Generative Adversarial Networks (GANs) are a powerful tool for creating synthetic data that is nearly indistinguishable from real-world inputs. By having two neural networks one generating data and one evaluating it GANs produce high-quality datasets for training AI in fields like computer vision, speech recognition, and simulation modelling, while reducing the reliance on real user data.