According to Emagia VP of Customer Success and longtime industry practitioner Phyllis Saavedra, the conversation on AI’s potential impact on Order-to-Cash has shifted away from “if” there will be an impact toward something more realistic and practical:

Where does AI deliver measurable impact in collections — and how do we deploy it responsibly?

As B2B receivables environments grow more complex, traditional collections models struggle to scale. Higher invoice volumes, fragmented customer behavior, increasing dispute frequency, and globalized operations have rendered aging-based, reactive approaches insufficient.

This is where predictive and Agentic AI moves from theory to tangible value in the area of collections.

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Global Business Services (GBS) has moved far beyond its origins as a transactional cost-saving model. Approximately 85% of organizations are committed to the GBS model, whether fully deployed or transitioning within the next three to five years, according to the recently released SSON report “State of the Shared Services and Outsourcing Industry 2026.”

The mandate has evolved:

• From cost arbitrage → to enterprise value creation
• From transactional processing → to analytics and decision enablement
• From back-office support → to digital transformation leadership

For finance leaders, particularly those overseeing Order-to-Cash (O2C), this shift elevates AI and autonomous capabilities from experimentation and theory to strategic necessity, according to Naomi Secor, global managing director at SSON. For more Information click here.

The “Experience Gap” reveals a stark reality: 93% of C-suite executives admit their digital customer experience is “broken” and needs improvement. Yet only 28% rate it as innovative or adaptive, despite 94% agreeing that CX drives business success. Meanwhile, top performers generate 30% more revenue, or $1.4 billion on average, than laggards. For trade credit, treasury, and finance practitioners, these findings spotlight untapped opportunities in quote-to-cash (Q2C), accounts receivable (AR), credit, and collections, where AI can forge emotionally intelligent connections.

CX leaders thrive by closing the gap with AI that deepens emotional ties, not just cuts costs. Improving Q2C offers finance the same path, with 86% eyeing it as a priority amid agentic AI’s rise. Credit and Treasury teams should get started by auditing silos (56% barrier), piloting AI for one process (such as cash flow predictions), and then measuring against the report’s revenue benchmark. In a world where buyers demand adaptive experiences, mastering Q2C CX isn’t optional; it’s your big advantage.

Editor’s Note: David is Editor in Chief & Co-Founder at Trade Credit & Liquidity Management and Partner at Quote to Cash Solutions LLC. This article originally appeared for the online publication Strategic Trader – you may read in full here: https://tradecredit.substack.com/p/bridging-the-customer-experience-gap-with-ai . David is also a frequent contributor to Emagia’s 2005-2006 executive white paper series – you may find his work on Deductions, Collections, and E-Invoicing at https://www.emagia.com/resources/white-papers/.