Skip to content
Skuto

Glossary

Anonymization

Anonymization means stripping data of anything that could identify a person, so it stops counting as personal data. In daily AI use it's a simple habit: replace real names, emails and numbers with placeholders before pasting text into a chatbot.

Anonymized data can’t be traced back to a person: not by you, not by anyone, not even by cross-referencing other sources. That’s a high bar: legally, data only escapes the GDPR when re-identification is no longer reasonably possible. Its lighter cousin is pseudonymization, swapping names for codes while a key exists somewhere, which still counts as personal data.

You don’t need the legal fine print to use the idea, though. The everyday version is a thirty-second habit. A bar owner wants help replying to a tricky customer complaint. Instead of pasting “Maria Bianchi, maria.b@gmail.com, table booked on June 3rd,” she writes “a customer, [EMAIL], booked last week.” The chatbot’s answer is exactly as good (it never needed the real details) and nothing identifying has left her computer.

That trick covers most situations: names become roles (“my supplier,” “a patient”), numbers become [PHONE] or [IBAN], addresses become “the customer’s address.” Before you paste something you’re unsure about, run it through our paste checker to see what’s risky where.

Where you’ll meet this

  • GDPR guidance from the EDPB and national authorities on anonymization standards
  • Enterprise AI tools offering automatic redaction or masking of pasted text
  • Privacy policies explaining when data is “anonymized or aggregated”

Put it to work

← Back to the glossary