Corporate treasury is approaching an uncomfortable reality about artificial intelligence. Almost every firm has it, but relatively few companies can demonstrate that it is making them financially better off.

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Findings in the latest 2026 edition of the Working Capital Index (WCI) from PYMNTS Intelligence reveal that 97% of the lowest-performing middle-market firms use AI in treasury, virtually matching the 100% adoption rate among top performers.

But the two groups still operate with notably different levels of financial efficiency.

Top performers report cash conversion cycles averaging 39 days, compared with 63 days among bottom performers. Some 70% of the strongest firms report predictable financing needs, versus just 3% of laggards.

The PYMNTS Intelligence WCI report findings suggest that the next competitive divide in corporate treasury may not be between companies that have adopted artificial intelligence and those that haven not. It may be between companies that use AI to understand their cash positions and those that can translate that technology into financial decisions.

Automating collections, identifying overdue invoices and improving cash forecasts can make finance operations more efficient. But those improvements do not alone change when customers pay, how much liquidity a company must maintain or whether cash can be deployed toward more productive uses.

A treasury department might know with greater precision that a cash shortfall is approaching. Unless that information changes borrowing, payment or investment decisions, however, the forecast remains an operational input rather than a financial advantage.

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