AI in hospitality and tourism service marketing: a systematic literature review and conceptual framework

The integration of artificial intelligence (AI) in hospitality and tourism service marketing has significantly transformed customer interactions, enabling more efficient operations and personalised experiences. This study employs a systematic literature review (SLR) to explore AI applications in service industries, with a particular focus on hospitality and tourism. An initial dataset of 542 records sourced from the Scopus database (2021–2024) was processed with automated and manual screening following the scientific procedures and rationales for systematic literature reviews (SPAR 4-SLR) protocol, narrowed through multiple filtering stages to a final set of 81 relevant records. These were categorised into four dominant themes using the Latent Dirichlet allocation (LDA) approach in Python: (a) predictive analytics and personalisation (n = 8); (b) AI-powered chatbots and virtual assistants (n = 8); (c) robotics and automation in hotels (n = 16); and (d) AI-driven sentiment and experience analytics (n = 49). The findings highlight key research gaps in multilingual sentiment detection, emotionally intelligent chatbot development and culturally adaptive personalisation systems. Emerging concerns include emotional deception in AI-human interactions and the risk of “personalisation fatigue” in recommendation systems. Integrating these findings, this study proposes a conceptual framework that links the four themes to the stages of the hospitality customer experience lifecycle.