Artificial Intelligence (AI) is revolutionizing agriculture by enabling data-driven, sustainable, and equitable farming practices. This review synthesizes AI applications—machine learning, computer vision, robotics, and IoT integration—to enhance crop productivity, resource efficiency, and climate resilience. We propose a novel Inclusive AI-Agriculture Framework (IAAF) that integrates AI with traditional knowledge and equitable access to address global food security. The review critically evaluates AI’s role in yield prediction, soil management, pest detection, and supply chain optimization, with a focus on India, particularly Punjab and Haryana. Barriers, including high costs, digital literacy gaps, and ethical concerns (e.g., data privacy, rural employment), are analyzed, alongside strategies like policy incentives and public-private partnerships. Global and regional adoption trends are presented, supported by a systematic literature review of 60 studies from 2018–2023. Future directions emphasize localized, climate-smart, and ethically grounded AI solutions. This paper underscores AI’s transformative potential to create resilient, inclusive agricultural systems.