Artificial intelligence (AI) is revolutionizing agriculture, making precision farming more efficient and data-driven. However, widespread adoption remains challenging due to limited computing resources, unreliable Internet access, and the need for real-time decision-making in the field. To address these constraints, this chapter introduces AgriNet-Light, a conceptual framework designed to leverage lightweight AI models that operate efficiently on edge devices like drones, IoT sensors, and mobile phones without relying on cloud-based infrastructure. AgriNet-Light incorporates key innovations, including multimodal data fusion, attention mechanisms, and adaptive decision-making, enabling AI-driven insights directly in the field. This framework has critical applications in crop disease detection, yield prediction, pest management, and smart irrigation, offering a scalable and energy-efficient alternative to traditional AI models. By bridging the gap between AI capabilities and agricultural constraints, AgriNet-Light empowers smallholder farmers and large agricultural enterprises, enhancing productivity, sustainability, and accessibility. As the demand for real-time, resource-efficient AI solutions grows, lightweight models like AgriNet-Light will play a pivotal role in shaping the future of smart farming and sustainable food production.