INDUSTRY FIN. TECH

NTELLIGEN

������������������������������������

Based on a global survey of 1,520 finance and business leaders, Payhawk’ s CFO’ s AI Readiness Report found 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 enter budget season under pressure to fund AI and automation, the findings offer a reality check on where the market stands and where execution risk is most concentrated.

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), making the‘ leader’ label common enough to require closer examination and too broad to treat as a single operating reality

• The market is moving unevenly rather than sequentially, with a small group scaling, a large middle struggling to convert activity into operations and a tail that remains early

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

“ The real risk in finance AI isn’ t experimentation, it’ s getting stuck halfway,” said Hristo Borisov, CEO and Co-founder of Payhawk.“ Many finance teams now have visible AI activity but lack the minimum structure needed to scale it safely under audit and control. The organizations that succeed won’ t be the loudest adopters, but the ones that make AI governable inside their finance operating model.”

AI maturity varies sharply by company context, with readiness strongly influenced by industry and company size. Tech organizations with more than 251 employees show the highest maturity levels globally, with over 70 % rating

The real risk in finance AI isn’ t experimentation, it’ s getting stuck halfway,

themselves as highly mature. Among smaller organizations in regulated and core-economy sectors( 50 – 250 employees), only 13.5 % report high maturity.

By contrast, large non-tech organizations largely sit in the midmaturity band, actively adopting AI but struggling to scale it into core finance operations.

A related structural factor helps explain this pattern. Higher AI maturity is more common in organizations with complex, multi-entity structures, where scale drives investment in standardization, shared services and centralized controls.

However, this does not guarantee AI readiness. Without data consistency and alignment, weak governance can create lag.

A key implication of the research is that self-identified‘ AI leaders’ are not a uniform group. The headline maturity figure masks wide variation in how finance teams deploy AI in practice. Some organizations have embedded AI into workflows with clear accountability. Others are moving quickly without minimum guardrails or investing with intent but lacking the foundations required to scale. • www. intelligentcio. com

INTELLIGENT CIO LATAM

41