Synthetic Data 2025
Page 3 of 14 · WEF_Synthetic_Data_2025.pdf
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 Frontiers1 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.Synthetic Data: The New Data Frontier September 2025
Introduction
Synthetic Data: The New Data Frontier
3
Ask AI what this page says about a topic: