Socioeconomic Impact of Smart Agriculture

Smart agriculture, supported by deep learning (DL), Internet of Things (IoT), and blockchain technologies, is transforming agrarian systems by enabling real-time data analytics, precision resource management, and transparent value chains. These advancements increase farm productivity, improve market access, and provide greater income stability for smallholders. This chapter analyzes the socioeconomic impacts of smart agriculture, including the inclusion of marginalized groups, shifts in employment toward technology-enabled roles, rural economic diversification, risk mitigation through predictive tools and parametric insurance, and enhanced value chain integration. These effects are shown through Indian case studies such as Tamil Nadu’s IoT irrigation (50% water savings, 30% yield gains), Maharashtra’s PoCRA (15–20% productivity increase), and Odisha’s Ama Krushi (90% higher harvests in rain-deficit areas). However, challenges like digital divides, affordability constraints, algorithmic biases, data privacy concerns, labor displacement due to automation, and increased technological dependency may undermine equitable outcomes without targeted interventions. To fully realize the transformative potential of smart agriculture, policy priorities should include developing inclusive digital infrastructure, farmer-centric data governance, public–private partnerships for capacity building, ethical Artificial Intelligence (AI) frameworks, and integrating indigenous knowledge to promote resilient and equitable agricultural futures.