Abstract
No doubt that Artificial intelligence (AI) is shaping the current era. At the same time, climate change is putting agriculture under immense stress—especially in vulnerable, low-resource areas. Rising temperatures, erratic weather, and recurring disasters like droughts and floods are threatening global food production. In this context, sustainable agriculture has become essential for reducing risks and protecting food systems. Nowadays, AI offers powerful solutions. It can forecast climate trends, monitor crop health, and optimize resource use. Through tools like machine learning and computer vision, AI enables smarter farming—helping farmers choose ideal planting windows, detect pests early, and adapt to shifting conditions, to achieve stronger resilience and higher amounts of yields. However, integrating AI into agriculture isn't without challenges. Many developing regions lack the digital infrastructure, finance, and high-quality data needed for effective AI use. While global investment in AI is rapidly growing—with projections reaching $1.39 trillion by 2029—the benefits are unevenly distributed. Added to the environmental concern about the cost of AI, such as high energy use and reliance on scarce materials. To ensure AI contributes to sustainable agriculture and climate action, its development must be guided by ethical principles that promote fairness, transparency, and environmental care. Within this context, this study aims to analyze the current state of the problem, establish sound foundations for its solution, propose several future scenarios, and present a comprehensive set of actionable recommendations for decision-makers.
