Debt collection has always been one of the most manual and costly areas of finance. When invoices go unpaid, accounts receivable (AR) teams either chase customers themselves or outsource the work to debt collection agencies. These agencies typically charge more than 15% of recovered amounts, yet their processes are still largely manual. They rely on people making phone calls, sending emails, and escalating accounts step by step. In other words, they are just outsourced humans doing the same manual work — only at a high cost to the business.
AI agents are now transforming this landscape. By automating dunning workflows and collections processes, they make chasing overdue invoices faster, cheaper, and more scalable. They can handle two-way conversations over email, follow up on promises to pay, escalate intelligently, and even use new channels like AI-driven voice calls. The result is lower Days Sales Outstanding (DSO), stronger cash flow, and less reliance on costly third parties.
Why traditional debt collection falls short
The standard approach to collections has long relied on either in-house AR clerks or outsourced agencies. In-house teams are expensive to scale as volumes grow, while outsourcing reduces visibility and still depends on people working cases manually.
Traditional dunning tools have tried to automate the process with scheduled reminders, but these lack personalisation. Customers quickly recognise templated emails and often ignore them. That is why so many overdue invoices eventually end up with human collectors.
How AI agents automate collections and dunning
AI agents act as digital credit controllers who can manage collections end to end. They do not just send reminders — they engage in contextual, human-like interactions across channels.
Contextual, personalised outreach
AI agents chase overdue invoices in existing threads so communication feels continuous rather than fragmented. They adapt tone, timing, and frequency to each customer’s payment behaviour, personalising collections at scale.
Two-way conversations
Unlike legacy systems, AI agents can handle replies. If a customer asks for an invoice copy, the agent sends it instantly. If they dispute a charge, the agent logs and escalates it. Collections become dynamic conversations instead of one-way reminders.
Promise-to-pay tracking
When customers promise to pay by a certain date, AI agents record it, pause reminders, check again after the deadline, and resume if payment has not arrived. This mirrors what human collectors do but without the overhead.
Automated escalation
AI agents escalate gradually, from polite reminders to firmer follow-ups, always maintaining a professional tone. They can also flag accounts for human oversight if payment fails despite multiple attempts.
AI voice calls: A new channel in debt collection
Large language models (LLMs) have unlocked a new capability: AI-powered voice. Agents can now place outbound calls, leave voicemails, and interact in natural spoken dialogue.
For B2C collections, AI voice calls are already emerging as a powerful tool. In B2B, companies may be hesitant to let AI call customers directly today, but voicemail is already highly effective — it creates urgency and reminds customers without requiring expensive human callers. Over time, as AI voices become indistinguishable from humans and capable of handling complex dialogues, voice agents will be used even in B2B collections.
This means debt collection will no longer be limited to email and manual phone calls. AI opens up a multichannel strategy that mirrors the effectiveness of human collectors, but at scale and with much lower cost.
Outsourcing vs AI agents
Outsourcing collections to agencies or shared service providers has long been the default solution for companies with growing AR. But this model does not solve the core issue — the work is still manual, carried out by people in another location, and charged back at a premium.
AI agents offer a smarter alternative. They combine the consistency of software with the conversational intelligence of a human collector. They work 24/7, never miss a follow-up, and can engage across email, chat, and voice. Instead of outsourcing to agencies that rely on human labour, businesses can deploy AI agents that scale instantly and deliver higher collection rates at a fraction of the cost.
Conclusion
Debt collection is no longer confined to manual chasing, expensive outsourcing, or rigid dunning software. AI agents are redefining the process by handling contextual outreach, managing two-way conversations, tracking promises to pay, escalating intelligently, and even using voice channels to reach customers.
For CFOs, the benefits are clear: faster collections, lower DSO, reduced bad debt, and less reliance on costly collection agencies. For AR teams, AI takes on the heavy lifting, allowing humans to focus on disputes, escalations, and strategy.