The finance function is the latest enterprise department to get a full AI-native overhaul. On May 5, 2026, OpenAI and PwC announced an expanded collaboration to build what they’re calling the first AI-native finance function at enterprise scale - combining agentic AI with human supervision to reshape how finance work actually gets done.

This is not a pilot program or a proof of concept. PwC and OpenAI are building real AI agents that are already processing contracts, managing investor communications, and automating the routine work that eats up finance teams’ time. And they’re doing it inside OpenAI’s own finance organisation first before rolling it out to enterprise clients.

What They’re Actually Building

The scope is broad. PwC and OpenAI are building agents around the core operating rhythms of finance: planning, forecasting, and reporting; procurement and payments; treasury and tax; and the accounting close cycle.

The first production deployment is a procurement agent built inside OpenAI’s finance org. Early results are concrete:

• OpenAI’s team used Codex to process five times more contracts with the same headcount
• A purpose-built tool called IR-GPT handled more than 200 investor interactions during OpenAI’s recent fundraising round

Sarah Friar, CFO at OpenAI, described the shift this way: “AI gives finance leaders a much deeper ability to see around corners and act faster.”

The practical capabilities these agents bring to finance teams include monitoring payments and exceptions in real time, reviewing contracts and invoices against policy, updating forecasts as conditions change, preparing reporting materials automatically, and surfacing risks before month-end or quarter-end close.

Why This Partnership Matters

The PwC relationship gives OpenAI a distribution path into large enterprises that professional services firms have always owned. PwC has relationships with most of the Fortune 500. Plugging AI agents into those relationships - and into the finance function specifically - puts OpenAI’s technology at the heart of how major companies operate.

For CFOs and finance leaders, this is a signal that AI agents in finance are moving from experimental to expected. The finance function is heavily workflow-driven, document-heavy, and full of repetitive reconciliation work. Those are exactly the conditions where AI agents deliver fast, measurable returns.

What This Means for Business

Finance teams at most organisations are still doing significant amounts of work manually that could be automated: reconciling invoices, chasing approvals, preparing close packages, building forecasts from scratch each quarter. The PwC-OpenAI model puts a template for AI-native finance on the table.

The early pattern emerging from AI agent deployments in finance is consistent: the highest-value use cases are not the glamorous ones. They’re contract processing, exception monitoring, and the close cycle - the unsexy, high-volume workflows where errors are costly and speed matters.

For businesses that haven’t started this process, the gap is widening. Finance teams at companies using AI agents are processing more work, catching more anomalies, and closing faster than those still operating manually.

The strategic question for any CFO right now is not whether to use AI in finance. It’s which workflows to prioritise first and whether to build internally, engage a consulting partner, or deploy an off-the-shelf agent. For most mid-market and enterprise businesses, the honest answer is that they need help figuring that out before they need help building it.

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Enterprise DNA helps businesses identify where AI agents will deliver the fastest return and how to deploy them without the guesswork. If your finance team is still doing manually what these agents can handle in minutes, book a discovery call to talk through where to start.