By 2026, 75% of businesses will use generative AI to create synthetic customer data, up from less than 5% in 2023. Synthetic data addresses gaps when real data is sensitive, costly, biased, or insufficient, boosting AI model accuracy (60%), efficiency (56%), privacy protection (45%), explainability (31%), and bias reduction (30%). Methods include simulation, statistical techniques like SMOTE, and AI-driven generation such as GANs. Best practices: choose the right generation method, address privacy early, validate outputs, blend augmentation with generation, and ensure scalability.

Join for free to read