From AI readiness to regenerative tourism orientation: a tourist-centric model of smart tourism villages

Purpose This study develops and validates a tourist-centric model of AI-driven smart tourism villages (AI-DSTV), explaining how perceived digital infrastructure and smart governance relate to tourist acceptance and perceived regenerative tourism orientation (PRTO) through rural authenticity, value co-creation, AI trust, and perceived service value. Design/methodology/approach A cross-sectional survey involved 686 domestic tourists who had experienced an AI-supported tourism touchpoint in rural tourism settings in Indonesia. The sample was predominantly young and digitally engaged, with 75.1% aged 18–24 and 68.4% students. The model was tested using partial least squares structural equation modeling (PLS-SEM) with 10,000 bootstrap resamples and importance-performance map analysis (IPMA). Findings All 12 hypothesized relationships were significant. Rural authenticity strongly enhanced perceived AI service value, while tourist value co-creation strengthened AI trust and ethical acceptance. Digital infrastructure and smart governance also showed significant downstream effects through authenticity–service-value and co-creation–trust pathways. The model explained 56.3% of PRTO variance. IPMA identified AI trust and ethical acceptance as the most important antecedent of PRTO and the lowest-performing construct, indicating a key managerial priority. Practical implications Rural destinations should prioritize transparent, culturally grounded, participatory and locally accountable AI systems. Strengthening ethical trust, co-creation, and culturally appropriate personalization may offer greater managerial leverage than technological sophistication alone. Originality/value The study extends technology-adoption research beyond behavioral acceptance by introducing PRTO as a tourist-level psychological outcome. It conceptualizes AI-DSTV as a socio-technical ecosystem linking destination readiness with authenticity, co-creation, trust and service evaluation while distinguishing regenerative orientation from verified destination regeneration.