Adoption Dynamics and Environmental Impact of AI-Enabled Drones in Precision Agriculture – A Theoretical Approach

Abstract

The adoption of AI-powered agricultural drones presents transformative potential for sustainable farming. This study examines the potential benefits of AI-powered agricultural drones, focusing on farmer perceptions, behavioral intentions, and sustainable usage aligned with the Sustainable Development Goals (SDGs). A comprehensive review (2018–2024) reveals a significant increase in global research post-2018, particularly from China, India, the U.S., and Brazil. This study develops an integrated conceptual framework combining the Technology Acceptance Model (TAM) and the Diffusion of Innovation (DOI) theory to investigate the behavioral factors influencing farmers’ adoption of drone technology. Key constructs from TAM—Perceived Usefulness (PU) and Perceived Ease of Use (PEOU)—are combined with DOI variables such as Relative Advantage, Compatibility, and Complexity to examine their influence on Behavioral Intention (BI) and actual Drone Usage. Furthermore, the model extends to assess the impact of drone adoption on sustainability outcomes, specifically SDG 2 (Zero Hunger), SDG 9 (Industry, Innovation and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). By embedding technological adoption within a sustainability framework, this study offers a holistic view of how socio-technical factors drive environmentally and economically beneficial outcomes in the agricultural sector. The framework serves as a foundation for empirical research and policy development aimed at accelerating drone adoption for sustainable agricultural transformation.