[{"data":1,"prerenderedAt":19},["ShallowReactive",2],{"post-en-chatgpt-im-unternehmen":3},{"slug":4,"title":5,"description":6,"date":7,"dateFmt":8,"minutes":9,"tags":10,"related":14,"image":15,"imageOg":16,"imageAlt":17,"html":18},"chatgpt-im-unternehmen","Using ChatGPT in your business: what it delivers, where the limits are","ChatGPT for business — what the public AI services deliver, where data protection and reliability hit their limits, and when the step to your own solution pays off.","2026-06-10","June 10, 2026",2,[11,12,13],"chatgpt","gdpr","strategy","ki-modelle","\u002Fblog\u002Fchatgpt-unternehmen-cover.webp","\u002Fblog\u002Fchatgpt-unternehmen-cover.jpg","A chat window surrounded by three limits: data protection, reliability and repeatability.","\u003Cp>ChatGPT has long been everyday reality for many teams — often unofficially, around the company rather than through it. That's understandable: the tool is impressive. But there's a big difference between "employees privately use ChatGPT" and "the company uses AI". Here's the honest classification.\u003C\u002Fp>\n\u003Ch2>What ChatGPT & co. are great at in a company\u003C\u002Fh2>\n\u003Cp>The public AI services are excellent for \u003Cstrong>work without sensitive data\u003C\u002Fstrong>: drafting and revising texts, structuring ideas, summarizing research, explaining code snippets, preparing translations. Teams that use them for this work measurably faster — that's not a fad, it's the new normal.\u003C\u002Fp>\n\u003Cp>The mistake isn't using them. The mistake is stopping there.\u003C\u002Fp>\n\u003Ch2>The three limits every company runs into\u003C\u002Fh2>\n\u003Cp>\u003Cstrong>1. Data protection.\u003C\u002Fstrong> The moment customer data, prices, contracts or internal documents wander into a public chat window, they leave your building. For GDPR-relevant data you need at least the business tiers with a data processing agreement — and even then the question remains whether that data should see a third-party data center at all. An internal policy ("what may go in, what may not") is the minimum; most companies don't have one.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>2. Reliability.\u003C\u002Fstrong> ChatGPT doesn't know your products, prices or processes — it guesses based on world knowledge. For a text draft, that's fine. For a customer reply, a quote or a delivery-time statement, guessing is a business risk.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>3. Repeatability.\u003C\u002Fstrong> A chat window is manual labor: every case needs a human who asks, checks and copies. The real lever of AI — routine workflows running \u003Cstrong>by themselves\u003C\u002Fstrong> — stays unused.\u003C\u002Fp>\n\u003Ch2>The step beyond the chat window\u003C\u002Fh2>\n\u003Cp>The companies that genuinely profit from AI go one step further — in one of two directions, often both:\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fblog\u002Fchatgpt-unternehmen-schritt.webp\" alt=\"From chat window to system: drafts and questions on the left — on the right, the company with its own knowledge, workflows and data sovereignty.\">\u003C\u002Fp>\n\u003Cp>\u003Cstrong>AI with your knowledge.\u003C\u002Fstrong> An assistant built on your products, documents and tone doesn't answer with world knowledge but with your knowledge — and can run where your data lives. For sensitive data this is often the only clean path; small specialized models (\u003Ca href=\"\u002Fen\u002Fblog\u002Fslm-statt-llm\">SLMs\u003C\u002Fa>) also make it economically attractive.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>AI inside your workflows.\u003C\u002Fstrong> Instead of a human copying every case into a chat window, the AI sits directly in the workflow: reads the request, pulls the data, creates the document, posts the case. That's the difference between "typing faster" and "not typing at all".\u003C\u002Fp>\n\u003Ch2>Starting pragmatically\u003C\u002Fh2>\n\u003Cp>Our advice is unspectacular: \u003Cstrong>use the public tools\u003C\u002Fstrong> for everything non-critical — with a clear, short policy. And \u003Cstrong>in parallel, identify the two or three workflows\u003C\u002Fstrong> where your own knowledge, data protection or volume demand more than a chat window. That's where the real edge is built.\u003C\u002Fp>\n\u003Cp>What the path to your own model looks like — from feasibility check to operation under your control — is shown at \u003Ca href=\"\u002Fen\u002Fki-modelle\">Custom AI models\u003C\u002Fa>. Or \u003Ca href=\"\u002Fen\u002Fkontakt\">tell us directly\u003C\u002Fa> where ChatGPT hits its limits for you today.\u003C\u002Fp>\n",1781540522046]