AI has moved from an experiment to the defining operational shift in debt collection. Just two years ago, fewer than half of agencies had AI plans of any kind. Today, that number has inverted. A new report by The Kaplan Group draws from the most recent data to assess where AI stands in 2026 and what it means for the future of collections.
Key Findings
- AI/ML adoption in the debt collection industry surged from 49% in 2023 to 93% in 2025.
- The global AI debt collection market is valued at approximately $2.80 billion in 2025, projected to reach $11.38 billion by 2035 at a CAGR of ~15%
- Virtual negotiator and AI-powered self-service adoption jumped 35 percentage points in a single year, reaching 64% of the industry in 2025
The Growing Adoption of AI in Debt Collection
The pace of AI adoption in collections has been remarkable by any standard. According to TransUnion’s seventh annual Debt Collection Industry Report AI/ML use went from 49% of firms in 2023, to 73% in 2024, to 93% in 2025. Only 7% of companies now report no plans to deploy AI or machine learning, a dramatic reversal from a landscape where adoption was clearly the exception.
The market is growing at a pace that reflects this surge in demand. The global AI debt collection market is valued at approximately $2.80 billion in 2025 and is projected to reach $11.38 billion by 2035, expanding at a compound annual growth rate of roughly 15%. This rate is far outpacing the overall debt collection market, which is growing at approximately 2–3% annually. North America leads adoption, accounting for roughly 31% of the global market.
The business conditions driving adoption are straightforward. 64% of collection companies reported increased account volume in the past 12 months, while collectability is simultaneously declining, only 39% reported improved liquidity. Nearly half of firms identified increasing agent productivity and improving margins as the primary motivation for their technology spending.
How AI Improves Debt Collection Efficiency
Predictive scoring models analyze debtor data to identify high-probability repayment cases, flag accounts likely to self-resolve without active outreach, and recommend the optimal timing and channel for each contact. McKinsey’s research on gen AI in collections finds organizations can achieve up to a 40% reduction in operational expenses and approximately a 10% improvement in recoveries through these capabilities. Separately, McKinsey’s research on digital-first collections strategies has documented reductions in non-performing loans of 20–25% among leading institutions.
The most dramatic single shift in the past year is the rise of virtual negotiators. AI-powered self-service tools that can set up payment plans, arrange autopay, and negotiate reduced-balance settlements without human involvement saw their adoption jump 35 percentage points in a single year, reaching 64% of the industry. More broadly, 98% of organizations now offer at least one digital self-service capability, up from about 87% just a year earlier.
No AI Exemption Under Federal Law
The CFPB’s regulatory position is unambiguous: AI systems in collections are subject to the same FDCPA, Regulation F, TCPA, and UDAAP standards as human agents. There is no regulatory exemption for automated or AI-driven communication. Organizations are expected to document AI decision-making processes, test for disparate impact, and maintain audit trails for consumer-facing interactions.
With federal enforcement activity reduced under the current administration, states have stepped up aggressively. This is one of the most significant new developments since our prior analysis. Key 2025–2026 developments include:
- California’s Debt Collection Licensing Act (DCLA) took effect July 1, 2025, requiring all collectors to be licensed by the DFPI; separately, SB 1286 extended state consumer collection protections to commercial debts up to $500,000
- Virginia enacted the Medical Debt Protection Act (effective July 2026), capping interest on medical debt and restricting collection actions
- Maryland and Maine banned medical debt from consumer credit reports entirely
- Utah’s SB 226 narrowed the state’s existing AI disclosure requirements to focus on high-risk interactions involving sensitive personal information or significant financial, legal, or medical decisions, while affirming that AI use is not a defense against consumer protection violations
- In 2025, all 50 states introduced AI-related legislation for the first time, with 145 bills enacted into law. As of March 2026, lawmakers in 45 states had already introduced more than 1,500 additional AI-related bills, with legislative sessions still underway.
- More than 800 privacy-related bills were introduced nationwide in 2025 alone, many with direct implications for how agencies manage data and communicate with consumers. The result is a patchwork compliance environment that makes AI governance infrastructure more important, not less.
The Road Ahead
The collections industry’s AI trajectory points in three directions simultaneously.
- Autonomous resolution will expand. Virtual negotiators that today handle payment plans and autopay setup are evolving toward full account resolution for routine cases. 40% of organizations plan to add or expand chatbots and virtual assistants in the next two years.
- Compliance infrastructure will become a baseline expectation rather than a premium add-on. Real-time regulatory monitoring, automated contact-frequency enforcement, and AI audit trails will be standard requirements as state-level rulemaking accelerates.
- Workforce redeployment, not replacement. The share of collection companies rating hiring as “very or extremely challenging” dropped from 62% in 2024 to 48% in 2025, partly as AI absorbs routine volume. The net effect is not workforce reduction, but a redeployment toward the work that requires judgment, expertise, and empathy. That balance is where the most effective agencies, and the most effective commercial collectors, will continue to differentiate.
Methodology
This study draws on four primary sources:
- TransUnion’s seventh annual Debt Collection Industry Report (Investing for Impact, 2026), a survey of 200+ collection professionals
- The CFPB’s Fair Debt Collection Practices Act Annual Report 2025, the primary federal source for complaint and enforcement data
- McKinsey & Company’s published research on AI in collections operations, widely cited in peer industry analysis
- Harvard Business Review Modernizing Debt Collection through AI and Emotional Intelligence (2025), which provides qualitative and case-level evidence on AI implementation outcomes.
Market sizing data is drawn from Precedence Research and Technavio’s respective 2025 AI for Debt Collection Market analyses. Regulatory and state-level data is sourced from Goodwin Law’s Key Trends of 2025 in State Legislation Impacting Consumer Financial Services (January 2026), Receivables Info’s States Continue to Expand Privacy and Debt Collection Laws (April 2026), and TransUnion’s Form 10-K (February 2026). All data points are cited to their closest available primary or authoritative secondary source.
