CFOs are under pressure to modernize receivables without creating new operational risk or adding headcount. Yet traditional accounts receivable still suffers from manual work, delayed visibility, and preventable friction that slows cash conversion. Meanwhile, the rise of machine buyers is putting pressure on finance teams to build payment flows that work for both humans and bots, a delicate balancing act.

In this session, discover how to apply AI to transform accounts receivable into a predictive, insight-driven finance infrastructure. Learn how to align invoicing and payments with buyer workflows, improving cash flow visibility and enabling earlier risk detection.

We’ll share a CFO-oriented framework for moving from “automated tasks” to more autonomous receivables, including where AI creates measurable value (working capital, cost-to-collect, revenue quality, and customer experience) and how to structure governance so AI drives outcomes.

We’ll highlight what we’ve learned about the rise of machine buyers and how to future-proof your payment flows and explore a case study where ML models used AR data to predict buyer churn with over 70% accuracy and AI-driven action recommendations drove 14% YoY revenue growth.