Agriculture remains the backbone of global food security, yet it faces unprecedented challenges due to population growth, climate change and resource scarcity. Artificial Intelligence (AI) has emerged as a transformative solution, enabling precision agriculture through data-driven decision-making, automation and predictive analytics. Empirical studies demonstrate that AI-based interventions can increase crop yields by 20–30%, reduce water usage by up to 50% and minimize chemical inputs by 40–77%, thereby promoting both economic efficiency and environmental sustainability. In the Indian context, where agriculture supports nearly 50% of the workforce and is highly vulnerable to climate variability, AI integration aligns with national initiatives such as Digital Agriculture Mission and PM-KISAN. Karnataka, as a leading agricultural state in horticulture and plantation crops, provides a compelling case with university-led pilot projects showing productivity gains of 22–25% in crops like ragi, rubber and coffee. This research article employs a narrative review approach following PRISMA-ScR guidelines, synthesizing 35 empirical studies conducted between 2015 and 2026. The findings indicate significant improvements in total factor productivity (TFP), resource efficiency and climate resilience. However, challenges such as digital divide, high adoption costs and ethical concerns related to data privacy persist. The study concludes that AI-driven agriculture has the potential to revolutionize farming systems in India, provided that policy frameworks focus on inclusivity, infrastructure development and capacity building among farmers.