What is ChatGPT? Explanation, examples & what companies must consider (2026)

What is ChatGPT? ChatGPT is an AI chatbot from the company OpenAI. You enter a question or task in natural language — the prompt — and ChatGPT generates a matching answer in text form. Technically it is built on a large language model (GPT) that has learned from vast amounts of text which word most probably comes next. This article explains ChatGPT clearly, shows concrete practical examples with a real prompt — and describes what changes as soon as a company puts it to use: data protection, GDPR and governance.

What is ChatGPT? — the short answer

ChatGPT is an AI chatbot from OpenAI, built on a large language model (GPT). It takes an input in natural language and generates a coherent, human-like text answer — in dialogue, follow-up questions included. "ChatGPT" stands for chat (the conversational format) and GPT (generative pre-trained transformer, the underlying model type).

Definition: ChatGPT is a dialogue-based AI system that generates a matching text output from a text input (prompt) using a large language model. It does not retrieve facts from a database but calculates the linguistically most probable continuation — which is why it is linguistically strong but not automatically factually correct.

Worth placing in context: ChatGPT is one product in a larger field. There are other language models and applications, and for companies what matters above all are platforms that make several models securely accessible.

How does ChatGPT work? — in plain terms

Behind ChatGPT sits a large language model. You can picture it as an extremely capable autocomplete:

1. Training. The model was trained on very large volumes of text and learned statistical patterns of language — which words typically follow which, in which context.
2. Prompt. You enter a task. The model processes your text together with the conversation so far.
3. Word-by-word prediction. It calculates the most probable next word, appends it, calculates the next — and assembles an answer sentence by sentence.

Two things follow, and they shape all practical handling of ChatGPT:

• It is linguistically strong and creative, because it produces fluent, context-appropriate language.
• It does not "know" anything in the real sense. It can invent facts, sources or figures that sound plausible but are wrong. This is called hallucination — and it is not a bug but a property of how the thing works.

Remember: ChatGPT predicts what sounds plausible — not what is true. Which makes it an excellent drafting tool and a poor sole source of fact.

What can ChatGPT do? — practical examples by function

ChatGPT suits anywhere language is involved: writing, rewriting, summarising, structuring, explaining, translating.

• Writing & phrasing. Drafting emails, shortening or expanding text, phrasing a polite rejection, turning bullet points into prose, varying subject lines or headlines.
• Summarising & analysing. Boiling a long document or meeting transcript down to its key points, setting out pros and cons, sorting a body of text by topic, formulating a first assessment.
• Translating & adapting. Rendering text in another language, changing register (formal/casual), translating specialist text into plain language.
• Customer service & communication. Turning a customer enquiry into a consistent draft reply in the desired tone, which an employee reviews and approves.
• Programming. Explaining code, finding errors, writing example snippets, commenting a function or porting it to another language.
• Ideas & structure. Brainstorming, outlines for presentations, question sets, checklists.

The same pattern holds in every case: ChatGPT delivers a draft in seconds, and the professional review stays with the person.

A concrete example: prompt and result

A good prompt says clearly what should come out, in what form, and under which constraints. An example from everyday office work — an unstructured note is to become a clean customer email:

Prompt:

"Write a friendly, professional reply email to a customer from these bullet points. Tone: binding but not stiff. Maximum 120 words. Please name a clear next step at the end. Bullets: delivery date shifts by one week due to a material shortage; we are offering a 5 % discount as compensation; new date 18 July; questions welcome at any time."

Expected result (abridged):

Subject: Your order — updated delivery date

Dear Ms Berger,

Thank you for your patience. Due to a short-notice material shortage, your delivery date shifts by one week to 18 July. We regret this and would like to offer you a 5 % discount on this order by way of compensation.

We are happy to answer any questions at any time. Next step: please confirm the new date briefly and we will reserve the goods for you.

Kind regards

The result is a usable draft in seconds — tone, length and the requested next step are right. Before sending, a person checks the facts (is the date correct, has the discount been approved?). That is exactly how ChatGPT should be used: as an assistant that does the preparatory work, not as an authority that decides on its own.

Is ChatGPT free?

Yes — there is a free version with which you can try ChatGPT and handle many everyday tasks. Alongside it, OpenAI offers paid tiers with more features and capacity. The exact tiers, limits and prices change regularly and should be checked with the provider directly.

For business use the price is usually secondary. What is decisive is where and how the data entered is processed — and whether inputs are used to train the models. This is exactly where the question shifts from "what does ChatGPT cost?" to "under what conditions may we use it at all?".

From a private tool to enterprise use — what changes

Privately, ChatGPT is simply a handy tool. But as soon as a company uses it and employees enter customer data, contracts or internal knowledge, the tool becomes a data-protection and governance question. Three things change fundamentally:

• Data leaves the building. Whatever is typed into the chat window is processed at the provider. Without a clear agreement, it is unclear where that happens and what becomes of the inputs.
• The GDPR applies. Where personal data is processed, you need a legal basis, as a rule a data processing agreement (DPA) with the provider, and transparency about whether inputs are used for training.
• Shadow AI emerges. When employees use private accounts for work on their own initiative, company knowledge spreads uncontrolled across external accounts — with no administration, no logs, no dependable assurances.

For serious enterprise use, these points should therefore be contractually assured and independently evidenced:

• Operation and data processing in the EU.
• A data processing agreement (DPA) as standard.
• No training on company inputs.
• Central role and permission management with logs (who accesses what?).
• Independent evidence such as an ISO 27001 certification and regular penetration tests.

The standard private login generally meets none of these — that is what enterprise platforms are for. How a company account differs from private accounts and how to set one up is covered in ChatGPT business account: what it is and how to set one up; selecting and introducing a platform is described in AI for companies.

Where meinGPT sits

meinGPT is a European enterprise platform that closes exactly this gap: it bundles several leading language models behind one GDPR-compliant interface — with EU operation, central permission management, connections to internal systems and your own assistants for recurring tasks. The operator is SelectCode GmbH, which is ISO 27001 certified and last had its security examined by an independent penetration test (SySS) in 2025; policies and evidence are available through the Trust Center. The difference from ChatGPT fits in one sentence:

ChatGPT is a single model access point; meinGPT is a platform that makes several models securely, manageably and GDPR-compliantly usable for a whole company.

To try it, meinGPT starts in self-service at €29 per user per month including usage credit — AI usage runs on shared credit rather than a flat rate.

Limits and risks — what ChatGPT cannot do

• Hallucinations. ChatGPT can invent facts, sources and figures that look convincing. Verify anything important independently.
• No guaranteed current knowledge. The model's knowledge has a training cut-off; without connected, audited sources, current or company-specific answers are unreliable.
• Bias. Training data contains distortions that can show up in answers — particularly delicate in decisions about people.
• Data protection. Inputs into a private account sit outside company control. Sensitive data needs an audited platform with a DPA and EU operation.
• No professional responsibility. ChatGPT makes no decisions and carries no liability. Checking and approving results always stays with the person.

Anyone wanting to go deeper on these limits will find more in managing AI risks: hallucinations & bias under control.

Conclusion

ChatGPT is an AI chatbot from OpenAI that generates a text answer from a natural-language input using a large language model. It is a strong drafting and assistance tool — for text, summaries, analysis, support and code — but not a verified source of fact: it calculates what sounds plausible, not what is true. Privately, simple access is enough; as soon as a company uses ChatGPT with real data, it becomes a data-protection and governance question — EU operation, a DPA, no training on inputs, roles and permissions. For safe, company-wide use, the route therefore leads from single model access to an audited platform.