The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies into precision irrigation management presents a promising pathway toward sustainable horticultural production. The present investigation studied the yield performance and economic feasibility of chilli (Capsicum annuum L.) cultivation under drip irrigation methods and irrigation scheduling approaches at Water Technology Centre fields, College Farm, College of Agriculture, Rajendranagar, Hyderabad during 2022-23 and 2023-24 of rabi seasons. The experiment was laid out in split plot design with two main plots viz., drip irrigation methods (surface drip and subsurface drip) and four subplots viz., irrigation scheduling approaches (soil moisture sensor, plant water stress sensor, ET sensor based irrigation triggering & irrigation scheduling at 1.0 Epan by manual). Results revealed that higher yield (green fruit+stalk) and economics (₹ 669148 ha-1 & 4.98) were registered with subsurface drip between drip irrigation methods. Among irrigation scheduling approach treatments, yield (green fruit+stalk) and economics (₹ 696735 ha-1 & 5.20) were better with ET sensor based irrigation triggering. The study demonstrates that integrating AI-based decision algorithms with IoT-enabled irrigation sensors not only optimizes resource utilization but also supports climate-resilient and economically viable chilli production. The findings provide a replicable framework for scaling sustainable smart-farming interventions across smallholder horticultural systems.