Against the backdrop of rural revitalization and agricultural modernization, traditional pig farming models are confronted with multiple challenges, including low efficiency, severe environmental pollution, and food safety risks. This study takes the “Zhu” Guang Yiyi—an AI-empowered rural ecological pig farming project—as the research object, and focuses on the deep integration of artificial intelligence with ecological breeding. It proposes a trinity development model integrating intelligent farming, ecological recycling, and data-driven management. By introducing Internet of Things (IoT) sensing devices, machine learning algorithms, and big data analytics, the study realizes intelligent management throughout the entire pig breeding process, including precision feeding, environmental regulation, and disease early warning. Meanwhile, a resource recycling system of “pig–biogas–fertilizer–planting” is established to enable the energy conversion and fertilizer utilization of livestock waste, thereby promoting green transformation in agriculture. On this basis, a data platform is employed to achieve coordinated optimization of production, management, and marketing, and to extend the ecological farming industry chain toward processing, e-commerce, and agri-tourism integration. The results indicate that AI technologies can significantly improve farming efficiency and resource utilization, while reducing disease risks and environmental burdens, providing a replicable and scalable technological pathway and practical paradigm for rural industrial revitalization.