawk’s CFO AI Readiness Report shows that half of organizations now sit in the “middle”, actively experimenting with AI in finance yet unable to scale it safely or consistently into core workflows.

As CFOs head into budget season under pressure to fund AI and automation, the findings offer a reality check on where the market actually stands and where execution risk is most concentrated.

The middle is now the market’s center of gravity

The CFO’s AI Readiness Report asked respondents to rate their organization’s AI maturity on a 1–10 scale (low: 1–3, mid: 4–6, high: 7–10). The findings show:

  • Around 50% of organizations globally sit in mid-maturity (4–6), they are adopting AI but not yet running it as a core finance capability.
  • Nearly one‑third self‑identify as high maturity (7–10), which makes the “leader” label common enough to warrant closer examination and broad enough that it can't be treated as a single operating reality.
  • The market is moving unevenly, not sequentially, with a small group scaling, a large middle struggling to convert activity into operations, and a tail that remains early.
Figure showing the percentage of companies considering themselves as AI mature
Figure 1: AI maturity is concentrated in the middle of the market.

This uneven distribution matters more in finance than in most other business functions. Unlike experimentation-heavy domains, finance AI must survive controls, audit, accountability and policy enforcement before it can scale into workflows that materially affect the business.

Hristo Borisov, CEO and Co-Founder of Payhawk, says:

Payhawk sits where AI ambition meets finance reality. We’re in the workflows where approvals turn into spend, payments go out, exceptions pile up, and audit trails get tested. That’s why we’re convinced the blocker isn’t experimentation but running AI inside controls without losing accountability.”

CFOs: How to scale AI when control is non-negotiable

AI maturity varies sharply by company context

AI readiness in finance is strongly patterned by industry and company size. Tech organizations with more than 251 employees show the highest maturity levels globally, with over 70% rating themselves as highly mature. Of smaller organizations in regulated and core-economy sectors* (50–250 employees), only 13.5% report high maturity. By contrast, large non-tech organizations overwhelmingly sit in the mid-maturity band, actively adopting AI but struggling to scale it into core finance operations.

A related structural signal helps explain this pattern. Higher self-reported AI maturity is more common in organizations with complex, multi-entity structures, where scale forces investment in standardization, shared services and centralized controls. But this does not guarantee AI readiness – without data consistency and data alignment, poor governance can create a lag.

Challenging the AI “leaders vs laggards” narrative

A key implication of the research is that self‑identified “AI leaders” are not a uniform group. The headline maturity number masks a wide variation in how finance teams deploy AI in practice. Some organizations have embedded AI into workflows with clear accountability. Others are moving fast without minimum guardrails or investing with intent but lacking the foundations to scale.

The research shows that the limiting factor for financial AI maturity is not model capability, but rather whether adoption can be made stable, defensible, and repeatable within financial control environments.

Methodology
To gain insights into how CFOs are adapting to the changing landscape, Payhawk partnered with IResearch to interview 1,520 senior professionals globally. Using affirmative statements developed in close collaboration with finance and business leaders, IResearch conducted interviews across eight countries to reflect genuine operational realities and challenges.

Coverage included:

  • Regions: DACH, Spain, France, Benelux, UK & Ireland, United States*
  • Seniority: C-suite, VPs, Directors, and senior individual contributors*
  • Functions: Finance, Accounting, Sales, HR, Procurement*
  • Industries: Services, Digital, Manufacturing, Healthcare, Education & Non-profit, B2C*
  • Company size: 50–100 FTE, 101–250 FTE, 251–500 FTE, 501–1,000 FTE, and 1,000+ FTE*)

The Payhawk Editorial Team consists seasoned finance professionals boasting years of experience in spend management, digital transformation, and the finance profession. We're dedicated to delivering insightful content to empower your financial journey.

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