The most valuable finance AI agent won’t sit in your ERP: It’ll live in Slack

By the time Amrita Singh sits down for her Monday leadership call, the questions have already started to ping her team’s Slack channel. 
A senior engineer wants to know whether the finance team will reimburse a late-night Uber from Terminal 5. Procurement is chasing sign-off on an urgent laptop order.

Two analysts need the last-minute figures for a board meeting slide.
In the past, Singh (the CFO of a fast-growing European software company) would have opened four browser tabs, navigated layers of the ERP, and sent a string of polite emails.

But today looks very different. She replies, “/approve” or “/policy?” and moves on. An AI “action agent” embedded in chat has done the grunt work of checking the Uber fare against company rules, cross-referencing the laptop request with the capital expenditure budget, and pulling the live revenue run rate for the analysts.

The significance of this unremarkable exchange? It points to a profound shift in where the finance function will capture value from artificial intelligence.

AI in finance: Driving efficiency in the day-to-day

For the past two years, fintech vendors have promised self-driving ledgers and autonomous closes. Leaving many CFOs to understandably assume that the pivotal AI innovations would be quickly welded into their ERP suites.

Yet, in reality, the most practical incarnation of finance AI is showing up where day-to-day decisions are already being made: In the tools teams use to collaborate.

Two forces collided to make the above possible.

The first: A philosophical split in how big-tech titans approach agents. Microsoft’s “bounded” Copilot Studio keeps its assistants on tight, enterprise-grade rails. While OpenAI’s Operator aspires to roam the open web, clicking and typing much like an enthusiastic intern, sometimes brilliantly, often haphazardly.

In heavily regulated finance operations, predictability trumps raw possibility, giving bounded agents who sit comfortably inside Teams or Slack and log every step for auditors the early advantage.

The second driver is the technological maturity inside the chat tools themselves. Slack’s Workflow Builder and Microsoft’s Graph APIs have quietly added secure hooks for file uploads, identity checks, and write-backs to back-office systems. A finance bot can now surface a purchase order in a channel, verify the approver’s role via single sign-on, and record the outcome straight into the ERP, with no unsecured screenshots and no shadow IT.

Beyond the collision, modern agent frameworks have also learnt to read company policies, respect role hierarchies, and create a clear audit trail for Sarbanes-Oxley or GDPR examiners. The old objection that “chat isn’t safe for finance” is losing weight.

Early adopters are discovering that the payoff is measured less in autonomy and more in ruthless cycle-time compression, as referenced in our (Payhawk) pilot, where finance teams saw a big shift.

Before, they relied on dashboard nudges and weekly mass emails, but results could still be slow. But once they layered in Slack-based reminders, missing documents came in within hours instead of days, easing the month-end scramble and freeing accountants from constant chasing. Bots flagged validated expense claims for one-click approval and nudged account managers the moment invoices passed due (replacing overnight batch delays).

It wasn’t complex finance logic, but the accumulated minutes saved across these micro-decisions unlocked real, strategic time.

Critics argue that chat-native agents amount to glorified robotic process automation (RPA), albeit wearing a friendly avatar. But there is a qualitative shift.

Traditional RPA followed brittle, pre-written scripts; action agents sense, plan, act and reflect in tight feedback loops, selecting their own tools on the fly — a pattern that analysts have dubbed the SPAR cycle. That ability to reason, however narrowly, means they can adapt to missing data, prompt humans for clarification and learn from rejection — capabilities no rules engine can match.

Timing favours pioneers: Start with the plumbing

Gartner expects that by 2027, a third of all enterprise software will ship with embedded agents and that up to 15% of everyday business decisions could be made autonomously. Yet many organisations remain bogged down in heavyweight AI projects aimed at automating the entire close.

The lower-risk, faster-return route is to insert agents at the collaboration edge, where integration hurdles are lighter and the human-in-the-loop is already staring at the screen.

The strategic lesson for CFOs is, therefore, counterintuitive: Begin with the plumbing, not the palace. Clean the data pipes that feed your spend and approval workflows; expose them securely to your chat platform; and let small, deterministic agents prove their worth chasing receipts, policing policies, and surfacing live KPIs in the daily stand-up. Once that lattice is in place, more sophisticated reasoning (like forecast variance explanations and real-time scenario modelling) have a trustworthy stage on which to perform.

In 2020, the finance team’s window to the world was still the monthly Excel pack. In 2025, it’s the blinking cursor in a chat thread. The smartest agent in Singh’s department isn’t buried in a server rack; it waits patiently in the sidebar, ready to turn a slash command into a controlled financial action.

While the ledger will remain the system of record, the chat window is fast becoming the system of action. Ignore that migration, and tomorrow’s autonomous enterprise will happen — one line at a time — in your competitor’s channel instead.

Explore how our AI Office of the CFO turns Slack into your team’s fastest approval engine — surfacing insights, chasing receipts, and compressing close time, all without touching your ERP. Discover the AI Office of the CFO.