The Perception of Climate Change Threats on Intention to Use AI for Sustainable Agriculture Among Thai Farmers

Climate change is significantly impacting sustainable agriculture and poses a threat that is likely to motivate farmers to adapt by applying AI technology to reduce risks, costs, expenses, and the impact on greenhouse gas emissions. In other contexts related to climate change, it is important to assess whether perceived climate threats and perceived vulnerability to climate change influence farmers’ intention to use artificial intelligence and whether farmers believe AI is an effective method for addressing climate change, as well as their confidence in its effectiveness. This research examines whether the ability to learn about AI independently affects the intention to use AI, aligning with Protection Motivation Theory. It further evaluates whether perceived ease of use of AI influences perceived usefulness, considering the core factors of perceived ease of use and perceived usefulness based on the Technology Acceptance Model as influencing the intention to use AI. Furthermore, it investigates whether PEOU (Perceived ease of use) and PU (Perceived usefulness) affect attitude (a key factor in the Theory of Planned Behavior) and subjective norm (another core factor in TPB (Theory of Planned Behavior)) influencing farmers’ behavioral adaptation to AI use. Therefore, exploring farmers’ behavioral intention to use AI integrates three theories: PMT (Protection Mo-tivation Theory), TPB, and TAM (Technology Acceptance Model), presenting them as a conceptual model to examine the motivating factors influencing behavioral change. This research surveyed 471 farmers in Thailand using data analyzed from PLS-SEM (Partial Least Squares Structural Equation Mod-eling). The findings revealed that only eight hypotheses (AI self-efficacy, PEOU, PU, ATT (Attitude), and SN (Social Norm)) significantly influenced the intention to use AI, while three hypotheses (PS (Perceived severity), PV (Perceived vulnerability), and RE (Response efficacy)) did not. This will be useful for planning or strategizing AI adoption among farmers, focusing on reducing problems and obstacles from insignificant factors to achieve sustainable agriculture and minimize the impact that may lead to inequality from AI use, or the AI divide, in the future.