AI-shoring operational finance

In the enterprise, it's not uncommon for 100 person teams to handle operational finance. Unlike strategic finance, FP&A or month-end accounting, this work is high velocity, constant and relentless. It's the back office function that ensures money moves smoothly in and out of a business and touches thousands of customers and suppliers.

It also requires context and judgement — which is why the headcount behind it has always scaled linearly with revenue. Consider that every customer is slightly different. Every supplier has their own quirks. And the knowledge behind each of them lives in someone's head.

Given the right context, agents are now remarkably good at making judgment calls. That makes them especially suited for a domain that's full of edge cases, where rule-based approaches were never able to encode the actual work. But almost all AI today is still built for single-player productivity. Prompts, co-pilots, chatbots. Running large-scale enterprise operations end to end is a fundamentally different problem.

Today, the only way to scale this work is to hire more people or outsource it. Most large enterprises do both. Soon, agentic systems will handle this work at scale. Once they do, the role of the operator shifts. Instead of drowning in day to day operations, they'll become managers of autonomous agents. Reviewing exceptions, defining processes and deciding how edge cases get handled. The system gets better over time because every human intervention contains signal.