Leveraging AI-Driven Chatbots For Sustainable Agricultural Advisory Services: Bridging SDG Innovation Gaps In Rural Malaysia

Abstract

The digital transformation of agricultural extension services is gaining momentum as governments and institutions seek to meet the Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger) and SDG 9 (Industry, Innovation, and Infrastructure). In Malaysia, rural agricultural stakeholders often face limited access to timely, expert guidance due to infrastructure gaps, labour shortages, and communication inefficiencies. This study investigates the adoption potential of chatbot technology as an innovative, low-cost solution to enhance digital service delivery in the agricultural sector. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), the research evaluates four key factors, Perceived Ease of Use, Perceived Usefulness, Social Influence, and Security Concerns, that influence behavioral intention to use chatbots among rural agri-entrepreneurs and extension officers. A quantitative cross-sectional survey was conducted with 124 respondents from key agricultural regions in Malaysia. Data were analyzed using SmartPLS 4, applying Partial Least Squares Structural Equation Modeling (PLS-SEM) to validate the measurement and structural models. The results revealed that Perceived Ease of Use and Perceived Usefulness had a statistically significant and positive influence on chatbot adoption, while Social Influence and Security Concerns showed weaker predictive power. These findings have direct implications for the design of digital agricultural interventions and policymaking, suggesting that usability and perceived value are critical to rural technology uptake. The study concludes with recommendations for embedding chatbots into Malaysia’s national agri-extension platforms and highlights the need to enhance digital literacy in rural communities to achieve SDG-aligned agricultural resilience.