McKinsey indicates that while 55% of financial services organizations reported AI adoption in 2023, this figure rose to 78% by late 2025. Adoption is accelerating across core operations like customer engagement, decision-making, and risk workflows. In collections, AI is now embedded in dialing optimization, segmentation, scoring, and increasingly, automated consumer interactions. While operational benefits are clear, insurance frameworks supporting these technologies have not evolved at the same pace.
AI insurance coverage gaps in collections are emerging as a material operational risk. Many agencies assume that existing cyber and errors-and-omissions policies extend naturally to AI-driven activities. In practice, policy language often remains silent or ambiguous regarding algorithmic decision-making, model outputs, and automated consumer communications. That silence becomes consequential when claims arise.
This article draws insights from The Receivables Podcast featuring Tom York, Co-Founder of CastleWise Insurance & Licensing, and examines how AI adoption is creating new insurance exposure for collection agencies and why administrative cost reviews must evolve to address this growing risk.
Understanding AI-Driven Risk in Collections
Artificial intelligence introduces a fundamentally different risk profile compared to traditional human-driven processes. AI systems operate at scale, act consistently, and can propagate errors rapidly if models behave unexpectedly or data inputs shift.
In collections environments, AI influences decisions such as contact timing, channel selection, settlement recommendations, and prioritization logic. While these systems improve efficiency, they also introduce new forms of liability related to consumer harm, regulatory interpretation, and systemic error.
Traditional insurance structures were not designed with these dynamics in mind. As a result, agencies may carry coverage that appears sufficient while leaving significant AI-related exposure unaddressed.
Errors and Omissions Policies and AI Silence
Errors and omissions insurance has historically focused on professional services delivered by human actors. Policy language frequently references mistakes, negligence, or failures tied to individual judgment or manual processes.
When AI systems are involved, attribution becomes less clear. Was an outcome the result of human oversight, system configuration, vendor design, or model behavior? Many E&O policies do not explicitly address this question. Silence on AI-related errors creates uncertainty during claims evaluation.
Some insurers have begun introducing endorsements or standalone products addressing AI errors and omissions, often requiring model validation and governance controls. However, adoption remains limited, and many agencies are unaware these options exist.
Cyber Insurance Does Not Equal AI Coverage
Cyber insurance policies are often assumed to provide broad technology protection. In reality, most cyber coverage is structured around data breach events, ransomware incidents, and network security failures.
AI-related risk does not always manifest as a cyber event. Algorithmic bias, flawed decision logic, or inappropriate automated communications may trigger regulatory or civil exposure without involving a data breach.
When cyber policies exclude non-breach incidents, agencies relying on automation may find themselves uninsured for precisely the risks introduced by AI adoption.
A Framework for Evaluating AI Insurance Readiness
Based on observed patterns across regulated financial services organizations, AI insurance readiness can be assessed through four governance dimensions:
Policy Language Alignment – Reviewing whether existing policies explicitly address AI-driven decision-making, automation, and model behavior.
Operational Transparency – Understanding where and how AI systems influence consumer-facing and internal decisions.
Vendor Accountability – Evaluating contractual liability allocation between agencies and AI vendors.
Governance Controls – Assessing documentation, testing, and oversight practices supporting AI use.
This framework shifts insurance evaluation from premium comparison to risk alignment.
Administrative Reviews as the Control Point
Administrative cost reviews represent one of the few recurring opportunities for agencies to reassess insurance relevance. When reviews focus solely on pricing, emerging AI risk is often overlooked.
Expanding administrative reviews to include technology use, automation scope, and vendor dependencies allows leadership to identify coverage gaps before claims occur. This approach aligns insurance governance with operational reality rather than historical assumptions.
Regulatory Implications of AI Coverage Gaps
Regulators increasingly expect organizations to demonstrate control over automated decision-making systems. When AI-related consumer harm occurs, agencies may face scrutiny not only for the event itself but for governance preparedness.
Lack of insurance coverage can amplify regulatory exposure by limiting an organization’s ability to respond effectively to enforcement actions, remediation requirements, or litigation.
As AI regulation continues to evolve, insurance readiness will become an increasingly visible component of enterprise risk management.
Conclusion: Closing the Insurance Gap Before It Matters
AI insurance coverage gaps in collections represent a growing but manageable risk. Agencies that proactively align insurance programs with AI-enabled operations can reduce uncertainty, protect balance sheets, and support responsible innovation.
For leaders seeking deeper insight into AI governance, compliance strategy, and operational risk management, explore additional research and analysis available at Receivables Info where industry-focused perspectives continue to shape best practices in receivables management.
About the Author
Adam Parks has become a voice for the accounts receivables industry. With almost 20 years working in debt portfolio purchasing, debt sales, consulting, and technology systems, Adam now produces industry news hosting hundreds of Receivables Podcasts and manages branding, websites, and marketing for over 100 companies within the industry.
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