6DECEMBER 2025CFO TECH OUTLOOKManaging EditorSarah DawsonAaron Pierce Ann Bennis Antony MosesVisualizersKevin ParkerSarah DawsonManaging Editoreditor@cfotechoutlook.comEditor's NoteEmail:sales@cfotechoutlook.comeditor@cfotechoutlook.commarketing@cfotechoutlook.com DECEMBER 2025, Vol - 11, Issue - 06 (ISSN 2644-2841)ValleyMedia, Inc. To subscribe to CFO Tech OutlookVisit www.cfotechoutlook.com Editorial StaffAva GarciaJoshua Parker Paul BarberJoy ParkerCopyright © 2025 ValleyMedia, Inc. All rights reserved. Reproduction in whole or part of any text, photography or illustrations without written permission from the publisher is prohibited. The publisher assumes no responsibility for unsolicited manuscripts, photographs or illustrations. Views and opinions expressed in this publication are not necessarily those of the magazine and accordingly, no liability is assumed by the publisher thereof.A s 2025 draws to a close, the U.S. market for AI-based revenue leakage detection platforms has shifted from experimentation to mainstream adoption, particularly in SaaS, healthcare revenue cycle management, and complex B2B subscription models. Vendors are increasingly positioning these systems as "revenue operating" or "revenue intelligence" layers that sit across CRM, billing, contracts, and usage data to continuously surface underbilling, missed renewals, and claims at risk of denial before they affect the profit and loss statement (P&L).Three forces have defined the year. Mounting pressure to protect margins in a sluggish macroeconomic environment has pushed CFOs to address revenue leakage--which can be 4 to 10 percent of top-line revenue in SaaS and service industries--as a key opportunity for value creation. Simultaneously, the rise of usage-based and hybrid pricing models has rendered manual controls impractical, fueling demand for anomaly detection, contract-aware analytics, and real-time usage metering. In healthcare, claims integrity and denial-prevention initiatives have intensified as providers rely on AI-powered revenue cycle management (RCM) tools to stabilize reimbursement and strengthen compliance.The market continued to grapple with data fragmentation, legacy billing systems, and mistrust of AI "black boxes," all of which slowed implementations and extended sales cycles. Leading platforms responded with more robust native integrations, domain-specific models, auditable rules engines, and pilot programs that demonstrated rapid, recoverable revenue to secure executive sponsorship.Heading into 2026, buyers are looking for platforms that are not only accurate but also explainable, pre-integrated with core financial ecosystems, secured against increasing cyber risks, and capable of managing the next wave of complexity in dynamic pricing and large-scale partner revenue sharing.In this edition, we spotlight some of the most influential names in the industry, including David Robertson, Director of Enterprise Architecture, Software Engineering and Applications at Exeter Finance, and Ciprian Porutiu, SVP of Strategic Initiatives, Change Management, and Business Transformation at Marsh McLennan. These leaders share their perspectives on the emerging challenges and opportunities in the space. We hope their insights will help you make better and more data-driven business decisions.THE NEW ERA OF AI-DRIVEN REVENUE ASSURANCEDisclaimer: *Some of the Insights are based on our interviews with CIOs and CXOs
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