It is a redesign of how finance operates
Most CFOs are experimenting with AI. They are piloting copilots, testing document automation, improving forecasting support. It feels measured. Responsible.
But it is too incremental.
The real shift is not about automating tasks. It is about redesigning how financial workflows are built, and what parts of the Finance stack are still necessary.
The Hidden Weight of the Finance Stack
Enterprise Finance has been constructed around a simple assumption: building software is expensive. So organisations bought systems. Then added systems. Then integrated them.
ERP at the core. Around it, tools for P2P, O2C, consolidation, reporting, planning and BI. Each layer solving a problem. Each introducing boundaries where data must move, be validated and reconciled.
The stack works. But a significant portion of the spend goes toward moving and reconciling data, not generating decisions.
AI changes that equation.
For the first time, core financial rules and decision logic can be translated directly into executable workflows. Instead of adapting processes to fit software constraints, organisations can build systems around the way the business actually operates.
That reduces friction. More importantly, it reduces reliance on software layers that exist only to coordinate other systems.
And once that coordination layer becomes optional, the economics shift. It becomes cheaper to build focused workflow logic than to carry overlapping platforms designed for a different era.
From Feature to Execution Layer
Many organisations are adding AI as a feature inside existing tools. A summarisation button. A copilot in reporting. A chatbot for policy queries. Useful, but incremental.
The real leverage appears when AI becomes part of execution itself.
Invoice processes that once depended on manual review can now run at scale with far less intervention. Judgement-based risk assessments can be converted into consistent, transparent decision logic. Global finance teams can align processes before embedding them into new ERP systems, rather than digitising inconsistency.
In each case, AI is not supporting the workflow. It is running it.
That is the difference between adding capability and changing how work gets done. And when execution changes, operating leverage follows.
Governance Should Accelerate Value. Not Delay It.
Most hesitation around AI is not about whether the models work. It is about when to move.
Some organisations wait for perfect data. Others delay decisions over cost predictability or platform choice. Many try to automate workflows that were never redesigned.
But waiting for certainty often costs more than moving with discipline.
Foundations improve through use. Control strengthens through iteration. Value compounds through execution, not preparation.
Governance should be deliberate but light. Clear guardrails. Human oversight where material risk exists. Transparent measurement of cost and impact. The goal is disciplined acceleration, not delay.
AI does not weaken control. It makes it explicit. Once financial logic is codified, it becomes measurable. Once workflows are modular, cost per execution becomes visible. Once exceptions are engineered, risk becomes predictable. That is stronger control, not weaker.
The Emergence of AI-native Finance
The future Finance function will not be defined by how many systems it runs. It will be defined by how clearly its financial logic is embedded into how work gets done.
Core platforms remain. But the layers around them become lighter, because the real value moves into codified rules: how revenue is recognised, how approvals escalate, how exceptions are handled, how risk thresholds are applied.
For example, instead of running a separate workflow tool to manage deal approvals and project staffing, Finance can embed the approval logic directly into the process itself. When a deal reaches a defined probability threshold, resources are allocated automatically. If margin assumptions fall outside tolerance, escalation triggers immediately. The logic sits in the workflow, not in an additional system.
That is a fundamentally different operating model. Changing a process no longer means replacing software. It means adjusting the rules behind it.
This is not about replacing teams. It is about shifting Finance from coordinating systems to governing performance.
The CFO’s Strategic Question
The question is no longer, “Where can we test AI?”
It is this:
If we were building Finance today, what would we NOT build the same way?
That is not a technology discussion. It is a capital allocation decision.
The CFOs who answer it early will not simply optimise Finance.
They will define its cost structure for the next decade.
