Budget season is starting and most finance teams are finding the AI line is the most evasive line on the page.
You lived through the year. AI spend came in higher than planned and moved in ways nobody could foresee or forecast. And when the board asked what it produced, the honest answer probably was “we’re working on it.”
Only 7% of leaders say they have established ROI from AI, even as nearly one in four face investor pressure to prove it (KPMG Global AI Pulse, June 2026). Meanwhile, 93% of enterprises have already blown past their AI budgets (McKinsey, July 2026). Forrester expects enterprises to defer a quarter of planned AI spend into 2027, as tighter financial scrutiny stalls production rollouts and kills proofs of concept before they ship (Forrester, October 2025).
Fewer than one-third of decision-makers can tie AI value to their organization’s financial growth, so CEOs will increasingly route AI investment decisions through the CFO, the one person who has to defend the number.
CloudZero’s own research corroborates the pattern. In a June 2026 survey of 260 senior finance leaders, more than half of them CFOs, 87% said they need the ability to tie AI spend to business results within the next year, but only 22% have it today. Of the teams that can’t measure AI outcomes, 75% have already held back on AI investment and 35% have killed an initiative outright.
This doesn’t represent a failure of finance. The data doesn’t arrive in a form you can plan against. Monthly bills show totals by vendor and service. Your plan needs spend by customer, product, team, and P&L category. The bill can’t connect those dots, so in the end, the number that lands in your plan becomes a cushion you’ll true up later. Probably more than once.
Three questions worth answering before the plan locks
Is AI showing up as a risk in your plan or an opportunity? Both are legitimate, but you can only make the opportunity case if you can show what last year’s spend produced.
How are you weighing a dollar of AI against a dollar of headcount or a dollar of software? That’s a tradeoff question and tradeoffs need comparable returns. Right now, AI is usually the only one of those three you can’t price per unit of output.
Are you capitalizing any AI-generated development work or is all of it hitting the P&L as Opex? For most teams it’s all Opex, usually because nobody has the allocation detail to support anything else. There’s real P&L relief going unrealized.
Report
Finance needs to prove AI’s return: CloudZero report
260 senior finance leaders (more than half CFOs) told us why the speed of seeing AI spend, not the size of it, separates who pulls ahead on AI from who gets burned.
What AI ROI actually looks like for finance
Never mind the abstractions. Everything real either grows revenue, cuts cost, or gives time back. For a finance team, that gets specific real fast.
- A faster, more accurate close
- Anomalies caught in hours instead of at month end
- Defensible capitalization instead of blanket Opex
- Product-side unit economics, so you can see AI’s effect on gross margin and evolve pricing accordingly
- Dev velocity and rep productivity you can trend over time
- A plannable AI line instead of a hedge
Every one of those needs the same input: spend allocated to the things you’re accountable for. Not tokens. Not models. Customers, products, features, teams, transactions.
This is the window
Plenty of finance leaders don’t know a system for this exists yet. It does.
CloudZero turns AI spend into a number you can plan, report, and defend. We take AI and cloud spend as the work happens, allocate it several levels deep, and connect it to the outcomes you report on, like cost per customer, per feature, or per transaction. It describes what the AI spend bought, in your language.
We’ve been solving complex allocation for cloud customers since 2016 and process 14 trillion billing events a year. Although AI is a newer surface area, it’s the same problem.
You’re setting FY27 numbers over the next few weeks. So this all matters right now, because a plan built on real allocation data means you can still defend it in March when someone asks what changed.
Let’s talk before the number gets locked. Reach out and we’ll walk through what your AI line could look like with the detail behind it.
Want to see how your AI spend experience sizes up against others in your cohort? Try our AI benchmark tool.
