Chief financial officers (CFOs) must stop treating AI as a collection of tools and use cases as they develop systems that allow AI to be productive at scale, according to Gartner.
“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,” says Clement Christensen, v ice-president analyst in the Gartner Finance practice.
That accidental factory problem is showing up in how finance leaders allocate AI spending. Rather than building the assets and systems needed to scale AI value, many finance functions are still concentrating investment on productivity and process improvement.
Gartner data indicates that 84% of finance AI spend relates to individual productivity and process improvement use cases, while only 16% goes toward use cases that can materially change business outcomes.
“With AI, it’s simply unnecessary and untrue to think finance must achieve efficiency gains before it can drive higher value outcomes,” Tamara Shipley, vice-president analyst in the Gartner Finance practice. “Breakaway firms prioritize their investments differently. They prioritise upside over cost-cutting.”
Christensen and Shipley says many organisations are experiencing “hopeful disappointment” with AI: executives remain optimistic about the technology, but returns have not yet matched expectations. They indicate that 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.
“Governance is not just about controls, guardrails and risk,” says Shipley. “It is just as much about making things go faster.”
A major barrier is talent. Gartner research shows that only about 30% of finance talent currently qualifies as digital talent — employees who can build a technology solution when they encounter a problem — while breakaway firms are targeting 90% or more.
“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,” says Christensen. “Finance work is technology work.”
Gartner recommends CFOs pull together all AI investments across the enterprise and evaluate them as a portfolio. Finance leaders should ask whether each investment accelerates future AI deployment, supports top-line growth or builds reusable assets such as knowledge, governance and data products.
“The system that finance leaders build to empower people and machines to work better together is just as important as the machines themselves,” says Christensen. “In short, CFOs need to build a factory on purpose.”