ChatGPT, Claude, Gemini or Copilot: which AI tool should your company choose

For a company that lives in Microsoft 365, Microsoft Copilot is the most natural choice; for Google Workspace, Gemini. ChatGPT and Claude are more general and often strong with text and code. What matters most is not the brand but a business plan that does not train on your data and clear rules on what may go into AI.

The short answer

All four tools now handle everyday office work: summarising a document, drafting an email, translating text or helping with a spreadsheet, and all of them work in Czech and English. The differences are mainly which systems they plug into, how they treat company data and what they cost for a whole team. Model quality also changes with every release, so the best test is always one on your own tasks.

If you are deciding now, start with where your company works. Email and documents in Microsoft 365 point to Copilot; Gmail and Google Drive point to Gemini. If you are tied to neither, compare ChatGPT and Claude on a few typical tasks of your team.

The comparison in one table

	ChatGPT	Claude	Gemini	Microsoft Copilot
Made by	OpenAI	Anthropic	Google	Microsoft
Best fit when	you want one general tool for the whole team	you work a lot with long texts, contracts and code	the company lives in Google Workspace	the company lives in Microsoft 365 and Teams
Company data	uploaded files and connected apps	uploaded files and connected apps	Gmail, Drive, Docs	email, documents and chats the user can access
Business plan	Business, Enterprise	Team, Enterprise	Gemini in Workspace	Microsoft 365 Copilot
Czech and English	yes	yes	yes	yes

Prices change often, so we do not quote them here. See the vendors directly: Claude pricing, Google Workspace pricing with Gemini and Microsoft 365 Copilot for business.

Data protection: what really matters

The most common question is whether AI will use company data for training. For the business plans of all four vendors, the answer by default is no:

• OpenAI says on its business data page that inputs and outputs from ChatGPT Business, Enterprise and the API are not used for training by default.
• Anthropic states in its commercial terms that it does not train models on customer content from its commercial services.
• Google says in its Workspace privacy hub that prompt content is not used to train models outside your domain without your permission.
• Microsoft states in its Copilot documentation that prompts, responses and Microsoft Graph data are not used to train foundation models, and that EU users are covered by the EU Data Boundary. The same page notes that Anthropic models offered inside Copilot are currently excluded from the EU Data Boundary.

Watch out for private accounts, though. When an employee pastes a contract into a free version on a personal account, none of these business guarantees apply. So the first step is always a business plan and short rules on what may go into AI and what may not. How we set up such rules and train the team is described in ChatGPT, Copilot and Claude for business, and EU obligations are summarised in the AI Act for companies.

When to choose which tool

Microsoft Copilot makes sense when your email is in Outlook, documents on SharePoint and meetings in Teams. Copilot works with whatever the user has access to, so folder permissions must be in order, or it may show an employee a document meant only for management.

Gemini is the natural choice for companies on Google Workspace. It works directly in Gmail, Docs and Sheets, so people do not have to switch to another app.

ChatGPT is the most widely used, and most people already know it. It works well as a general assistant for the whole team, from sales to marketing, and connects to many other apps.

Claude is often chosen for long documents, contracts, analyses and code, which makes it popular with lawyers, analysts and developers.

In practice many companies combine them: Copilot or Gemini for everyday office work, and ChatGPT or Claude for heavier tasks. It is fine to start with one tool and add another later.

An example from a Czech company

Picture a distributor with 40 employees on Microsoft 365. Sales write quotes every day, the accountant checks invoices and management wants a monthly overview. Copilot for the whole company helps write email and summarise meetings. But a chat does not check invoices on its own: that needs AI invoice processing connected to the accounting system. And answering customers from the company price list and terms is a job for a company AI knowledge base that answers only from your documents.

When chat is not enough and you need an AI agent

A chat gives advice but does not do the work. Every time, someone has to open the window, paste the inputs, check the result and copy it into a system. For tasks that repeat dozens of times a day, it pays to go one step further:

• emails and customer questions that are always handled the same way,
• invoices, orders and other documents that are retyped into a system,
• reports that someone assembles from several spreadsheets every week.

This is where a custom AI agent comes in. It uses the same models as ChatGPT, Claude or Gemini, but it is connected to your systems, finishes the work itself and sends steps with consequences for approval. The difference between a chat and an agent is explained in Agentic AI: what it is. Prices are on our pricing page.

Five questions to ask before you choose

1. Where are our documents and email? Microsoft 365, Google Workspace or something else? This often decides it.
2. Who will use AI, and for what? Sales for email, accounting for documents, developers for code. Each group needs something different.
3. What data will people put into AI? Personal data, contracts or health data need stricter settings and sometimes hosting in the EU.
4. Who will manage the tool? Someone has to set up accounts, permissions and rules and make sure they are followed.
5. How will we know it paid off? Decide upfront which time or cost you want to save, and measure it after a month.

The most common mistakes

We see the same mistakes again and again. The first is buying licences for everyone without training: people try AI twice, get a poor result and stop. The second is having no data rule, so staff keep using private accounts because they are faster. The third is expecting a chat to automate a process on its own. A chat saves individuals minutes, but the process only speeds up when a system connected to your data takes over the work. The fourth is messy permissions: an AI tool connected to the company drive will find files only a few people were meant to see. Before connecting AI to your documents, review who has access to what.

How to start in two weeks

1. Find out which AI tools people already use, including on private accounts.
2. Choose one business plan that fits your ecosystem and stop private use with company data.
3. Write one page of rules: what may go into AI, what may not, and when output is checked.
4. Run short AI training on the team's real tasks.
5. After a month, review where time is saved and where an agent would help.

Prahapp is the Prague AI division of Buinsoft Technology. We do not resell any vendor's licences, so we recommend based on your systems, not on commission. If you are not sure where to start, a free AI consultation helps.

And if you want AI to do the work itself: within 3 working days we build a free, working AI agent prototype on your data. Tell us which process costs you the most time.