What it does
It is not a tool but a market study. Gartner asks finance leaders how long it takes to get the expected value from each AI use case. It concludes that investment is concentrated in quick-return and productivity uses, such as reporting and process automation, and recommends not neglecting those that improve decision-making, risk management and revenue even if they mature more slowly.
Reported result or impact
Data stated by Gartner: 160 finance leaders surveyed between January and April 2026. Returns from data extraction, accounts payable and receivable automation and report creation generally arrive in 9 to 10 months. Gartner adds that low AI literacy is now the main barrier, ahead of talent, partly because agentic coding tools have reduced the technical difficulty. The figures per use case are in charts and in a paid report that we could not consult.
Mind the evidence. A study, survey or analysis by a third party. Useful as context; it does not prove that a specific tool works.
How to replicate it
Use it as a reference for setting expectations, not as a guarantee. For each AI pilot, set a realistic time-to-value (9 to 10 months for document, collections and payments automation according to this study, longer for forecasting), reserve budget for hands-on team training and review midway which initiatives to cut. If you run an advisory firm or a small business, start with the quick-return cases and leave the analytical ones for a second phase.
Nuances
- It is a press release from a consultancy that sells studies; the public summary does not include the complete figures per use case.
- The sample is 160 finance leaders with no public detail on country, sector or size; it cannot simply be extrapolated to small businesses in Spain.
- It does not discuss any specific ERP, which is why this entry appears as general context.
Sources
We wrote this entry in our own words from the sources above and checked that the links worked on October 17, 2026. Is anything incorrect? Tell us.