What it is
Synthetic data is created using algorithms, often AI models, to mimic the patterns, distributions, and relationships found in original datasets. Unlike anonymized real data, synthetic data does not contain any direct samples from the original source, making it useful for privacy-preserving applications. It can be generated quickly and in vast quantities, addressing issues of data scarcity for model training or testing.
Companies use synthetic data to train AI models when real data is scarce, expensive to acquire, or restricted by privacy regulations like GDPR. This reduces reliance on proprietary or sensitive information, accelerating development in areas like healthcare or finance. Its use can impact the valuation of AI startups that offer synthetic data generation services or rely on it for their products.
Why it matters
Synthetic data enables AI development while respecting privacy and overcoming data scarcity, impacting the speed and ethics of AI innovation.
Reviewed under editorial standardsUpdated September 26, 2026Not investment advice