Agriculture and Food in the Era of Generative Artificial Intelligence: Constructing the AIFE-SC (Artificial Intelligence–Food–Ecology Symbiosis Cycle) Theory

Generative Artificial Intelligence (AI) is profoundly changing the development model of the global agriculture and food industry. From smart planting, agricultural robots, and precision fertilization to food research and development, supply chain optimization, and personalized nutrition services for consumers, AI has gradually become an important driving force for agricultural modernization. However, existing research focuses more on specific technological applications and lacks a theoretical framework that can systematically explain the synergistic development of agriculture, food, and ecology. Therefore, this paper proposes the AIFE-SC (Artificial Intelligence–Food–Ecology Symbiosis Cycle) theory. This theory posits that generative AI, through three core capabilities—data generation, knowledge generation, and decision generation—drives a dynamic and synergistic cycle among agricultural production systems, food supply systems, and ecological environment systems. This paper constructs a theoretical model, operational mechanism, and evaluation index system, and explores its application value in smart agriculture, precision food manufacturing, agricultural supply chain management, and sustainable development. Research shows that the AIFE-SC theory can explain the process of agricultural systems transforming from traditional production models to intelligent ecosystems in the era of generative AI, providing a new theoretical foundation for future agricultural digitalization and food industry upgrading.