Choose Tools Your Team Can Use, and Afford

T16-L02 · Choose tools · Level 2 Power user · 15-minute read, plus 60 minutes of doing

The $25 tool that cost $725

A research group of five signs up for a team plan at $25 per person a month. That's $125, and the PI approves it without a second look. In March a PhD student uses the same plan to screen 2,000 full-text papers for a systematic review, and runs the screening three times as the criteria change. The included usage runs out on day two. Someone had switched on extra usage with automatic top-ups, so the work carries on at pay-per-use rates, charged per token, a small piece of text. The March invoice is about $725.

In a company it's a customer service team of four at a lab-supplies distributor. A colleague found a tool "for $20 a month". That turned out to be per person, billed annually, with extra usage billed on top afterwards. The week of a product recall tripled the email volume, and the bill with it.

Nobody did anything wrong. Most AI tools now charge a monthly plan plus usage beyond an included allowance, and the headline price describes a quiet month. This book shows you how to choose a tool for your team that people can use and the budget can carry, including the busy month. You are at Level 2 Power user: your team sees the result. A wrong choice means colleagues who can't open each other's work, a figure nobody can check, or an invoice your group leader has to explain.

After this you can

• Read a plan's allowance and say what happens when a busy month uses it up.
• Estimate the monthly cost of one team task from the vendor's published prices, before anyone signs up.
• Choose between paying per seat and paying per use for your team's workload.
• Set a spending cap and an alert, and name the admin who watches them.
• Run a short team trial that tests handover, export and access, not only the output.

Before you start

• Books: T01-L01 for the four-quadrant method. T16-L01: picking a tool for one task by trying it. This book does the same for a team, with cost at the centre.
• One shared task your team does every month, with a rough count: papers, emails, reports.
• The vendors' pricing pages for two candidates, and the plan your team uses today, if any.
• Two or three colleagues willing to try it for a week.
• About 75 minutes: 15 to read, about 60 to do.

Last verified 23 September 2026. ChatGPT Business and Claude Team both cost $25 per person a month, or $20 billed yearly. On Claude Team, usage beyond the allowance is billed on top once an admin switches it on. Details for experts at the end of this book.

The idea in one page

Three ways AI tools bill. Know which one you're buying before you compare numbers.

Read the allowance. Five questions, answered from the vendor's own pages: What's the unit (messages, tokens, credits, runs)? Per whom (each seat, or pooled for the team)? When does it reset (monthly, weekly, every few hours)? What happens at the end (blocked, slowed, or billed extra)? Who can switch on extra usage, and is it on by default? If a page won't tell you the size of the allowance in numbers, plan for it to run out in your busiest week.

Price one task, then the month. For a pay-per-use job, the arithmetic is short:

items × tokens per item × price per token = cost of one run
cost of one run × runs per month          = monthly usage
seats × seat price + monthly usage        = monthly cost (+ tax)

Don't trust your guess at tokens per item. Run five real items and read the numbers off the usage page. Then work out two months: a normal month, and a busy month at about three times the volume, with one rerun.

Cap it, then watch it. A cap stops the spending, and it also stops the work. So set the cap at the busy-month figure, and an alert (or a weekly look at the usage page, if there's no alert) at the normal one. Switch off automatic top-ups until you've seen two real months. One named admin, with a deputy, is responsible for the cap. They can raise it in five minutes when a deadline needs it.

Count the costs that aren't on the invoice. Admin time: adding and removing people, checking the usage page monthly. Training: an hour per colleague is realistic. Lock-in: can you get the team's work out in a format that opens without the tool? And a cheap API job needs someone to build and maintain it. That person's hours often cost more than the tokens.

The team test. A tool that works for you can still fail your team: a colleague can't open the result, comments disappear in the export, or the person who has to check the output spends longer than the author saved. So the trial always includes one colleague picking up another's work, and one export opened outside the tool. The tool you use today, even a non-AI one, is a candidate and can win.

Worked example: two teams, four quadrants

The method comes from T01-L01. Here it is for a research group, then for a customer service team.

