GDPR and AI: not a contradiction — when done right
AI and data protection are not mutually exclusive. How Domani AI builds GDPR-compliant AI products — privacy by design, not bolted on afterwards.
"Are we even allowed to use AI?" is the question we hear most often from European companies. The answer is: yes. But properly.
The misconception
Many companies believe that AI and the GDPR are incompatible. That is not true. The GDPR does not prohibit the use of AI — it requires that the use be transparent, purposeful and secure. That is exactly what you can build.
Privacy by design: the principle
At Domani AI we do not build a product first and then glue data protection onto it. Data protection is part of the architecture — from the very first line of code.
Concrete measures:
**1. No tracking cookies** We use Plausible Analytics instead of Google Analytics. Plausible is EU-hosted, sets no cookies and collects no personal data. We still see which pages are working.
**2. Data minimization** We only store what we need. Chatbot conversations keep the content, but personal data is anonymized automatically once the consent period expires.
**3. Automatic anonymization** Instead of deleting data (which destroys analysis), we anonymize PII: "Max Mustermann" becomes "Contact_A7B3". The conversations remain available for analytics, but they can no longer be traced to a person.
**4. Consent management** Before any AI processing we obtain clear consent. No dark patterns, no pre-ticked checkboxes, no confusing cookie banners.
**5. Transparency** Our privacy policy clearly states: which data, why, for how long, processed by whom. Including every sub-processor (Anthropic, OpenAI, Supabase, Vercel).
SCCs and international data transfers
Yes, we use US services (Anthropic, OpenAI, Vercel). That is GDPR-compliant when:
- Standard Contractual Clauses (SCCs) are in place
- The processing is purposeful
- The user is informed
We make sure all of this is the case. For every sub-processor.
Bottom line
GDPR and AI are not mutually exclusive — but they do require deliberate engineering. Anyone who treats data protection as a feature rather than a foundation will always run into problems. Anyone who gets it right from the start builds trust and avoids expensive retrofits.
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