Applications of AI in Future Farming

Global food production faces serious threats as the world population increase significantly by 2050. At the same time, approximately 24 billion tons of fertile soil are lost annually and water scarcity affects nearly 40 % of the global population. Here comes the relevance of artificial intelligence (AI) offers, which offers transformative solutions to these challenges by enabling smarter and data-driven farming practices. This chapter comprehensively explores how AI technologies are being applied across all stages of modern agriculture. The role of sensor networks, satellite imagery and drone surveillance to collect real-time field data, and utilisation of machine learning algorithms to process and guide precision soil management, irrigation scheduling and nutrient application are discussed in detail. Advanced computer vision systems to detect crop diseases and pest infections at early stages, for timely and targeted remedies to reduce chemical usage has also been included. AI-powered yield prediction models provide accurate harvest forecasts, while automated robots perform for planting, weeding, praying and harvesting open-up novel opportunities with minimal human labour. Environmental stability strengthening through AI-assisted water conservation, carbon footprint monitoring and biodiversity management has also been included. The chapter also addresses major adoption barriers such as poor rural connectivity and high implementation costs. Evidence from global case studies confirms that AI could increase the yield of 10-20 % water saving of 20-40 %labour reduction of 30-50 % and pesticide reduction to 40-6- %, establishing AI as an essential pillar for future sustainable agriculture.