Video · May 19, 2026
Go Further with Forward Finance
About this video
The pressure Finance organizations feel in 2026 is distinct from the familiar stresses of inflation or geopolitical uncertainty. It is the pressure of a world that now expects in minutes what used to take months, and Finance sits at the center of that demand. Forward Finance is OneStream's framework for this moment: a new operating model where AI amplifies Finance rather than replacing it, and where the Office of the CFO shifts from scorekeeper to control tower. Research across dozens of companies reveals that the most forward-looking Finance organizations are already using AI to augment staff, optimize operations, and transform core processes. But the AI gap is widening, held back by three persistent barriers that become even more consequential in an agentic world: poor data quality, insufficient controls and context, and weak governance.
Key takeaways
- Finance has moved from scorekeeper to control tower, and the operating model must catch up. Markets shift overnight, demand moves in real time, and decisions that once took months are now expected in minutes. Finance organizations that continue operating as backward-looking reporting functions will cede strategic relevance to those that have rebuilt their processes around real-time insight and AI-driven decision-making.
- AI amplifies Finance, but only when built on trusted data with proper context. The most forward-looking organizations use AI to augment their teams and transform core processes like planning and forecasting. However, public AI models lack the business context, rules, and operational knowledge that Finance requires. Without that context, AI does not deliver insight. It delivers fast confusion.
- The AI gap is already widening, and governance is the critical missing piece. Half of Finance leaders surveyed admitted to making decisions on bad data in the past year, and heavy AI users were four times more likely to fall into that group. AI can generate answers quickly, but in Finance, an answer that cannot be traced, audited, or defended is not an insight. It is risk at scale.
Video Transcript
Hello, how's everyone doing? Good? I've been thinking a lot about 2026 and how I've been feeling this year, and I would characterize it as nervous excitement. And why do I say that? Basically, I'm feeling that we're in high stakes mode.
Not because of inflation, not because of geopolitics, the normal things that we worry about, but because the pressure that we all are feeling to do more faster than ever before. The truth is, the world is now changing and accelerating faster than we've ever experienced.
Markets shift overnight, demand moves in real time, and now things that used to take months, decisions that we had to contemplate now are expected to be done in minutes. Finance is no longer the scorekeeper.
It's the control tower for your business. The future isn't reporting on what happened. It's deciding what happens next. The market is now demanding that you get real value out of AI at scale. I know we're all tired of hearing AI over and over and over, but that's the fact that we all face running businesses.
While most finance orgs have been experimenting and finding pockets of value with artificial intelligence, there's a growing belief now that you must fundamentally rethink a lot of processes in your business in order to extract that value that AI can bring.
I know we're all feeling that. Well, we call this forward finance, a new operating model for the office of the CFO. Where AI doesn't get replaced, it doesn't replace finance, it amplifies it. After benchmarking dozens of companies, we found that the most forward-looking are using AI to augment their staff, augment their workforce, help you be more productive, optimize operations, look for ways that you can improve your business, and transform core financial processes like planning, forecasting, and other analytic tasks.
Our research uncovered, though, that the AI gap isn't coming to finance. It's already widening. And there are three things that are holding finance back. These are consistent, these are themes that you're used to, but they're even more important in the agentic world.
That's poor data. It's lack of controls and context around that data and weak governance. Finance leaders agree that trusted data is critical. Yet, half of our study, the folks in that admitted that they've made decisions on bad data in the last year.
And even more importantly, and the kicker of those organizations that made bad decisions, they were 4x more likely, four times more likely to be users, big users of AI. So think about that. That's risk.
That's risk. Why is that? Public AI models, they lack context of your business, your data, your rules, your operations. And without context, AI is just going to deliver fast confusion. Finally, there's governance.
AI can generate answers. But if in finance, if you can't trace it, if you can't audit it or defend it, it's not insight. It's just risk at scale.
Related Resources
Look into the future of Finance
Demo: Modern Financial Close
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