Is ChatGPT Team right for a small office?

Since OpenAI launched ChatGPT Team on January 10, small businesses have had a middle option between individual ChatGPT Plus accounts and the larger ChatGPT Enterprise plan. Enterprise, introduced last August, was built for big organizations. Team is self-serve: you upgrade from inside ChatGPT's settings.

The deciding questions for a small office are practical. How many people will use it, how often, for what kind of information, and who will look after it? This guide sets out what the plan includes and then walks through a decision with real prices.

What you get

According to OpenAI's announcement, ChatGPT Team includes:

• GPT-4 with a 32K context window. The context window is how much text the model can consider at once, measured in tokens (pieces of words). 32K tokens is room for a long report plus your questions.
• The main tools: DALL·E 3 for images, GPT-4 with Vision for reading pictures, browsing, and Advanced Data Analysis for working with spreadsheets and files, with higher message limits than Plus.
• A shared workspace for the team, with an admin console to add and remove people and manage the workspace.
• Shared custom GPTs. Members can build GPTs and publish them only to the workspace, where they appear in a private section of the GPT Store.
• No training on business data. OpenAI says it does not train its models on Team data or conversations.

TechCrunch reports that the plan is aimed at teams of up to 149 people.

What it costs

OpenAI's published price is $25 per user per month when billed annually, or $30 per user per month when billed monthly. For comparison, an individual ChatGPT Plus subscription is $20 a month.

A worked decision checklist

Take a fictional six-person accounting office. Three staff use ChatGPT daily for drafting client emails and summarizing documents; three use it a few times a month. Work through the questions in order.

Now the arithmetic, using OpenAI's prices:

The Plus-only option is cheaper, but each person then has a separate account, nothing is shared or managed centrally, and the business has no workspace-level promise about its data. For this office, which handles client information every day, the data commitment and shared setup probably justify the extra cost. A two-person office using ChatGPT twice a week might reasonably decide the other way.

Practical tips if you sign up

Agree on a short written policy first: what may be pasted (internal drafts, public documents) and what may not (for example, health details or anything a client asked you to keep out of third-party tools). Appoint one administrator. Build one or two shared GPTs for the tasks people repeat most, and review them after a month. And keep the human check: GPT-4 can still produce confident mistakes, so anything that goes to a client needs a person's review.

How is workspace data handled?

OpenAI's core statement is that, as with Enterprise, the business owns and controls its data in Team. It says it does not train on Team business data or conversations, and that its models do not learn from your usage.

Within the workspace, the admin console lets the account owner manage who is a member, so access ends when someone leaves. GPTs that members publish to the workspace stay inside it, in a private part of the store rather than the public listing.

For deeper detail, OpenAI points customers to its privacy page and Trust Portal, which a cautious office should read before signing up. Enterprise customers were promised specific measures such as SOC 2 compliance, a security audit standard, and encryption of data both stored and in transit; the Team announcement does not list those details itself, so check what applies to Team rather than assuming. If your work is covered by professional or legal confidentiality rules, compare those rules with OpenAI's terms, and ask your professional body or adviser where the line is.