Artificial Intelligence Development and Sharing Policy in an Agriculture Platform With Self-Built Farm

As artificial intelligence (AI) technology continues to advance, an increasing number of platforms are integrating AI into their agricultural investments to manage pests and diseases. However, the complexity of AI application may increase the planting costs for farms. Meanwhile, platforms building their own farms is becoming a common practice in agriculture. This study presents a contract farming supply chain involving a platform and a farmer, where the platform resells the farmer's products and introduces its own farm's products as competitors. Unlike improving consumer utility, AI is developed to increase agricultural yields in this study. We use game theory to analyze and compare three AI technology policies of the platform: no AI, only developing AI in the self-built farm, and sharing AI with the farmer. Results show that the platform benefits from AI and shares the technology only if AI technology increases the efficiency of agricultural planting or slightly reduces it. Interestingly, the higher the AI technology effect, the less likely the farmer is to accept AI sharing policy. Additionally, when the farmer accepts it, the higher its efficacy, the less advantageous it may become. Through extended analysis, we find that these conclusions are stable regardless of whether the platform charges technology fees to the farmer or whether the role of AI is restricted. These insights contribute to a deeper understanding of AI technology policies for platforms in agricultural production.