The study explores agentic AI characterization on autonomy, adaptivity, empathy and transparency shaping sustainable consumer engagement within health and wellness tourism. Further, it aims to understand the mechanisms of AI agency promoting long-term trust, empathy and sustainability outcomes in digitalized service ecosystems.
An integrated mixed-method design was employed, combining qualitative inquiry, fuzzy Delphi expert validation and Bayesian structural equation modeling with data from 1,853 consumers across six countries. The study draws on actor–network theory (ANT) and systems theory to conceptualize AI as both a relational actor and a systemic stabilizer of sustainability.
Results reveal that agentic AI significantly enhances sustainable consumer engagement both directly and indirectly through trust and perceived empathy. Transparency moderates these effects, strengthening the link between AI characteristics and user trust. Sustainable engagement, in turn, predicts loyalty, well-being and sustainability advocacy. Cross-cultural analysis confirms model robustness while highlighting variations in transparency sensitivity across digital readiness levels. The study contributes a validated integrative ANT systems framework with strong Bayesian evidence linking AI agency to sustainability outcomes.
Service organizations and wellness tourism providers can leverage agentic AI to foster authentic, trust-based and ethically sustainable consumer relationships. Designing AI systems with empathic communication, transparent data practices and cultural adaptivity can reinforce long-term engagement and sustainability alignment.
This study is original in its integration of qualitative themes and expert consensus into Bayesian modeling, directly connecting exploratory and confirmatory research. It uniquely accounts for Southeast Asia's regional factors such as linguistic diversity and healthcare variation and reveals how trust, empathy and transparency interact with agentic AI in this context. By focusing on sustainable engagement in AI-driven health and wellness tourism, the research addresses a significant gap in the literature.
