Finance teams are adopting AI tools ahead of governance, turning one of the most regulated business functions into a hotbed of informal experimentation 1. This bottom-up integration is now forcing executives to reconcile measurable productivity gains with oversight, risk and accountability frameworks that lag behind the tools 1.

AI is embedding itself across routine finance workflows where unstructured data once slowed everything — from variance commentary and fraud detection to contract review and close-narrative drafting 1. Glenn Hopper, head of AI and managing director at VAi Consulting, says: "the proliferation of AI happened kind of before governance and before a real plan came about" 1.

The shift is as much cultural as technical. Ranga Bodla, VP of industry and field marketing at Oracle NetSuite, argues AI must remain "a means to an end, as opposed to AI being the end," working inside existing processes rather than replacing them 1. Embedded systems, seamless integrations and protocols such as model context protocol (MCP) are making AI an ambient capability for finance teams 1.

Ease of integration — not cost savings or flashy features — has become the strongest adoption driver. Yet the real bottleneck may be people: Hopper calls out a widening gap between domain expertise and AI fluency, warning that over-restrictive controls can prompt employees to seek unsanctioned workarounds 1. Concerns about data security and model opacity remain, but misunderstanding the tools is an immediate operational risk 1.

Bodla stresses the importance of auditability: "The auditability of it, I think, is critical." Looking ahead, the piece flags emerging AI agents able to execute multi-step tasks, expanding context windows and interoperable systems that could deliver deeper, persistent intelligence — a gradual shift toward systems that bolster judgment and automate routine closure tasks 1.

This content was produced by Insights, the custom content arm of MIT Technology Review, in partnership with Oracle NetSuite. It was researched, designed and written by human writers, editors, analysts and illustrators, with AI tools limited to secondary production processes under thorough human review 1.

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