Deep Learning: A Catalyst for Sustainable Agriculture Transformation

This chapter explores the potential of AI to transform sustainable agricultural development across several regions of India. The research examines the dynamic realm of artificial intelligence applications in agriculture, investigating the possible advantages, disadvantages, and impacts. In addition to exploring opportunities such as climate-resilient techniques, data accessibility, and precision farming, we also consider challenges such as inadequate technological infrastructure and a shortage of experienced labor. This article explores the impact of artificial intelligence (AI) on supply chains, inclusive growth, and smallholder farmers. Engaging in discussions about ethical concerns and the consequences of policies also provides insights into the appropriate incorporation of AI. This chapter provides further insight into the ongoing discourse on utilizing artificial intelligence to advance agricultural sustainability. Data science innovation can potentially create novel products, services, technology, and business models within the agriculture industry. There are two primary avenues through which an inventive concept might progress: uncovering a superior method to address an existing issue or redefining an existing problem to enhance its importance before determining how to resolve it. Although they may come from different origins, both types of creativity are powerful.