Guide

Connecting data protection and AI compliance with existing systems

Does everything need to be replaced for this? Usually not. What can be connected to an existing system landscape, where the limits are, and which part typically takes the longest.

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In short

For data protection and AI compliance, in most cases nothing existing needs to be replaced: inventory management, CRM, calendar, accounting, or phone systems are connected via interfaces. The key question is whether the respective system has a documented interface — and the time-critical part is almost never the technology, but obtaining access credentials.

01 — Integration

Connection with existing systems

The most common misconception is that everything must be new. In most cases, the existing system landscape remains in place, and data protection and AI compliance builds on top of it — through interfaces, not through replacement.

What gets connected in practice: ERP, CRM, calendar, accounting, phone system, newsletter system, website. What matters is whether the respective system has a documented interface. Where none exists, there's usually a workaround — but that costs effort and needs to be clarified up front, not discovered later.

The time-critical part is almost never the technical integration, but obtaining access credentials. Starting early here noticeably shortens the project timeline.

02 — Requirements

What you need for AI compliance

A clearly defined trigger. Not “we should do something with AI,” but a process that demonstrably costs time or orders today.
Existing content or data. Data protection and AI compliance works with what's already there. The more complete the starting point, the shorter the setup.
Access to the systems involved. Whoever manages the credentials needs to be involved from the start — this is, in our experience, the most common cause of delays.
One decision-making contact person. One, not three.
Willingness to refine after launch. The first weeks in real operation show what was missing in the concept. That's normal and accounted for.

03 — Bottlenecks

What typically causes delays

Content and deliveries. By far the most common cause of delay. Text, images, price lists, access credentials — what's missing blocks progress.
Decisions. When it's unclear who approves, the project waits. A named contact person with decision-making authority noticeably shortens the timeline.
Access to third-party systems. Getting access to inventory management, phone systems, or CRM regularly takes longer than the integration itself.
Endless review rounds. Two correction rounds are normal, five are a sign that the goal wasn't clear at the start.

04 — Questions

Frequently asked questions

Do we need a data protection impact assessment?

Not generally. It becomes necessary when the processing is likely to pose a high risk to data subjects — such as extensive profiling. For an FAQ chatbot on a website, it's usually not required. We review this case by case and document the result in writing.

Do AI-generated texts need to be labeled?

For content that is published and synthetically generated or substantially modified, yes. Purely internal use — research, drafts, summaries — typically does not trigger this obligation.

How often does the inventory need to be updated?

Whenever a new tool is introduced or the purpose of an existing one changes. An annual review as a minimum interval makes sense, even without a specific trigger.

May we enter customer data into ChatGPT?

In the free version without contractual safeguards: no. With a business account, data processing agreement, and training excluded, it may be permissible — depending on what data is involved. Precisely this distinction belongs in the usage policy, because it's constantly relevant in daily operations.

What if we use multiple AI tools from different providers?

Each tool is assessed individually — provider, data processing, and risk class differ. The usage policy summarizes the results so no one has to look up each tool separately.

What does the EU AI Act specifically require of us?

For most businesses, it comes down to two things: transparency and competence. Transparency means people must recognize when they're speaking with an AI system or seeing AI-generated content — this has been in effect since August 2026. Competence means the people deploying such systems are adequately trained to do so. Both are documentable and achievable with manageable effort.

Does this also apply to sole proprietorships?

Yes. The AI Act doesn't distinguish by company size, but by purpose and risk. Anyone with a chatbot on their website is affected — regardless of whether one or a hundred people work in the business.

05 — Next

Data protection and AI compliance by region

Next step

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