As real-world data becomes harder to obtain due to privacy regulations and copyright concerns, synthetic data — artificially generated training data — has emerged as a critical resource for AI development.
What Is Synthetic Data?
Synthetic data is artificially generated information that mimics the statistical properties of real data without containing actual personal information. It can include text, images, tabular data, and even video.
Key Advantages
- Privacy compliant: No personal data means no GDPR/CCPA concerns
- Unlimited scale: Generate as much as you need, when you need it
- Bias control: Deliberately balance datasets to reduce AI bias
- Edge cases: Generate rare scenarios that are hard to find in real data
Market Growth
Gartner predicts that by 2028, 60% of all data used for AI training will be synthetic, up from 10% in 2023. Leading providers include Gretel, Mostly AI, and Tonic.ai.
The challenge: synthetic data can amplify biases if the generation process isn't carefully designed, and models trained exclusively on synthetic data may miss real-world nuances.
