Purpose This paper explores the use and perception of artificial intelligence in the context of sustainability in nature-based tourism (NBT) destinations, examining the interplay among ecological conservation, visitor experience and community well-being through a Tourism Social–Ecological–Technological Systems framework. Design/methodology/approach An exploratory sequential mixed-methods design synthesized 44 peer-reviewed studies identified via Scopus and Web of Science. Bibliometric co-occurrence mapping in VOSviewer first established macro-level structural clusters, which directly seeded the coding framework for deductive–inductive thematic analysis in NVivo with inter-rater reliability checks. The study integrated findings from both phases to derive the final socio-technical dimensions. Findings The integrated analysis identified three core clusters: sociotechnical sustainability demonstrates that smart and ambient systems optimize mobility, monitor ecological impacts and support visitor management, though realization depends on institutional capacity and data governance; robotics and automation indicates that while autonomous systems improve operational resilience and resource efficiency, they introduce risks of experiential dehumanization, labour displacement and ethical concerns and social-ecological and human dimensions highlights AI’s capacity to foster environmental stewardship and local livelihoods, while cautioning against algorithmic standardization that privileges commodified, image-driven experiences over low-impact, context-specific practices. Originality/value This study is among the first to synthesize AI–sustainability research in NBT through a multi-dimensional Tourism Social-Ecological-Technological Systems perspective, uncovering systemic synergies and socio-technical tensions to guide responsible technological interventions in fragile destinations.
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Bahcelerli et al. (2026) studied this question.
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