With the acceleration of urbanization and the intensification of the impact of climate change, traditional urban agriculture is confronted with challenges such as tight resources, low production efficiency, and complex management. Generative artificial intelligence (GAI), as an emerging technology, has provided a new path for the intelligent transformation of urban agriculture with its powerful data modeling and content generation capabilities. This article analyzes the compatibility of generative AI with urban agriculture from both theoretical and technical perspectives, explores its specific application scenarios in production optimization, marketing innovation, and farmer education, and summarizes the current problems, such as agricultural data silos, model adaptability, cost, and talent shortages. Research shows that generative AI can drive urban agriculture to shift from experience-dependent to intelligent decision-making, enhancing resource utilization efficiency and industrial sustainability. However, its wide application still requires the collaborative support of multiple parties, including policies, technologies, and talents.