This article explores the application of generative artificial intelligence (GAI) in enhancing the communication and networking performance of unmanned aerial vehicles (UAVs). The authors review key GAI technologies and their roles in UAV networking, highlighting the limitations of traditional discriminative and predictive AI methods. They propose a novel framework for advanced UAV networking using GAI and present a case study on UAV-enabled spectrum map estimation and transmission rate optimization. The framework leverages GAI to improve communication, network, and security performances, demonstrating its effectiveness through experimental results. The article also discusses future directions, including energy-efficient GAI, secure GAI, and multimodal processing on UAVs. The contributions of the article include a systematic tutorial on GAI for UAV communication and networking, a novel framework, and a case study to validate the effectiveness of GAI in these areas.This article explores the application of generative artificial intelligence (GAI) in enhancing the communication and networking performance of unmanned aerial vehicles (UAVs). The authors review key GAI technologies and their roles in UAV networking, highlighting the limitations of traditional discriminative and predictive AI methods. They propose a novel framework for advanced UAV networking using GAI and present a case study on UAV-enabled spectrum map estimation and transmission rate optimization. The framework leverages GAI to improve communication, network, and security performances, demonstrating its effectiveness through experimental results. The article also discusses future directions, including energy-efficient GAI, secure GAI, and multimodal processing on UAVs. The contributions of the article include a systematic tutorial on GAI for UAV communication and networking, a novel framework, and a case study to validate the effectiveness of GAI in these areas.