Gartner says 58% of finance teams now use AI

Finance teams have spent the last two years getting asked why HR and legal seemed further ahead on AI. Gartner’s latest finance survey suggests that gap has narrowed fast, and it changes what CFO operations leaders need to run day to day: less “should we try AI” and more “how do we control it, price it, and prove it.”

CFO Dive, citing Gartner survey findings published Sept. 11, 2024, reported that 58% of finance functions said they were using AI in 2024. The same write-up said that figure is up 21 percentage points from 2023, and that the survey covered 121 finance leaders across industries.

Adoption is rising, but the survey is light on ROI numbers

The adoption number is a clean benchmark for operators because it is specific, recent, and tied to a defined respondent pool. It is also incomplete in a way that matters operationally: CFO Dive’s summary of Gartner’s results included sentiment and adoption, but no disclosed savings, cycle-time reductions, or revenue impact figures that would let finance teams calibrate expectations.

CFO Dive reported that 66% of finance leaders said they were more optimistic about the technology compared with the prior year. Gartner also found, per CFO Dive, that among the 42% of finance functions not currently using AI, half were planning implementation. Those are planning signals, not business cases, which means finance teams still have to build the measurement layer themselves.

Gartner is packaging “the next step” as tools, benchmarks, and journey steps

On its Gartner for Finance Leaders page, Gartner frames common CFO questions around AI roadmaps, cutting costs without harming growth, changing finance operating models to capture AI benefits, and assessing AI ROI and ongoing AI costs. That menu matters because it matches where projects tend to stall: once the pilot works, nobody has agreed on chargeback, control points, or what “good” looks like.

Gartner’s Gartner for Finance membership overview positions its offering around mission-critical priorities and step-by-step “journey steps” from strategy to execution. Gartner also says the service is backed by more than 510,000 client discussions, 23,000 vendor conversations, and 500,000 AI queries, and it highlights decision tools including AskGartner, AI Use Case Insights (over 1,000 use cases), Finance Score, Accelerators, and a Finance Budget & Efficiency Benchmark.

Where this lands in finance operations and procurement cycles

For finance ops leaders, the practical shift is that AI in finance is moving into the same governance-and-benchmarking machinery used for other enterprise systems: standard definitions, controlled workflows, and vendor evaluation artifacts that can survive audit scrutiny. Gartner’s positioning of tools like Finance Budget & Efficiency Benchmark suggests buyers will increasingly justify AI spend using peer comparisons, not just internal anecdotes.

This also reframes vendor conversations. As adoption approaches a majority of finance functions, procurement and IT governance teams will likely be asked to support more “CFO-owned” tools and embedded AI features inside existing platforms, and to reconcile them with policy around data handling, model access, and ongoing run costs that land in the finance budget.

Questions CFO ops teams can take into the next steering meeting

• What counts as “using AI” in the finance function: production workflows under control, supervised pilots, or individual ad hoc tools, and how will that definition be reported quarterly?
• Where will AI run costs sit: a central IT/AI budget, a finance cost center, or vendor line items embedded in existing contracts, and what metric will trigger a renewal conversation?
• Which governance artifacts are required before scaling: documented use-case selection criteria (for example from an AI use-case library), a control checklist tied to close/reporting processes, and an ROI model that separates cycle-time gains from headcount assumptions.