Pull up your AI spend for last quarter. In Irvine or Riverside, it doesn’t matter — you can probably find it in about thirty seconds. A line item. A per-seat number. A total you feel reasonably good about.
Now find the rest of it.
The subscriptions on personal cards, coming back through expense reports labeled software, or professional development, or nothing at all. The department that signed up for its own tool because waiting for IT wasn’t an option. The four people paying twenty dollars a month each for four different models that all do roughly the same thing — and that your company owns none of.
That’s the second bill. It doesn’t arrive. Nobody approves it. And it is not the expensive part.
The Expensive Part Is What Doesn’t Compound
Here’s what should bother a finance leader more than the duplicate subscriptions.
In PwC’s 2026 Global CEO Survey, 56% of chief executives said AI had produced no significant financial benefit for their business. Only 12% could point to both a cost improvement and a revenue improvement. These aren’t companies that failed to adopt AI. These are companies that adopted, spent, and still can’t find the money.
Four people using four different AI tools aren’t four times as productive. They’re four silos. Someone in operations figures out how to cut a recurring three-hour task down to forty minutes — and that knowledge stays in their head, in their tool, on their personal account. Someone in finance solves the almost identical problem six weeks later, from zero, in a different product entirely. Nothing accumulates. Nothing transfers. Nothing gets better across the company because it got better for one person.
You are paying for individual productivity and getting exactly that: individual, unrepeatable, unmeasurable productivity that walks out the door if that person leaves — a real risk for lean SMB teams across Orange County and the Inland Empire, where a single ops or finance lead often carries knowledge no one else has documented.
And that’s before the parts that never even show up as spend. Company data sitting in tools you don’t control. No volume leverage on pricing, because you’re buying in ones instead of in blocks. Per-seat rates a fraction of what you’d negotiate as an organization. And no line of sight — none — from any of it back to a recovered hour or a recovered dollar.
This is what makes AI sprawl uniquely bad as a category of spend. Most uncontrolled spend is merely wasteful. This kind is wasteful and it compounds against you, because the longer it runs, the more the value gets locked into places you can’t reach.
The Five Numbers You Can’t Produce
Try this. Right now, without asking anyone, answer these five:
- How many AI models are running in your business? Not licensed. Running. Including the ones on personal accounts.
- What percentage of your workforce is using AI? Weekly, not ever.
- What percentage of that usage is governed — a sanctioned tool, under your control, with a policy behind it?
- What percentage is charged back to a department, a cost center, a budget owner?
- What percentage is tied to a stated business outcome rather than an individual’s personal preference?
If you’re like most SMBs in Irvine or Riverside, you can’t answer any of the five with confidence. Some leaders can’t answer the first one within a factor of two.
Sit with that. A category of spend and risk is running inside your business right now — touching client data, absorbing budget, shaping how work actually gets done — and there is no number attached to any of it. You would not accept that in any other line of the business. Payroll, insurance, facilities: you’d have caught this in a review a long time ago.
The reason nobody’s caught it here is that nobody owns it. It didn’t come in through procurement. It came in through people trying to do their jobs.
You Can’t Fix What You Can’t See
Notice that none of this argues for spending more. It argues for seeing what’s already being spent.
That’s the good news buried in here, and it’s the reason this is worth an hour of your time rather than a project plan. Most companies that finally look at their five numbers discover two things at once: they’re spending more than they thought, and they’re capturing less of it than they thought. Which means the first move isn’t a purchase — it’s consolidation. One sanctioned path. Volume pricing. Gains that stack instead of resetting to zero every time someone new figures out the same trick. A policy that gives people permission to use the thing the company has actually paid for, instead of quietly working around it.
Companies routinely find they were already paying for AI capability inside licenses they already hold — like a Microsoft 365 environment with Copilot rights sitting unused — while separately reimbursing staff for personal subscriptions to do the same work. That’s not a technology problem. That’s a visibility problem, and visibility is cheap.
The hours are there — most SMBs are sitting on four to eight hours per knowledge worker, per week, in repetitive admin and information search. The spend is there too. Right now, neither one is on a report you’ve seen.
Come Find Your Five Numbers
We’re running a working session on exactly this: what shadow AI is really costing SMBs, how to find the five numbers inside your own business, and what to do with them once you have them.
Not a product demo. Not a keynote about transformation. A method for producing the numbers, and a walkthrough of what most companies find when they run it — for finance and operations leaders across Orange County and Riverside County, where lean teams can least afford duplicate, ungoverned spend.
Webinar: The Shadow AI Audit — What’s Really Running in Your Business
45 minutes. You’ll leave with the five-number framework, the questions to ask, and a clear read on the cost and exposure sitting inside your company right now.
Built for finance and operations leaders at companies between 25 and 200 people.
Can’t make it live? Register anyway and we’ll send you the recording and the audit worksheet.
