Microsoft is spending the next month running webinars for business customers on controlling AI costs and proving that Copilot agents pay for themselves, and the invitation puts the problem in one sentence: “AI costs are easy to start and hard to forecast.” When the company selling the product says so, it is worth looking at your own AI line.
For most businesses it started as one subscription on one card. It is now more likely to be several: ChatGPT Plus for two or three people, a Claude plan for whoever does the modelling, Copilot switched on inside Microsoft 365, and, since last month’s agent launches, at least one thing billed by use rather than by seat. The amounts are small. The total is rarely on a budget line, and the return is rarely measured.
The surveys say this is normal. U.S. Bank polled 1,000 senior finance leaders in the United States and reported on 29 September that 51 per cent said spending on AI tools and platforms had exceeded budget over the past year, while 69 per cent said the investment had delivered benefits. A June survey of 260 finance executives by the cost-management firm CloudZero found that only 22 per cent could tie AI spend to business outcomes, and 60 per cent agreed with the statement that they were “spending more on AI than we can currently justify with measurable outcomes.” Both are vendor-run surveys, mostly of large US companies, so hold the exact figures loosely. The direction is not in doubt.
Per seat: ChatGPT Plus US$20, Claude Pro US$20, Microsoft 365 Copilot US$30 per user a
month on an annual commitment. Per use: tokens, or Copilot Credits at one US cent each, 25,000 for
US$200 a month prepaid. Included: a starting price, not always the final price. (Branded graphic by PGH Consulting, LLC)
AI is priced in three shapes, and the confusion comes from mixing them up.
The first is per seat. ChatGPT Plus is US$20 a month, Claude Pro is US$20, and Microsoft 365 Copilot is US$30 per user a month on an annual commitment, or US$21 on the small-business edition for companies under 300 users. A seat is predictable: you know the number in January. The risk is sprawl, not surprise.
The second is per use, and this is where the forecasting breaks. Under the hood every AI model charges by the token, roughly three-quarters of a word, counted on what you send and on what comes back. Business products wrap that in friendlier units. Microsoft bills agents built in Copilot Studio in Copilot Credits at one US cent each, pay as you go or as a prepaid pack of 25,000 credits for US$200 a month, and one complicated question can cost a dozen credits. On Claude, the newest model is a separate purchase of prepaid usage credits on the US$20 plan, as Week 15 covered. Usage pricing is not a trick. It is a bill that depends on behaviour, and behaviour is the thing a budget cannot see.
The third shape is “included”. Copilot agents, OpenAI’s Dots, Claude in Google Sheets: each arrived with the message that it comes with a plan you already pay for. Read the terms and “included” has edges. Microsoft’s licence covers an agent used by your own licensed staff, within fair-use limits; point the same agent at a customer-facing web page and it draws credits regardless of the licences your staff hold. The first Dot is included, but on the Pro tier or a Business Premium seat, not on Plus. Included is a starting price.
Long chats resend the full context. Agents make many model calls. Expensive models get used
for simple jobs. Nobody owns the line. And the surveys: 51 per cent over budget, 22 per cent can tie
spend to outcomes, 60 per cent spending more than they can justify. (Branded graphic by PGH Consulting, LLC)
Four things push the number up, and none of them is anyone deciding to spend more.
The first is that the model forgets. Microsoft’s own explanation, from an August post by its Foundry team, is that models are stateless, so “the full context is sent with every request.” A long conversation re-sends its whole history with every follow-up, so a question in the tenth turn costs several times what it cost in the first.
The second is agents. One instruction to an agent is not one model call. In Microsoft’s words, “A single user request can generate many model calls,” and each retry, lookup and step is metered. An agent that fails halfway and tries again has billed you twice for one outcome.
The third is using the most expensive model for everything. Microsoft’s line is blunt: “Most requests do not need a frontier model.” Summarising an email or cleaning a date column does not need the model that tops the reasoning benchmarks, and the two-hour bake-off from Week 15 will tell you which cheaper model scores the same on your work.
The fourth is that nobody owns the line. CloudZero’s survey found AI is driven outside finance in 74 per cent of companies but finance owns the bill in 60 per cent. Seats get added by whoever has the card, and the first person to see the total is whoever reconciles the statement.
Keeping it predictable
The fix is the same discipline you apply to telephone and fuel.
Put every AI subscription, seat and usage account on one register with an owner, a monthly cost and what it is for. The permissions register from Week 16 is the natural place; add a cost column.
