Automated credit tools offered by global fintech providers now go far beyond simple scoring. They combine AI driven collections prioritization, real time cash at risk visibility, predictive analytics that can identify delinquency 30–60 days in advance and fully automated cash application workflows. These systems automate large parts of the credit to cash cycle ; from onboarding and credit reviews to collections and dispute handling; helping companies reduce DSO (Daily Sales Outstanding); the average number of days it takes a company to collect payment after issuing an invoice; improve working capital, and operate more efficiently with fewer manual tasks.


What makes these tools even more powerful is the statistical impact they have on business outcomes. Research shows(1)


that companies using AR (Accounts


Receivable) and credit automation tools experience a 10– 15% reduction in bad debt write offs and an additional 15% reduction when invoicing processes are automated. They also see DSO reductions of up to 22%, meaning faster payments and fewer overdue invoices. Efficiency gains are equally compelling: AI supported AR systems can increase team productivity by up to 40%. 95% of companies using these tools report significant operational efficiency improvements.


It is true that AI and automation are transforming credit risk by helping teams identify warning signs earlier, predict customer behaviour more accurately and manage large portfolios with far greater speed and consistency than manual processes ever could.


Still, despite these advantages, I strongly believe that human judgment remains essential. A strong risk analyst and a good collector needs more than data — they need emotional intelligence and the ability to read situations.


Sometimes you walk into a customer’s office, meet their team, and instantly feel they are reliable. And sometimes you encounter what looks like a “…desk company…”, with one laptop and little substance behind the façade. No AI system can interpret the subtle, cultural, credibility based signals in these moments. A machine cannot sense hesitation, confidence or maturity — but humans can.


This is why we must understand the roles of AI, automation and human judgment in the credit to cash process:


Automated credit tools are the systems that run our end to end credit to cash process; AI is the intelligence inside them that predicts risk, prioritizes actions, and improves outcomes. We design both to work together: automation for scale and consistency, AI for foresight and humans for judgment.


Even so, large companies rarely adopt these systems instantly. They often start cautiously with pilots and isolated use cases. According to enterprise AI


studies(2) , two thirds of organizations are still in pilot


or experimental phases, mainly due to integration, data and governance challenges. However, the trend is unmistakable: adoption is accelerating fast. AI production use cases doubled in 2025and Fortune 500 companies are dramatically increasing investment, especially as they see proven results : lower bad debt, reduced DSO, and large efficiency gains.


Even Mel Robbins, the author & podcaster captures this reality with humor. In her podcast, she says that most people panic about AI without even knowing the basics, yet we are already living with it every day, whether we notice it or not. It is funny…but also very true: fear often comes from misunderstanding, not from the technology itself.


As we move forward, my role; and our role as credit leaders; is not to choose between humans and AI…but to orchestrate the best of both. AI gives us unprecedented visibility, speed, and predictive power; our teams bring context, experience and sound judgment. When we combine them, we build credit organizations that are not only more resilient…but also more strategic, scalable and future ready. And that is exactly where our focus must be: shaping a credit function that protects cash, strengthens relationships and positions the business for long term success in an increasingly data driven world.


Elif Imer Global Director, Credit and Collections, ADM E: elif.imer@adm.com


(1) Resolve: 17 statistics linking AR automation to lower bad debt write offs(June 12, 2025). EY: AI driven productivity is fueling reinvestment (Dec 2025) Accenture: Companies with AI led processes outperform peers(Oct 10, 2024)


(2) McKinsey: State of AI: Global Survey 2025 (Nov 5, 2025) Deloitte: State of AI in the Enterprise 2026. ISG: State of Enterprise AI Adoption 2025.


23 | ADMISI - The Ghost In The Machine | Q1 Edition 2026


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