Lab: a research group that screens papers every quarter

Structure it. Petra, the group's lab manager, gets the March invoice and the job of fixing it. "Five people use AI every day for writing and reading. Once a quarter we screen about 200 new papers for our living review. A useful result: one tool everyone can use, with a monthly cost I know in advance and a hard maximum the PI has agreed."

Understand it. She reads the team plan's allowance with the five questions. The unit is usage per seat, and it resets on a schedule. At the end, usage credits take over if they're switched on: extra usage, billed at the pay-per-use API price. They were on, with automatic reload, which buys more credits by itself, and no limit. Then she prices the quarterly job. A ten-page paper is about 10,000 words, around 13,000 tokens, and more like 17,000 on a recent model. With the instructions, call it 20,000 tokens in and 1,000 out per paper. She runs five papers and reads the usage page: close enough. At the prices of Sonnet 5, Claude's mid-sized model, 200 papers cost about $10 per run. Through the Batch API, the cheaper route for jobs that can wait, it's $5.

That changes her problem. The screening was never expensive. March cost about $600 extra because 2,000 papers went through a large model three times, at $4 per million tokens in and $20 out, with nothing to stop it. Back to Structure it: "Seats for daily use, plus a small capped budget for the screening. The cap matters more than the plan."

Choose tools. Two candidates, both with no training on the team's content by default: Claude Team, which they have, and ChatGPT Business at the same seat price. She knocks out nothing on price, since five seats cost $125 a month either way. The team already has its projects and instructions in the current tool, and switching would cost a week of setup. She keeps it, and changes the terms:

• Five Standard seats, billed monthly for three more months, then annually if usage holds. That saves $25 a month from then on.
• Usage credits on, automatic reload off, an organisation limit of $50 a month and $25 per person.
• The screening runs on Sonnet 5, not the largest model, with a test on five papers before every full run.
• Admin: Petra. Deputy: the PI.

Build it. Before she writes the decision, she checks the team side with two volunteers. One screens twenty papers into a table in a shared project. The other opens it, adds a column and exports it to Excel. The export keeps the table and loses the comments, so the group agrees that decisions go into the table, not into comments. A colleague who works with screen magnification checks that she can use the project view at 200% zoom. She can.

Her decision note: normal month $125; busy month (screening, one rerun) $125 + about $20; hard maximum $175; alert when usage credits pass $25; review at the end of December.

What it taught her: the plan was fine. The missing cap and the choice of model were the problem, and neither needed a new tool.

Company: 500 customer replies a month

Structure it. Jonas leads a customer service team of four at a lab-supplies distributor. "We answer about 500 emails a month about orders, delivery dates and product specifications. A useful result: a first draft in our tone, from the order record and our product sheets, that a colleague checks and sends. Budget: under €150 a month."

Understand it. He prices both routes. Four ChatGPT Business seats cost $100 a month billed monthly. The pay-per-use route would be an automation that sends each email and its order record to Claude Haiku 4.5 through the API. Anthropic's own example puts 10,000 conversations at about $37, so 500 replies come to about $2 a month. A recall month at three times the volume is about $6.

Then he looks at who would build it. The automation needs someone to connect the mailbox, the order system and the API, and to fix it when a field changes. Nobody on the team has done that, and the IT contractor quotes two days plus an hour a month. Back to Structure it: "The tokens are nearly free either way. What we're really choosing is whether the team drafts in a chat window, or someone builds and maintains a pipeline, an automation that runs by itself."

Choose tools. For now, seats. Four ChatGPT Business seats, billed monthly, because everyone can start tomorrow and the price is flat: there's no usage bill to surprise anyone. The customer data in the emails stays out of training by default on the Business plan. The API pipeline goes into the decision note as the next step, for when volume doubles (T05-L02). It will need its own spend limit in the Console, Anthropic's account page for the API, and a named person who maintains it. Admin: Jonas. Deputy: the office manager.

Build it. Two colleagues try it for a week on twenty real emails each, against the Outlook templates they use today. Drafts are faster for product questions and no better for delivery dates, where the date still comes from the order system. One test matters more than the rest: a colleague picks up a half-finished draft from another's shared project and sends it. It works. The team's tone and reply rules live in a plain text file on the shared drive, pasted into the project, so they aren't locked in.

