While most finance organizations have embraced AI, only a small fraction report significant financial returns, spotlighting the urgent need for solutions that directly boost cash flow and reduce accounts receivable complexities.
- 84% of finance organizations have adopted AI but only 7% see strong ROI
- Accounts receivable complexities slow down cash flow, causing finance headaches
- New AI tools promise automated, error-free collections with transparent audit trails
What happened
By mid-2025, the vast majority of finance organizations had invested in or planned to integrate AI tools, according to Gartner's research among CFOs. Despite this adoption, only a small minority have experienced a meaningful financial impact from AI, with many gains limited to enhanced productivity, improved efficiency, and time savings rather than direct revenue growth or cost reduction.
Accounts receivable (AR) is identified as a critical bottleneck in many organizations' cash flow, with trillions of dollars tied up globally due to complex payment scenarios and process frictions. Traditional AR software has struggled to manage these complexities effectively, leaving many finance teams overwhelmed and reliant on manual intervention.
Why it matters
The finance function is under increasing pressure to demonstrate hard ROI from their AI investments, shifting focus from mere operational improvements to direct cash benefits such as faster payments, cost savings, and improved liquidity. The perception gap revealed by Gartner highlights a disconnect between AI adoption success reported by finance leaders and the limited strategic value recognized by boards.
Effective AI application in AR promises real financial transformation by intelligently handling complex invoicing issues and customer interactions that traditionally delay payments. With a significant share of credit sales overdue and typical sales invoices requiring processing through specific vendor portals, innovative AI solutions capable of navigating these challenges could unlock billions in working capital.
What to watch next
Companies deploying advanced AI tools that combine large language models with deterministic coding to manage accounts receivable should be closely monitored. These tools can autonomously resolve complex payment disputes, apply cash precisely, and maintain transparent audit trails—potentially revolutionizing how finance teams handle collections without human error risk.
Market developments will also be shaped by how quickly CFOs can integrate AI solutions that deliver measurable cash benefits and the responses of finance teams adapting to a new era where AI is expected to do more than productivity enhancements. Observers should watch adoption trends, technology advancements, and reported improvements in cash flow metrics as key indicators of AI’s strategic impact in finance.