This article was originally published in Perspective by CRF, October 1, 2025.
Collections professionals are facing a quiet crisis. Not one of capability, but of capacity. The daily grind of managing accounts receivable has become increasingly unsustainable, with inboxes overflowing and burnout rising. The problem isn’t just operational, it’s strategic. When collectors are buried in administrative tasks, the financial health of the organization is at risk.
At the heart of the issue is email. According to industry data, collectors spend an average of eight minutes per email. This time isn’t spent on high-value activities like negotiating payments or resolving disputes. Instead, it’s consumed by context-switching: locating account details, parsing long email threads, extracting relevant information, and manually updating systems. Multiply that by hundreds of emails per week, and the cost, in both human and financial terms, becomes staggering. For these reasons, CFOs are turning to automated collections software. But AI isn’t always a cure-all.
The Hidden Cost of Inefficiency
Busywork in collections is more than a morale killer – it’s a direct threat to working capital. When collectors are overwhelmed, accounts go unaddressed, disputes linger, and follow-ups are missed. These delays often lead to increased write-offs and deteriorating customer relationships.
Recent trends show that bad debt is on the rise, with many organizations reporting a doubling of write-offs year-over-year. As macroeconomic pressures mount, finance leaders are seeking ways to shore up their positions. But without addressing the root inefficiencies in collections workflows, even the most robust financial strategies may fall short.
Automated Collections Software: AI Isn’t a Cure-All
Faced with mounting pressure, many organizations turn to automation, particularly artificial intelligence (AI), as a potential solution. The appeal is understandable: AI promises speed, scalability, and reduced manual effort. But the reality is more complex.
AI, when deployed without thoughtful oversight, can be a blunt instrument. Poorly implemented automation risks misclassifying communications, mishandling sensitive customer interactions, and eroding trust. In collections, where nuance and relationship-building are critical, this can be especially damaging.
The real challenge isn’t access to AI; it’s trust in it. Finance professionals need to be confident that automation will support, not supplant, their judgment. That means building systems that are not only intelligent but also transparent, adaptable, and accountable.
Human-Aided Automation: A Smarter Path Forward
One emerging best practice is the concept of “human-aided automation.” Rather than replacing collectors, this approach positions AI as a collaborative partner that handles repetitive tasks while leaving room for human oversight and intervention.
Effective human-aided automation tools typically:
- Categorize inbound emails (e.g., disputes, payment confirmations) for easier triage
- Extract and summarize key data from email threads
- Recommend next steps and draft responses for collector review
- Create tasks based on email content and required actions
- Learn from collector edits to develop a personalized communication style
Crucially, these systems offer a verification step — a single click that allows collectors to approve, adjust, or override AI-generated actions. This feedback loop not only builds trust but also trains the AI to improve over time, aligning its outputs with the team’s standards and tone.
From Bottleneck to Breakthrough
Organizations that have embraced this approach are seeing measurable results. By targeting the “eight-minute email” bottleneck, some have reduced handling time to just 2.5 minutes, a more than threefold increase in capacity. This translates into faster dispute resolution, more proactive outreach, and a tangible impact on cash flow.
But the benefits go beyond efficiency. By automating the mundane, collectors are freed to focus on what they do best: building relationships, negotiating payments, and solving complex problems. The result is not job elimination, but job elevation.
Designing for Trust and Transparency
As finance departments look to the future, the goal should be more than just automation—it should be transformation. That means:
- Investing in tools that support human judgment: AI should enhance, not replace, the expertise of collections professionals.
- Prioritizing trust and transparency: Systems must be explainable, auditable, and adaptable to changing needs.
- Focusing on outcomes, not features: The true measure of success is improved cash flow, reduced bad debt, and higher team satisfaction.
Ultimately, the path forward lies in balancing innovation with empathy. By designing collections workflows that respect both the complexity of the work and the people who do it, organizations can turn burnout into breakthrough – and collections into a strategic advantage.