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AI is becoming increasingly common in debt collection. New tools promise faster follow-ups, automated conversations, and the ability to manage thousands of accounts at once. On paper, it sounds like the obvious solution. More efficiency, lower costs, and less reliance on internal teams.
But there’s a key question most businesses don’t ask: does it actually get you paid? Because in credit control, speed and scale only matter if they lead to one outcome — cash in the bank.
Why AI Is Gaining Traction
It’s easy to see why AI is being adopted. It can send reminders instantly, follow up consistently, and operate across multiple channels without increasing headcount. For businesses dealing with high volumes of invoices, that level of automation is appealing.
AI also brings consistency. Messages are standardised, compliance is built in, and there’s no risk of human error or variation in tone. In tightly regulated environments, that can be a real advantage. For early-stage chasing and simple reminders, AI can play a useful role. It keeps invoices visible and reduces the administrative burden on internal teams.
But this is only one part of the process.
Where AI Starts to Break Down
The assumption behind most AI tools is that unpaid invoices are simply the result of poor follow-up. In reality, that’s rarely the case. Invoices are usually unpaid because something is getting in the way. There may be a dispute that hasn’t been resolved, a missing purchase order, or an internal approval delay. In some cases, your invoice has simply dropped down the priority list.
Automation doesn’t solve these problems. It just repeats the request for payment. And when the same message is repeated without resolution, it quickly becomes easier to ignore.
Payment Is a Behavioural Problem, Not a Process Problem
One of the biggest misunderstandings around credit control is treating it as an operational task rather than a behavioural one. Getting paid is not just about sending reminders. It’s about influencing decisions.
Customers choose when to pay. They prioritise certain invoices over others. They respond differently depending on who is contacting them and how the conversation is handled. This is where AI struggles. Even with advanced language models and sentiment analysis, it lacks one critical factor: accountability.
Why People Respond Differently to Humans
Research from Yale University found that borrowers who were contacted by AI repaid less of their debt than those contacted by humans. Even after a year, repayment rates remained lower when AI handled the initial interaction. More importantly, people were less likely to keep promises made to AI.
The reason is simple. A commitment made to a machine does not carry the same weight as a commitment made to a person. There is less pressure, less accountability, and less emotional investment in following through. In practice, that means more delays, more broken promises, and ultimately less cash collected.
Chasing Is Easy. Resolving Is What Gets You Paid
Most AI tools are built around one function: chasing. They send reminders, follow up automatically, and maintain contact at scale. But they don’t resolve the underlying issues that are preventing payment.
Resolution requires conversation. It means asking the right questions, identifying the problem, and taking action to remove it. That could involve clarifying an invoice, addressing a dispute, or helping a customer move the payment through their internal process. Sometimes it simply means ensuring your invoice stays front of mind. This is where human credit control makes the difference.
The Risk of Relying on Automation Alone
Automation can improve efficiency, but it can also create a false sense of control. On the surface, everything appears to be happening. Emails are being sent, reminders are going out, and activity is being logged. But if payments are still delayed, the underlying problem remains.
In some cases, starting with automation can actually make recovery harder. If the first interaction lacks impact, it sets the tone for slower payment behaviour from the outset. Once that pattern is established, it becomes difficult to reverse.
Where AI Does Have a Role
This doesn’t mean AI has no place in credit control. Used correctly, it can support the process. It can handle routine communication, flag high-risk accounts, and help prioritise activity. It can also improve consistency and efficiency in early-stage collections.
But it works best as a support tool, not a replacement. The moment a situation requires judgment, negotiation, or problem-solving, human involvement becomes essential.
Why Human Credit Control Still Wins
At its core, credit control is about people. It’s about understanding why a payment hasn’t been made, having the confidence to address it, and guiding the conversation towards a resolution.
Human credit controllers bring accountability, adaptability, and commercial awareness. They can navigate difficult conversations, respond to changing situations, and build relationships that encourage payment rather than resistance. That combination is what drives results.
A Smarter Approach to Getting Paid
The most effective approach to credit control is not choosing between AI and humans. It’s understanding where each adds value. Automation can support consistency and scale, but when it comes to actually getting invoices paid, human interaction remains the deciding factor.
At My Credit Controllers, the focus is on what makes the biggest difference. Not just chasing invoices, but resolving the issues behind them. Because ultimately, getting paid isn’t about sending more messages. It’s about making sure those messages lead to action. If you're struggling with any unpaid invoices and need human outsourced credit control, contact us!
