• Rob Harvey, Chief Product Officer at Sidetrade


• 02.07.2025 10:30 am
#AutonomousAgents #OrderToCash

A new generation of AI is taking hold and it’s set to completely reshape how finance teams run and scale their O2C operations. Rob Harvey, Chief Product Officer at Sidetrade, takes a closer look at agentic AI and its ability to think, plan, and act autonomously.

After years of progress in automation and generative AI - including LLM capabilities coming on leaps and bounds - we’ve seen a new form of AI begin to take hold in the last 12-18 months or so: Agentic AI. 

Think of it like this - automation follows rules, generative AI creates content, and Agentic AI goes a step further. It understands the goal, plans the necessary steps to achieve it, and takes action, all without requiring constant human input.

Being highly adaptive and capable of making human-like decisions in milliseconds, agentic systems are poised to impact nearly every aspect of operational efficiency in finance over time. But it’s in the world of O2C where I see particularly exciting possibilities. 

Whether it’s assessing credit risk, managing disputes, reconciling payments, uploading customer invoices, or making outbound calls, Agentic AI-powered O2C assistants —also known as Autonomous Agents—don’t just assist; they act. For example:

• Autonomous outbound calling: Agentic AI can make 1,000s of personalised calls per day, speaking with customers in their preferred language. Not only can it initiate first contact and follow up, but it can also adapt tone and strategy in real-time, and escalate only when strategic risk is detected. It means every customer can get a call about their invoices.

• Payment automation: It can identify missing remittance or payment allocation details and provide matching information. And because payment auto-matching has become so accurate, businesses no longer need to focus on match rate metrics.

• Promise-to-pay tracking: Agentic AI doesn’t just log outcomes; it ensures every collector protocol is followed precisely, every time, down to capturing wire confirmation and payment dates.

• Inbound customer emails: Not only can it understand sentiment and detect what the email regards, but it can also categorise issues into dispute reason codes, auto-respond where safe to do so, and initiate escalation workflows when necessary.

In the current climate, where finance teams face numerous challenges, including shrinking headcount, rising complexity, and a relentless urgency to secure cash faster, the above has never been more necessary. Granted, intelligent automation has helped, but only to a certain point. Most automation still relies on static workflows and human-in-the-loop supervision. It breaks down under variability, scale, or exception-heavy processes like collections and disputes. 

Agentic AI fills this gap. It adapts to context, acts continuously, and frees finance talent from repetitive follow-ups, leading to a range of impressive benefits, including 50% fewer manual interventions and full coverage of long-tail accounts without increasing headcount. The increased coverage contributes directly to the financial results, with key indicators like DSO ultimately benefiting. Unlike human teams stretched thin, agentic systems respond to volatility with precision and repeatability—never missing a follow-up, never forgetting a priority, and always aligned with your strategic cash goals.

But achieving this level of performance doesn’t happen by accident, despite being able to act with autonomy. To successfully implement agentic AI, there are four essentials every finance team must prioritise:

• Data quality: Just like human-based systems, Agentic AI underperforms without clean, structured, and contextual data. It must possess those behavioral insights to make decisions with precision.

• Integration readiness: Building your own agents opens challenges when it comes to data access and integration with your FinTech stack. Consider embedded, purpose-built Agentic AI in dedicated O2C platforms to overcome these obstacles and deliver a return on investment (ROI).

• Change management: Introducing autonomy means redefining trust, meaning finance leaders must be ready to let go of micro-control and instead orchestrate teams around exception management and strategic oversight.

• Security and governance: Look for a system housed in ISO- and SOC-certified infrastructure, ensuring full data sovereignty, compliance, and auditability.

In addition to the above, for any finance organisation exploring Agentic AI, I always advise that they don’t treat it as a feature, but rather as a co-worker. If you approach it like a tool, you’ll miss the transformation. But if you define the outcomes you want to delegate—collections, disputes, matching—and pair them with clear rules, real data, and the right agent, you’ll gain a teammate who delivers results autonomously, every day.

To do this, though, we need to see both a skills shift and a mindset shift from the finance professional. Yes, the repetitive, rules-based finance operator is being replaced, but not by technology, by a more strategic, yet still human role; an AI orchestrator, exception handler, data-driven negotiator, with the time to focus on relationships, risk scenarios, and strategic decisions. Professionals must now understand how to supervise agents, interpret AI-led decisions, and intervene only when the system flags meaningful anomalies.

Is there still hesitance? Yes. But as one finance executive told me, once you start to see the benefits, fear gives way to trust: “My collectors were afraid of losing control. But once they saw firsthand how an AI-powered O2C assistant could follow our rules better than we could—every time—they saw the upside. It doesn’t replace us. It finally lets us stop doing the robot’s job.”

And it’s that very shift in mindset that unlocks real progress. So, start small, and start with a real problem, but most importantly, start now. Every delay risks missed cash, strained liquidity, and reactive firefighting. CFOs can’t afford to wait for input or workflows that crack under pressure.