The Rise of Searching for Hard ROI in the CFO Role
September 7, 2026 – 6:11 pm
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The Shift from Adoption to ROI
In a June 2025 survey of 183 CFOs, Gartner reported that 84% of finance organizations had deployed AI or planned to, but only 7% reported a high impact. Most AI spend results in increased productivity, efficiency, and time back, rather than hard ROI.
A subsequent Gartner survey in March 2026 found that 45% of finance AI investment leans toward productivity, and 20% toward decision quality. Shankar Keshav, the analyst behind the survey, highlighted a "perception gap" where finance leaders claim progress on AI adoption, but boards see limited strategic impact.
Hard ROI must be grounded in cash, whether through revenue growth, cost savings, or faster access to cash. While time-saving is valuable, finance leaders should differentiate between AI deployment and business value creation and seek solutions delivering tangible cash benefits to the business.
Accounts Receivable: Delivering Hard ROI
The Federal Reserve estimates $9.8 trillion in trade receivables sitting in the United States as of Q1 2026. Allianz Research reported an average company’s days sales outstanding at 59 days in 2023, across 45,000 listed companies in over 35 countries. Atradius found 43% of credit-based B2B sales overdue in 2025.
Accounts receivable (AR) represents a significant and widespread financial challenge in B2B today. AR solutions have been complex to solve pre-LLMs, with minimal room for error, leading companies to be cautious about automation.
When implemented correctly, AI can expedite payments, demonstrating its value.
The Limitations of Traditional "AR Automation"
Rules-based AR software has existed for years, sending reminders at set intervals and functioning adequately for straightforward invoices. However, as most finance teams know, the reality is far more complex.
92% of enterprise invoices require submission through a vendor portal or network rather than email payment, each with its own browser automation intricacies. Our data indicates 39% of cash flow slowdowns stem from edge cases like missing W-9 forms, out-of-office approvers, PO discrepancies, and portal rejection formats.
In a NACM and BlackLine survey of over 400 credit professionals, 44% reported minimal or no automation for remittance data, received across emails, PDFs, portals, and lockboxes.
Most slowdowns aren’t due to customers refusing to pay but rather friction caused by invoices lingering in inboxes for weeks. Pre-LLM software hasn’t been sophisticated enough to handle edge cases, leading to ongoing workload for finance teams.
Leveraging LLM for Nuanced AR Collection
Collecting unpaid invoices is a nuanced process, and directly communicating with customers can be delicate. An inappropriate message from an automated agent could damage years of relationship-building.
LLM software offers a unique advantage by being able to adapt its communication style for each customer’s needs, tone, and situation. When deployed correctly, AI-driven AR tools can relieve finance teams of this task but must be executed with absolute precision.