SDAIA has published a study on synthetic data for training and testing AI, covering its benefits, its privacy and bias risks, and how to govern it.
The Saudi Data & AI Authority (SDAIA) has published a study titled "Synthetic Data: Opportunities, Challenges, and Governance Mechanisms". Arab News reported on the study on 3 November 2026.
Synthetic data is artificially generated data that follows the patterns of real data. It can be used to train and test AI systems without relying entirely on real datasets. SDAIA says it can help when large amounts of high-quality data are hard to obtain, and can cut the time and cost of collecting and preparing data. The report names healthcare and financial services as sectors where strict privacy rules limit access to real data.
Three types, and the risks
The study describes three types: fully synthetic data created entirely by models, partially synthetic data where some real values are replaced, and hybrid data that combines real and synthetic records. SDAIA notes that synthetic data can help reduce bias by generating more examples for underrepresented groups.
It also warns that synthetic data can carry over biases from the original data, and that people may still be identifiable if the data is not generated and managed properly. SDAIA says organizations should run regular assessments, tests and quality checks.
Recommended governance
For responsible adoption, the study points to clear usage rules, oversight and accountability, quality verification standards, transparency about where data came from and how it was generated, and regulatory sandboxes for safe testing.
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