Under the rapid development of live commerce, impulse buying has become a core consumption phenomenon, yet its psychological triggering pathways across different consumer groups remain to be fully elucidated. Drawing on the S–O–R framework, this study conceptualizes live-stream interactivity, novelty, and streamer attractiveness as external “stimuli,” and positions immersive experience as the core “organism” mechanism, thereby constructing and testing an integrated “stimulus–experience–response (impulse buying intention)” model. Using a mixed-method approach that combines structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA), the results show that all three live-stream features significantly enhance impulse buying intention, primarily by strengthening immersive experience, with immersion exerting a significant partial mediating effect. Moreover, consumers’ loneliness significantly amplifies the indirect effect of live-stream features on impulse buying via immersive experience. The fsQCA further uncovers multiple equivalent pathways leading to high impulse buying intention, including a strong-experience pattern centered on “streamer attractiveness + immersive experience,” as well as a social compensation pattern centered on “high interactivity + high loneliness.” This study provides a testable theoretical framework, actionable operational strategies, and sustainable ethical guidance for live commerce, offering a pathway for the industry to achieve a “high experience × high conversion × high well-being” triple-win outcome.

Sustainable rural cultural tourism requires effective approaches to improving the visibility, accessibility, and decision feasibility of dispersed cultural resources, particularly in destinations where service information is fragmented across online and offline channels and tourists face substantial uncertainty in coordinating transport, accommodation, and cultural experiences. This study examines how artificial intelligence (AI) agents can support the sustainable digital transformation of rural cultural tourism by alleviating information asymmetry, releasing latent tourism demand, and facilitating calibrated human–machine trust. Drawing on human–machine trust theory and the Stimulus–Organism–Response framework, this study conceptualizes AI agent functionality through three dimensions: AI Information Quality (AIQ), Information Extensibility (IE), and AI Planning Autonomy (APA). Travel Planning Risk Awareness (TPRA), Human–Machine Trust (HMT), Planning Satisfaction (PS), Rural Cultural Tourism Attractiveness (RCTA), and Rural Cultural Tourism Intention (RCTI) are further incorporated into an integrated model comprising four pathways: information empowerment, autonomy–risk awareness tension, trust boundary, and demand release. Using the Ctrip AI Travel Assistant as the research context, 413 valid questionnaire responses were analyzed through a hybrid Structural Equation Modeling–Artificial Neural Network approach. The results support 12 of the 14 hypotheses. AIQ significantly influences IE (β = 0.530), PS (β = 0.304), and HMT (β = 0.380). HMT functions as a central mechanism connecting AI empowerment with tourism decision-making and exerts the strongest effect on RCTA (β = 0.485), reaching 100% normalized importance in the corresponding ANN model. TPRA positively affects HMT (β = 0.262), indicating that risk awareness can facilitate rational and calibrated trust rather than simply inhibiting AI acceptance. RCTA (β = 0.281) and PS (β = 0.218) jointly promote RCTI through the complementary mechanisms of destination pull and planning push. The findings demonstrate that AI agents can contribute to the sustainable development of rural cultural tourism by improving information accessibility, strengthening responsible human–AI collaboration, and transforming fragmented cultural resources into credible and actionable travel-planning options. This study provides implications for sustainable destination marketing, responsible AI travel-service design, rural revitalization, and the long-term development of rural cultural tourism, while clarifying trust as a psychological gate in AI empowerment.