The growth of AI in our industry is undeniable, but the data from the past year reveals we are automating our way into a litigation crisis.

The market for AI in debt collection is on a vertical climb, projected to grow from $2.8 billion to over $11 billion over the next ten years. Today, 57% of agencies are already leveraging AI for predictive analytics and account segmentation. However, this rapid adoption has also created a massive accountability gap. In 2025, complaints regarding debt collection calls surged, with per-capita reports rising 200% from the previous year.

This isn’t a coincidence. As ARM professionals struggle to keep pace with the sheer speed of AI adoption, compliance is falling through the cracks. We are seeing a direct correlation between unvetted AI workflows and a rise in complaints. For leadership, if you don’t implement rigorous compliance protocols into your AI workflows, you may be looking at significant legal exposure and harassment claims very soon.

Governance Must Precede Deployment

Much like an estate plan, AI compliance is not a “set it and forget it” task. If you don’t update a will after a major life change, your assets end up in the wrong hands. Similarly, if you don’t update your AI’s “logic” when regulations shift, your automation may eventually violate current and existing laws.

Therefore, compliance must be baked into the AI’s DNA before a single account is touched, and that starts with rigorous pre-deployment governance. Every AI tool must pass a comprehensive “governance check” to ensure it understands the nuances of the FDCPA and can distinguish between state-specific mandates, such as varying calling-hour restrictions.

This internal vigilance must be coupled with absolute vendor accountability. Because regulatory landscapes are constantly shifting, collections leaders need a direct line to their AI vendors when those changes occur. And in any case, a vendor cannot guarantee a 24-to-48-hour update window for these changes; the tool is just essentially compounding risks.

Finally, this technological framework requires human-first SOPs. When you establish clear guidelines on permitted usage and define exactly where automation ends and human intervention begins, agencies can prevent the human error that occurs when staff rely too heavily on the machine.

Transitioning to 100% Monitoring

Traditionally, compliance teams audited around 1% to 2% of calls. In an AI-driven world, that is no longer enough. If an AI agent makes a mistake, it doesn’t just make it once. It makes it 10,000 times in an hour.

Teams need to move toward real-time, 100% monitoring using AI-driven compliance tools that can analyze every email, SMS, and call for risks as they happen.

The goal is to automate compliance alerts. When an AI agent (or a human assisted by AI) misses a Mini-Miranda disclosure, violates the 7-in-7 rule, or perhaps uses prohibited language, supervisors should receive an automated alert instantly. It only means we need to catch the fire while it’s a spark, not after we’ve received a complaint.

Scaling AI Literacy to the Front Lines

We often talk about training the AI, but we are failing to train the people behind the scenes who manage it. Staff training shouldn’t just be a dry review of the law; it needs to be an engaging look at how the AI actually functions.

Training programs must involve everyone, and that includes collections agents and legal teams, as well as IT and data departments. Staff need to know:

• When human oversight is mandatory. For example, handling a sensitive dispute or a complex estate collection.
• How to spot “Hallucinations.” AI commonly provides information that sounds confident but is factually incorrect. LLMs and other AI tools learn from what you feed them, so make sure you give them enough accurate and timely information.
• Red Flag Reporting. Encourage agents to raise a flag the moment they notice the AI behaving outside of established parameters.

Why Compliance is Your Real ROI

In the rush to automate, many leaders mistake faster for better. But in the ARM industry, speed without a safety net is just a faster way to reach a courtroom. AI is the most powerful tool our industry has ever seen, but without a compliance-first culture, it is a ticking legal time bomb.

To diffuse that bomb, leadership must move beyond the surface-level features of AI and look at the underlying work. For example, vetting beyond the sales pitch.Treat your AI vendor like a co-signer on your legal liability. You wouldn’t hire a collection agent without a background check. Therefore, don’t onboard a “black box” algorithm without a forensic audit. Ask for documentation on how the model handles edge cases—those moments where a consumer’s response is ambiguous or emotionally charged.

Secondly, do what I call “hardcoding the guardrails.” Compliance cannot be an afterthought or a plugin. It must be embedded directly into the software’s logic. If a regulation changes in a specific jurisdiction, your AI should be physically unable to execute a non-compliant action.

Lastly, maintain a rigorous reporting loop that feeds near-misses back into your training modules. Every time a human supervisor has to override an AI suggestion, that data point should be used to sharpen the tool’s regulatory accuracy.

Efficiency is certainly the engine of growth, but in the collections world, compliance is the steering wheel. You can have the fastest car on the track, but if you can’t navigate the turns of the FDCPA or state-specific mandates, you’re eventually going to hit a wall.

Arguably, AI can speed up collections, but it can also make compliance failures harder to contain as they multiply just as fast. In collections, efficiency only creates value when the agency can show that each consumer interaction was handled lawfully, consistently, and with proper oversight.