Implementing advanced AI technologies in finance | MIT Technology Review

SponsoredIn partnership withOracle NetSuite In finance departments that have long been defined by precision and control, AI has arrived less as a neatly managed upgrade than as a quiet insurgency. Employees are already using it while leadership races to impose structure, governance, and strategy after the fact. The result is a paradox: one of the most tightly regulated functions in the enterprise is now among the most experimentally transformed. REGISTER TO WATCH What’s emerging is a layered shift in how work gets done. From variance commentary and fraud detection to contract review and close narrative drafting, AI is embedding itself across workflows, particularly where unstructured data once slowed down everything. Yet, as Glenn Hopper, head of AI and managing director at VAi Consulting, puts it, “the proliferation of AI happened kind of before governance and before a real plan came about.” That bottom-up adoption is forcing a recalibration at the top, where executives must now reconcile productivity gains with oversight, risk, and accountability. Just as critical is reframing AI’s role. “AI as a means to an end, as opposed to AI being the end,” says Ranga Bodla, VP of industry and field marketing at Oracle NetSuite, underscores a growing consensus: the technology is most effective when it disappears into existing processes rather than outright replaces them. Embedded systems, seamless integrations, and tools like model context protocol (MCP) are accelerating this shift,...