Synthetic Data Explained: How It Works and Why It Matters in 2026

Frequently Asked Questions

01.What is synthetic data?

Synthetic data is records produced by rules, simulations or a generative model rather than collected from real people or events. It is built to mimic the structure and statistics of a real dataset closely enough to test software, train or evaluate a model, or share data with partners.

02.Is synthetic data automatically anonymous under GDPR?

No. Under GDPR Recital 26, data stays personal if a person is identifiable by means reasonably likely to be used, and synthetic records generated from personal data can still leak information about individuals in the source. Treat the output as personal data until a re-identification test supports a different conclusion.

03.Can a startup train a model on synthetic data alone?

Sometimes, for a narrow task, but I would not plan on it. The Stanford AI Index 2026 reports that synthetic data is still not replacing real data in pre-training (Stanford HAI, 2026), and research on model collapse shows that training on generated data can erase the rare cases a product depends on.

04.What does the amended EU AI Act say about synthetic data?

Article 4a, inserted by Regulation (EU) 2026/1744 (EUR-Lex, July 2026), lets AI providers and deployers exceptionally process special categories of personal data where strictly necessary for bias detection and correction, only if other data, including synthetic or anonymised data, cannot do it effectively, and the records of processing must explain why.