Pests pose a significant challenge to global agriculture, accounting for an estimated 20–40% reduction in crop yields annually and causing widespread economic losses across food systems. Conventional pesticides can effectively control pests and boost yields; however, they also raise costs, harm the environment, reduce biodiversity, and may lead to resistance. Ecological pest management has gained traction as a sustainable and eco-friendly alternative. Artificial intelligence (AI) technologies, including machine learning, computer vision, IoT sensors, and predictive modeling, are being applied to detect pest outbreaks early, accurately monitor population dynamics, and implement precise intervention strategies. This chapter presents the integration of AI with ecological pest management as a pathway toward more resilient and sustainable cropping systems. By combining AI-driven tools with bioagents, we can enhance decision-making, optimize the use of natural enemies, and contribute to global food security. Beyond the theoretical framework, this chapter investigates practical examples and recent case studies demonstrating successful implementation. Finally, it examines the challenges faced by farmers and researchers in adopting these innovations and how such barriers can be transformed into opportunities, marking a shift from chemical-intensive practices toward intelligent, eco-friendly systems that safeguard both crop productivity and environmental health.