Next-Gen Farming: The Role of AI and ML in Sustainable Agricultural Innovation

The agricultural sector plays a vital role in supporting human life by supplying essential food, fibers, and raw materials. Recent technological progress has significantly transformed agriculture, with Artificial Intelligence (AI) and Machine Learning (ML) becoming major contributors. This article outlines the scope of agriculture and highlights the critical role of modern technologies. AI and ML have reshaped traditional farming practices across areas such as crop cultivation, livestock care, aquaculture, forestry, and agribusiness. These innovations are essential for overcoming challenges like resource limitations, climate change, and population growth. The application of technology in agriculture has led to increased yields, better precision in farming, efficient use of resources, improved disease and pest control, and streamlined supply chains. AI and ML now serve as valuable tools by enabling soil and crop monitoring, precision agriculture, robotic automation, predictive insights, livestock tracking, and drone deployment. Their integration supports higher productivity, minimizes waste, fosters sustainability, and enables data-driven agricultural decisions. In response to rising food security concerns and climate change, the agricultural sector is increasingly integrating AI into its operations. Although many benefits are expected, a clear understanding of the motivations and outcomes of AI adoption is still developing. This study addresses that gap by examining core themes surrounding AI in agriculture through the lens of dynamic capabilities. By using centering resonance analysis, we analyzed news content from 2014 to 2019 across Asia, Africa, Europe, and North America. Findings indicate that AI is mainly employed to boost efficiency and output, while also helping to address labor shortages and environmental issues. Regionally, North America and Europe lead in AI adoption, with Asia and Africa showing growing engagement.