His decision note: normal month $100; busy month $100, because seats are flat; cap: four seats, removed within a week when someone leaves; checked monthly on the admin page; review in three months or at 1,000 emails a month.

In both cases the headline price wasn't the decision. The busy month, the cap and the person who watches it were.

What goes wrong

Reading the headline price. Symptom: "$20 a month" becomes $180 on the first real invoice. Fix: read the allowance with the five questions, and price the busy month before you sign up.

Top-ups with no ceiling. Symptom: extra usage with automatic reload quietly carries a runaway job through the night. Fix: turn off automatic reload, set an organisation limit and a per-person limit, and test a new job on five items first.

A cap that stops the deadline. Symptom: the limit hits in the week of a grant deadline, and nobody knows who can raise it. Fix: alert at the normal-month figure, cap at the busy-month one, and name an admin and a deputy who can change it in minutes.

Seats nobody uses. Symptom: eight seats, three people using them. Fix: bill monthly until you know real usage, look at the admin page once a month, and remove the seats of people who have left.

Annual billing before the trial ends. Symptom: you save 20% and are stuck for a year with a tool the team dropped in week three. Fix: monthly first, annual only after two or three real months.

Counting only the invoice. Symptom: the cheap API route needs a contractor every time something changes. Fix: write the setup and upkeep hours into the decision note next to the dollars.

A tool one colleague can't use. Symptom: most of the team likes it, but the one person who checks every result can't use it with their normal keyboard or zoom settings. Fix: test with each person's normal setup. One unmet must-have outweighs several happy votes.

Do it yourself (60 minutes)

1. Structure it (10 min). Write the shared task, the monthly volume and who does what. Add a budget and a busy month: what happens at three times the volume?
2. Understand it (15 min). Open the pricing pages of your current tool and one challenger. Answer the five allowance questions for each, from the vendor's own pages. Run five real items and read the usage.
3. Choose tools (10 min). Work out a normal and a busy month for each candidate: seats, usage, tax. Add the hours for admin, training and building. Knock out anything whose data terms don't fit your material. Pick one, with billing period, cap, alert, admin and deputy.
4. Build it (25 min). Set the cap and the alert, and switch off automatic top-ups. Run the team test: one colleague picks up another's work, and one export opens outside the tool. Write the one-page decision.

Exit check

Delivered artifact: a one-page tool decision for your team with:

• the workload: the task, the monthly volume and the busy-month volume;
• the monthly cost estimate for a normal and a busy month, with the vendor's prices, the date you read them, and your tokens or units per item from a real test;
• the cap and alert, as actually set, and whether automatic top-ups are off;
• the admin and deputy, by name;
• the team test: who picked up whose work, which export you opened, and what didn't survive;
• the non-money costs in hours, and the date you'll review the decision.

It passes when a colleague can recompute your estimate from the page and the vendor's price page, and the cap on the page matches the one in the tool.

Rule to remember

Price the busy month, set the cap, and name who watches it.

Details for experts

Checked on 23 September 2026. You don't need this to follow the book; it's for setting things up or answering a colleague.

Further reading and tools

Next books

• T16-L01 · Pick the right tool for one task by trying it: the fair trial this book builds on.
• T16-L03 · Test a Tool on Your Own Work Before Your Team Depends on It: a bigger trial with a fixed test set.
• T16-L04 · Replace a tool without losing your work: when the review date says switch.
• T05-L02 · Put AI in the Middle of a Workflow, and Check Every Answer: the pay-per-use route, built.
• T02-L03 · Build a Shared Assistant Your Team Can Test and Take Over: shared projects and instructions once you've chosen.

Tools

• Claude: Taught. The team plan with usage credits and spend limits in the lab example.
• ChatGPT: Taught. The Business plan with flat seats in the company example.
• Claude API: Taught. Pay per use, with a spend limit in the Console.
• n8n: Catalogued. One way to build the pay-per-use pipeline later.
• Cursor: Catalogued. Another seat-plus-usage example, for teams that write code.