Synthetic Data: The New Data Frontier

Data-driven decision-making shapes every aspect of our lives. Yet access to high-quality, representative data remains a persistent challenge. Real-world datasets are often incomplete, biased, restricted by privacy concerns, or simply unavailable – hindering innovation and reinforcing systemic inequalities.

Synthetic data offers a solution. Synthetic data is data artificially generated to mimic the statistical properties, structure and distribution of real-world data. It can fill data gaps, protect privacy and enable the testing of new scenarios, providing a scalable and cost-effective alternative when real world data is limited or sensitive.

However, synthetic data introduces new governance and ethical risks. If not carefully generated and managed, it can perpetuate biases in the original datasets, mislead decision-makers, leak sensitive information, or be weaponized for malicious purposes (such as through the creation of deepfakes). Ensuring the accuracy, traceability and clear labelling of synthetic data is essential to mitigate risks, preserve model performance and maintain public trust.

Recognizing synthetic data’s transformative potential, the World Economic Forum’s Global Future Council on Data Frontiers has developed this executive primer to explain its main types, use cases and governance considerations. This strategic brief seeks to empower leaders across public, private, academic and civil society sectors to harness synthetic data for innovation – while upholding standards of accuracy, equity and privacy.