Finance departments have moved quickly to put generative artificial intelligence to work. They’ve been far more cautious about letting AI act on its own.
Generative AI use for cash flow management jumped from 16% in 2025 to 80% in 2026, according to PYMNTS Intelligence’s “Time to Cash: What Two Years of Data Say About Faster Cash and Rising Risk.” Agentic AI went the other direction, edging down from 6% to 5%, as detailed in the report, done in collaboration with JPMorgan.
The gap offers a measure of where finance automation stands. AI is becoming common in the systems that analyze cash and recommend what to do next, while autonomous execution remains rare.
Nearly two-thirds of finance teams, 64%, now use AI-generated insights or recommendations when making cash flow decisions, up from 44% a year earlier. Twenty-eight percent of CFOs call those insights their most impactful cash flow action, more than twice the 13% who said so in 2025. Business intelligence dashboards rank just one percentage point higher, at 29%.
The Decision Layer Changes Faster Than Execution
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AI hasn’t pushed out the finance department’s existing technology.
Business intelligence and analytics tools are used by 96% of companies, spreadsheets by 95% and ERP systems by 93%. Companies are layering AI into a technology stack that remains largely intact.
Manual spreadsheet analysis is still used by 76% of finance teams, but only 2% now identify it as the cash flow action with the greatest impact, down from 10% last year. AI-generated insights, by comparison, are used by 64% and cited as most impactful by 28%.
The emerging model has several layers: dashboards organize information, models run scenarios, alerts identify changes and AI produces recommendations. Finance executives can use the output without turning the subsequent decision and execution over to an autonomous AI agent.
Results elsewhere in the study show why the recommendation layer is attracting attention. The share of CFOs reporting improvements in cash flow model accuracy rose from 67% to 86%, while the share reporting faster forecasting increased from 70% to 85%.
Automation is also reaching functions adjacent to the cash decision. Sixty-five percent of companies use AI or machine learning for real-time fraud detection. The rate rises to 71% among companies using at least two types of artificial intelligence for cash flow, compared with 53% among those using one type or none.
Agentic AI remains the exception. The data don’t establish why adoption has remained around 5%, so they don’t support attributing the gap to trust, technology limitations or corporate policy. They do show that finance teams have drawn a practical line so far: AI is rapidly becoming part of deciding what should happen to cash, while autonomous AI remains a small part of managing it.
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