The question “Claude or ChatGPT” in a company rarely comes up in an IT strategy session. It comes up when a manager learns that half the employees are already using one or the other with personal accounts, and are uploading customer contracts and financial reports to them. Then you have to choose quickly: which tool to make official, which plan to buy, and how to make sure data does not leave where it should not.
In marketing the two products look similar: both write, analyse and code, and both have business plans and an API. The differences emerge when you start asking specific questions: where is the data physically stored, is it used to train models, how does the tool connect to your systems, how does it handle a 200-page contract.
In this article we compare the two against the questions companies ask us. We do not claim that one is better. In our experience most companies end up using both, just for different tasks.
Business plans and API: two different purchases
The first thing to separate: employees using a chat interface and company systems integrating through an API are different products with different terms.
Claude (Anthropic) offers a Team plan for smaller groups and an Enterprise plan with centralised management, single sign-on (SSO) and audit capabilities. ChatGPT (OpenAI) has an analogous pair: the Business plan for teams and Enterprise for larger organisations. In both cases an administrator manages users, sees usage and can set which integrations are allowed.
The API is a separate path: your system sends requests to the model programmatically, without a chat interface. It is needed when you want AI to process documents from your system, answer customers on your website or automate a process. Claude models are available through the API directly from Anthropic and also through Amazon Bedrock and other cloud platforms; OpenAI models are available directly from OpenAI or through Microsoft Azure.
The practical conclusion: if the goal is employee productivity, look at Team or Business plans. If the goal is process automation, look at the API. Often you need both.
Data and training: what is actually promised
The main difference between a personal and a business account is not features but data use. On business plans both providers by default do not use your conversations and uploaded files to train models. On personal plans it depends on settings that an employee may not change.
This is the main reason why employees using personal accounts for work is a problem. Not because the tool is bad, but because the company does not control the terms. Moving to a business plan solves this problem immediately.
For the API, the commercial terms of both providers also state that data is not used for training. It is also worth checking the retention period: how long requests are kept for abuse monitoring, and whether you can ask for zero data retention for sensitive scenarios.
EU data residency
For companies in the EU, especially those subject to NIS2 or DORA requirements, it matters where data is physically processed and stored. Both providers have solutions here, but different ones.
Claude models can be used through Amazon Bedrock in an EU region, for example Frankfurt. In that case requests are processed in an EU data centre under AWS terms, and Anthropic itself does not store the data. This is a convenient option for companies that already use AWS, or whose backups, like ours, are kept in an Amazon data centre in Germany. Anthropic is also expanding EU options directly, but the Bedrock route is proven and works now.
OpenAI offers EU data residency to Enterprise and API customers, with data stored in an EU region. The alternative is OpenAI models through Microsoft Azure in EU regions, which is natural for companies that are already in the Microsoft environment.
In both cases it is worth asking the provider for documents: a data processing agreement (DPA), a list of subprocessors and a clear confirmation of where exactly processing takes place. These are questions we help formulate and assess in a risk assessment.
Document analysis: where the differences show
Both tools read PDF, Word, Excel and images. The differences show up in long and complex documents.
Claude has a large context window and in our experience follows instructions well when working with long contracts, technical specifications and audit reports: it less often “loses” details from the beginning of a document and cites more accurately. This is noticeable when you need to compare two 80-page versions of a contract or extract all the commitments from a supplier’s proposal.
ChatGPT is strong where you need more tools in one place: data analysis with code execution, charts from Excel, image generation, web search. For a finance department that wants to upload a table and ask “show me the trends by month”, this is a convenient way to work.
Neither replaces human review when it comes to contracts or numbers. Both sometimes err with confidence. The process must allow for that.
Integrations: MCP and Agents SDK
The value of a tool to a company depends heavily on how it connects to your systems: CRM, accounting, document management, helpdesk.
Anthropic created the open Model Context Protocol (MCP) standard, which lets AI connect to external systems through a unified interface. Its advantage is that one MCP server for your system works with the various tools that support the standard, and today it is supported not only by Claude but also by OpenAI products and Microsoft. The Claude Agent SDK lets you build agents that run in your environment and use the same MCP connections.
OpenAI offers the Agents SDK, a library for building agents with tools, handoffs between agents and guardrails, and it also supports MCP connections. ChatGPT Business and Enterprise have ready-made integrations with popular business tools, and in the Microsoft environment OpenAI models are available through Azure and Copilot Studio.
Our practical recommendation: build integrations through MCP, regardless of which model you choose first. That way, in a year you can change the model without building the integrations again. How we do this in practice is described on the Claude and ChatGPT solution pages.
When to use both
In our experience the most common end result is not “either/or”. A typical split in a mid-sized company:
- Everyday use by employees: one tool with a business plan, to make it simpler to administer and train. Usually the one that more people already used.
- Document analysis and contracts in the legal and procurement departments: Claude, for its accuracy on long documents.
- Data analysis and visualisation in the finance department: ChatGPT, for code execution and charts.
- Process automation through the API: whichever model gives better results for the specific task in testing, connected through MCP so it can be swapped.
- In a Microsoft 365 environment: Copilot as a third layer for e-mail and meetings, because it sees Microsoft data.
This is not inefficient. Models improve at different rates, and a company that has both can choose by task rather than by what it bought a year ago.
Where to start
The choice does not require long research. It needs a few weeks of structured testing.
- List 5 to 8 real tasks from different departments: contract review, drafting a proposal, data analysis, replying to a customer, explaining an internal procedure.
- Run the same tasks with both tools using trial accounts of the business plans. Have the results assessed by the people who do that work every day.
- In parallel, request the DPA and EU data residency confirmations from both providers. If NIS2 or DORA requirements apply to your company, this is a mandatory part.
- Decide which tool will be the main one for employees, and prohibit personal accounts for work data.
- Plan integrations separately, through MCP, and only for the tasks where the test showed a clear benefit.
If you want us to organise and assess the test, our AI solutions for business service covers task selection, testing both tools with your data, assessment of the providers’ documents and a recommendation that you can justify to management with results rather than advertising.
