Agentic AI is shaking up the future of finance leadership

By Mark Sheldon, CTO, Sidetrade

 Forget RPA. Today’s AI agents bring autonomy, context, and decision-making power to complex financial processes like Order-to-Cash (O2C). Agentic AI is reshaping finance teams from the ground up

A new wave of AI has landed, and it’s already having a knock-on effect across businesses. Taking hold in the last 12-18 months or so, Agentic AI is somewhat different to its earlier counterparts. Rather than simply making predictions, following pre-defined rules, and relying on humans to handle exceptions – like traditional RPA and earlier AI solutions were built to do – instead, it operates with purpose and reasoning. Opening the door to autonomy with intent, it understands context and executes actions without needing explicit prompts or scripts, in pursuit of achieving a specific goal.

Not only is it proving revolutionary across all manner of industries and functions, gaining traction quickly in sectors where autonomy, decision-making, and complex workflows offer high value, but it’s also impacting how business leaders approach the structure and roles within their teams.

Multi-entity finance environments

From customer service to software development, Agentic AI is already busily reshaping the way work gets done far and wide. However, for me, given that Agentic AI is, by design, great at managing repetitive but complex tasks, finance stands out as one of the most promising areas for this technology.

In multi-entity finance environments in particular – spanning countries, currencies, ERPs, languages and large organisations – software, automation and many manual interventions are the norm. And it’s here that Agentic AI-powered Order-to-Cash (O2C) assistants will no doubt thrive.

There are so many agent use-cases, from cash collection calls and email handling, cash application validation calls and smart reconciliation to one-click portal integration; this technology can coordinate each with precision and autonomy. The result: large finance organisations can now…

• Cover global portfolios with consistent 24/5 execution
• Handle thousands of additional interactions per day without scaling headcount
• Ensure data standardisation and clean execution across entities

All of the above are well known pains for a CFO. By nature, humans are unreliable (they have sick days and annual leave), they get frustrated when their twentieth call of the day goes to voicemail and they will probably forget to write up notes on a couple of their daily calls. Agents won’t do any of these.

For CFOs and CEOs, this isn’t just a leap in efficiency, it’s a structural shift in enterprise control. Agentic AI transforms finance from a cost centre into a real-time command centre: accelerating liquidity, eliminating operational noise, and enabling leadership to act with precision at the pace of business. More importantly, it equips finance leaders with the resilience and agility to navigate volatility, turning uncertainty into advantage, and disruption into decisive action.

Today, perhaps you have 10,000 lower-value (“long-tail”) accounts who you just chase with dunning emails and occasional manual follow-up. Tomorrow you could decide to execute agent dunning calls and agent follow-up. Every account would get almost the same experience as your high-value accounts. You can imagine the impact on your collection efficiency. So it’s not all about replacing the human workforce.

Rethinking workforce planning

In leading enterprises, a new class of manager is emerging, one that doesn’t just lead people, but orchestrates a hybrid workforce of humans and intelligent agents. AI is not replacing these leaders. They are becoming the first generation to manage it, integrating autonomous agents into daily operations to drive speed, consistency, and scale.

The shift is no longer about growing headcount. It’s about scaling intelligence. Forward-thinking CFOs and CEOs are redesigning roles from the ground up. Collection agents are evolving into relationship strategists focused on complex negotiations, controllers are shifting from retrospective reporting to real-time risk governance, and shared services are becoming dynamic, AI-augmented ecosystems.

The advantage isn’t in automation alone; it’s in amplification. By offloading repetitive, rules-based work to agentic AI that never sleeps, never forgets, and never deviates from the best processes, organisations free their people to focus on what humans do best: judgment, creativity, and strategic action.

Those who embrace this new model aren’t just adapting, they’re gaining a competitive edge. Because in the age of intelligent co-workers, the winners won’t be those who scale faster, but those who scale smarter.

The CFO’s 5-step blueprint for implementing Agentic AI

1. Map your friction zones: Audit your O2C processes. Identify where manual effort still dominates, where exceptions slow down performance, and where standard automation has already hit its ceiling. These pain points are your entry points for agentic automation.
2. Evaluate your data infrastructure: Put simply, poor data = poor decisions. Agentic AI can’t reason with incomplete or siloed data, and the quality of your inputs defines the intelligence of your agents. Ensure you have access to clean, contextual, and behaviour-rich data across all systems, including ERP, CRM, ticketing, and payment platforms. If your data isn’t ready, your AI won’t be either. Clearly, there is no point in making 10,000 calls today and the same again tomorrow, even if you have agents that can do this very cost effectively. Smart agents (powered by all your internal data) are essential for success.
3. Start narrow, scale fast: Keep it simple. Not all tasks should be agentic from day one. Define where full autonomy is lowest risk (e.g. outbound collections) and where human validation remains critical. And remember, early wins build internal trust and momentum, so aim to launch focused use cases—such as collections and payment matching—where agentic agents can demonstrate value quickly.
4. Prepare your people: With cultural buy-in just as critical as technical integration, how do leaders ensure that the people within their organisations fully harness this technological shift, rather than resist it, and overcome fears around agentic AI and human replaceability? The answer here is to bring teams into the loop early. Show them the data and proof that agents work and why; this is how you earn the trust in AI.
5. Beware of building agents outside of your operational software: Let’s be clear, agents won’t automate 90% of your teams in the next three years (despite what the AI visionaries want you to believe). That means you’ll still need to handle exceptions, manage agent hand-offs, and support human users who are doing the complex work agents can’t. With that in mind, focus on fully embedding them into your O2C systems.

One last thought: agentic transformation here isn’t to go “fully autonomous” overnight, building everything at once. Rather, it’s about laying the right foundations for controlled delegation and scalable intelligence. But timing matters. The leaders in this new era won’t be those who wait until it’s safe or perfect. They’ll be the ones who move early, build smart, and scale intentionally. Because in the age of agentic AI, advantage accrues to those who architect the shift, before they’re forced to react to it. Now is the time to start.