CFOs risk falling behind without scalable AI strategy

Chief financial officers risk falling behind without a scalable AI strategy, Gartner said, with a small group of firms already pulling ahead.

In its assessment of finance teams, the research group argued that many leaders still treat AI as a collection of isolated tools and pilot projects, rather than building the systems needed to use it across the organisation.

Clement Christensen, vice president analyst, and Tamara Shipley, vice president analyst in Gartner's finance practice, said the gap in results will depend heavily on leadership decisions about spending, measurement and priorities.

Their argument centres on what Gartner calls "breakaway firms" - companies generating stronger returns from AI because they have changed how they invest, govern data and organise teams.

That divide is visible in spending patterns. Gartner data presented in the keynote showed that 84% of finance AI spending goes to individual productivity and process improvement use cases, while 16% is allocated to uses that can materially change business outcomes.

Many finance functions have assembled AI tools without the structures needed to make them work together, Christensen said.

"If CFOs are feeling stuck in the piloting phase of AI, it's likely because they've built an accidental factory: lots of new machines, but no systems to enable and connect them," he said.

This pattern has contributed to weak returns despite widespread executive optimism about AI. According to figures cited in the keynote, 71% of typical finance teams report low impact from their AI investments, and 62% of CFOs say fewer than a quarter of their AI initiatives deliver measurable benefits.

Investment choices

Shipley said the current allocation of capital suggests many finance leaders remain focused on efficiency first, even though stronger gains may lie elsewhere.

"With AI, it's simply unnecessary and untrue to think finance must achieve efficiency gains before it can drive higher value outcomes," she said. "Breakaway firms prioritize their investments differently. They prioritize upside over cost-cutting."

The analysis suggests CFOs need to reassess not only which projects they fund, but also how they judge success. Gartner recommended gathering AI spending across the enterprise and reviewing it as a portfolio rather than as separate initiatives.

Under that approach, finance leaders would test whether each investment supports future AI deployment, helps drive revenue growth or creates reusable assets such as governance structures, knowledge and data products.

Factory model

The keynote compared the shift to AI with earlier industrial changes, including the railway age and the first mechanised factories. The point was that lasting value comes from systems that connect machines, people, data, knowledge and governance, rather than from technology alone.

That view also changes how governance should be understood inside finance functions, Shipley said.

"Governance is not just about controls, guardrails and risk," she said. "It is just as much about making things go faster."

Many organisations are experiencing what Gartner called "hopeful disappointment" with AI, where confidence in the technology remains high but commercial outcomes have yet to match expectations.

One of the biggest constraints is talent. Gartner research found that only about 30% of finance employees currently qualify as digital talent, which it defines as workers able to build a technology solution when they encounter a problem.

By contrast, the firms making the fastest progress are aiming for 90% or more, according to the keynote research.

That leaves finance leaders facing a workforce challenge as well as a capital allocation question. Rather than relying on recruitment alone, organisations will need to spread technology work across existing teams, Gartner said.

"Finance leaders must democratize technology work now and empower their people because it simply won't be possible to hire all the digital talent they need," Christensen said. "Finance work is technology work."

The implication is that CFOs must take a broader role in shaping AI systems, operating models and workforce design, rather than treating AI as a narrow automation programme.

Christensen said the central task is to create an environment where people and technology can work together in a more organised way.

"The system that finance leaders build to empower people and machines to work better together is just as important as the machines themselves," he said. "In short, CFOs need to build a factory on purpose."