Prefer a cap to an open meter. Where a vendor offers a prepaid pack and a pay-as-you-go option, the pack is the one with a ceiling. A pay-as-you-go agent facing the public has no ceiling unless you set one. Set the alert before you set the agent loose.
Route by job, not by habit: the frontier model for the work that needs it, the cheaper one for everything else.
Measure cost per finished job, not per message. A second Microsoft post, two weeks later, calls this “cost per completed outcome,” what the business actually paid across every turn and retry to get one usable result. A cheaper model that needs three attempts is not cheaper.
Line 1: monthly cost equals seat price plus usage. Line 2: value created equals hours saved
times hourly cost, plus work you would otherwise pay for. Measure one job, tally minutes saved, then
renew or remove. (Branded graphic by PGH Consulting, LLC)
Proving return on an AI tool needs two lines, written before you renew.
Line one is what it cost: the seat price plus any usage, per month, from the register. Line two is what it saved or earned: the hours it removed, multiplied by what those hours cost you, plus anything it produced that you would otherwise have paid for. Line two is the hard one, and the only way to fill it is to count. Keep the ten-cell scorecard from the bake-off, add a column for minutes saved, and tally it for a month. A US$30 Copilot seat is US$360 a year; if the tally shows it saving an hour a month for someone whose time is worth more than US$30 an hour, it pays. If the tally shows nothing, the seat goes, however good the demo was.
The sequence matters. Measure first on one job, then expand. Microsoft’s ROI session is pitched the same way: prove the return on the agents already in the licence before buying more. CloudZero found that three-quarters of the companies that cannot measure outcomes have held back investment, and 35 per cent have killed an initiative outright. Not measuring is the expensive option.
What this does not settle
The survey figures come from a bank and from vendors who sell cost-management software, and their samples are mostly large US companies. A business with eight staff will not see the same percentages; it will see the same pattern on a smaller bill.
Prices here are the published US figures. ChatGPT bills local subscribers in Jamaican dollars at a localised price, and Microsoft licensing runs through resellers, so the number on your statement will differ, and several of these prices changed last month.
Hours saved are self-reported unless you time them, and people are generous to tools they like. Have someone other than the enthusiast keep the tally.
And a tool that passes the two-line test on cost can still fail on accuracy. The survey in Week 19 found finance teams spending about a quarter of the week checking AI output. Checking time belongs on line one.
List every AI subscription, seat and usage account with an owner and cost. Set a spending alert
or cap on each usage-priced tool. Write the two lines for one tool. Run one routine job on a cheaper
model. Put the AI total on the management accounts as its own line. (Branded graphic by PGH Consulting, LLC)
1. List every AI subscription, seat and usage account the business pays for, with an owner and a monthly cost. Most owners are surprised by the total.
2. Open the billing page of each usage-priced tool and set a spending alert or cap. If the tool has no cap, note that on the register.
3. For one tool, write the two lines: monthly cost, and hours saved times the cost of those hours. If you cannot fill line two, start a tally this week.
4. Run one routine job on the cheaper model and compare the result. If it scores the same, change the default.
5. Put the AI total on next month’s management accounts as its own line. A number that appears every month gets managed.
Survey figures are as published by U.S. Bank (29 September 2026), CloudZero (24 June 2026) and Datarails (6 October 2026) and are vendor-commissioned; prices are the published United States figures as at 8 October 2026 and may change. An AI bill you cannot forecast is still a bill you can measure.
Peta-Gaye Hardy is the founder of PGH Consulting, LLC, where she helps finance and operations teams adopt AI in practical, low-risk ways. She writes the weekly AI in Finance & Business column and is based between Jamaica and the United States. Learn more at www.pghconsultinggroup.com. Follow on Instagram and YouTube @pghconsultinggroup, and connect on LinkedIn at linkedin.com/in/peta-gaye-hardy.
Disclosures: This article is informational and does not constitute investment, tax, legal, or accounting advice. Readers should consult a qualified professional before acting. Prices, plan inclusions and billing mechanics are as published by OpenAI, Anthropic and Microsoft at the time of writing and are subject to change; readers should confirm the current position on the vendor’s own pages before subscribing. Survey findings are reported as published by their sponsors and have not been independently verified. AI tools can produce errors, and every figure, clause, or claim they produce should be verified against a source before being shared or acted upon. The author has no commercial relationship with OpenAI, Anthropic, Microsoft, U.S. Bank, CloudZero, Datarails or any product mentioned and was not compensated by them. All product names, logos, and trademarks are the property of their respective owners and are referenced for editorial purposes. The examples described are illustrative and do not depict any real business.
