This talk focused on how Federated Learning stood as one of the most significant opportunities to enable the next AI breakthrough. We explored the core principles of FL, compared it with conventional methods, and discussed real-world applications that demonstrated its potential to revolutionize industries such as healthcare, finance, and telecommunications. Through our work on Flower, an end-to-end framework that enabled both FL research and FL production deployments in enterprise settings, we aimed to illustrate a clear pathway for integrating Federated Learning into mainstream AI development. The convergence of FL with emerging technologies positioned it not just as an incremental improvement but as a catalyst for unprecedented progress in AI.