What is AI data anonymization?
AI data anonymization is the process of automatically detecting and removing or masking personally identifiable information (PII) before processing by AI models. This includes names, social security numbers, email addresses, phone numbers, IP addresses, and other identifiers.
Why is this critical?
Sending non-anonymized data to LLMs (especially cloud-based) carries serious risks: GDPR violations, personal data leaks, and data being used for external model training. Anonymization enables leveraging AI power without compromising customer and employee privacy.
Anonymization techniques
Modern systems combine: Named Entity Recognition (NER) for PII detection, reversible tokenization (replacing PII with tokens that can restore originals), pseudonymization (replacing with fictitious but structurally valid data), and k-anonymization for statistical datasets.