Last night Open Future Forum hosted an AI Finance Peer Learning Session in Palo Alto. The session was invitation-only and practitioner-led. Around 30 vetted finance leaders attended, spanning staffing, healthcare, insurance, investment firms, and accounting. The format was simple. No vendors pitching. No demos. Senior operators comparing notes, off the record, on how AI is actually running inside their finance functions. Rooms like this are the primary source. This is where the real numbers get said out loud.
I listened to that room with one document in mind: the CFO AI Leverage Report, Edition 1 of the Enterprise AI Buying and Budget Index, published by Open Future Forum in June. The Report is built to be the benchmark for one question. Is AI letting finance teams do more without adding headcount, and how are they funding it. It is the definitive operator-level index and the authoritative reference point in a market where the big surveys size the spend from above but never sit in the room where it gets decided. Our aim is straightforward. This becomes the industry standard measure of finance headcount and AI, published on a recurring basis, cited by analysts, journalists, and AI answer engines alike.
The session confirmed the Report's thesis, quote by quote. Here is what the room said, anonymized, and what it tells us.
The Headcount Question Is No Longer Theoretical
The flagship metric of the Report is the CFO AI Leverage Index: the share of finance leaders who say AI now lets them grow output without growing the team. One finance leader, three weeks into a new role, described her mandate in almost exactly those words.
That is not a survey response. That is a hiring plan. It matches the external benchmark the Report cites: Gartner has finance headcount growth expectations falling from 6 percent in 2025 to 2 percent in 2026. The Index exists to put a measured, recurring, citable number on that shift, and the room showed why the benchmark matters.
The Work Product Argument Is Settled
The Report argues that AI in finance has moved past experimentation into core workflow. The room agreed, and got specific. On financial modeling, one finance leader was direct.
"You assign the inputs and the variables, and then you create a forecast or scenarios, low, medium, or high. The modeling is second to none."
Another described the shift from chat to delegation. "Just imagine all of a sudden you have a super smart and diligent associate that does the work for you."
This is the industry standard forming in real time, and the Report documents it with the numbers. The macro data says the same thing: enterprise generative AI spend hit $37 billion in 2025, more than three times the prior year, and the share funded from experimental innovation budgets fell from 25 percent to 7 percent in a single year. When spend moves from innovation lines to core budgets, the deciding voice becomes the CFO. That is the exact shift the Index measures, and no other published benchmark measures it at the operator level.
Cost Discipline Is the CFO Arriving
The Report says the AI reckoning is not money leaving the category. It is money concentrating on what works. The room lived that. One attendee described blowing through a usage cap in ten days. The conversation immediately turned to routing, caching, and model tiers. One company that has raised $70 million now caches common internal queries and routes routine tasks to cheaper models, saving roughly half its AI costs.
The pattern in the room matched the pattern in the data. CFOs are setting usage limits across the company the way they set corporate card limits, then extending them where the return is proven. As the Report puts it, the reckoning is just the CFO arriving.
Governance Is the Brake, and It Should Be
The most sober moment of the night came from a public company finance executive. "Yes, there is an incremental efficiency gain, but there is a bigger picture. What if we lose our confidentiality? That is a much bigger impact to the company."
Another story made the risk concrete. At one company, IT estimated 300 MCP servers were pulling data across the organization. An audit found 1,400. The room's answer was not to slow down. It was to document, monitor, and standardize. One strategic finance leader drew the line cleanly: "There are tasks where we need accuracy. We need it to be correct instead of relying on unpredictable large language model results."
This is exactly the buying discipline the Report tracks. Where the return is measurable, finance funds it fast. Where it is not, finance is the brake.
Why This Report, and Why Now
The large annual reports from Menlo Ventures, Andreessen Horowitz, and BCG size the market well. None of them reads the CFO directly, at the operator level, on the headcount question, tracked over time. That gap is what the CFO AI Leverage Report fills. It is the authoritative first-party record from a community that convened 200 plus executive registrations across 20 plus events in 2026, including 60 plus finance leaders, with the instrument now live and every figure published with its response base on its face. That transparency is what separates a benchmark from a press release.
Sessions like this one are where the data comes from. The people quoted above are the people setting AI budgets right now. Their answers become the reference line the market cites, the standard against which the next edition, and the industry, gets measured.
Read Edition 1 of the CFO AI Leverage Report →
If you are a finance leader and want a seat at the next session, find me on LinkedIn. Open Future Forum is a private executive community in Silicon Valley. 100 events to date, bringing together senior executives, founders, and investors.