Academic ResearchJanuary 1, 2026F1000Research

Mapping Research Trends in AI-Based Tourism and Hospitality Marketing: A Bibliometric and Thematic Review

This study systematically reviews 320 peer-reviewed articles from 2003 to 2025 on artificial intelligence (AI) applications in tourism and hospitality marketing. Using bibliometric and thematic analyses, it identifies key publication trends, influential journals and authors, and emerging research themes. The findings reveal a significant growth in AI-related tourism marketing research since 2017, highlighting four main thematic clusters: digital influence and tourist behavior analytics; AI-enabled smart tourism and commerce ecosystems; technology-driven hospitality and experience innovation; and data-driven decision making in predictive tourism modeling. The review underscores AI's transformative role in enhancing personalized marketing, customer engagement, and operational decision-making in the hospitality sector, while also noting challenges related to ethics, data privacy, and maintaining human touch in service.

Authors

Pankaj Kumar Tyagi, Priyanka Aggarwal, Priyanka Tyagi, Asokan Vasudevan, Premendra Kumar Singh

Article content

What the paper studied

This paper systematically reviewed 320 peer-reviewed articles published between 2003 and 2025, focusing on the application of artificial intelligence (AI) in tourism and hospitality marketing. Using the SPAR-4-SLR systematic review protocol, the authors collected relevant publications from the Scopus database and applied bibliometric tools (VOSviewer and Biblioshiny) to map publication trends, influential journals and authors, and keyword co-occurrence. Thematic analysis was then used to identify the main research clusters and emerging themes in the field.

Key findings

There has been a marked increase in AI-related tourism and hospitality marketing research since 2017, with influential journals including the International Journal of Hospitality Management and Tourism Management, and prolific authors such as Buhalis.
Four major thematic clusters emerged: (1) digital influence and tourist behavior analytics, focusing on AI-driven social media analytics and sentiment analysis; (2) AI-enabled smart tourism and commerce ecosystems, exploring seamless commerce and intelligent destination management; (3) technology-driven hospitality and experience innovation, including chatbots, virtual assistants, and immersive technologies; and (4) data-driven decision making in predictive tourism modeling, such as demand forecasting and dynamic pricing.
AI technologies like machine learning, big data analytics, and natural language processing are enabling more effective customer acquisition, personalized marketing, and operational efficiency.
Despite these benefits, the sector faces challenges including ethical concerns, data privacy, algorithm transparency, consumer trust, and the risk of depersonalization and reduced emotional engagement due to overreliance on automation.

Why it matters for hospitality

AI is fundamentally transforming how hospitality businesses approach marketing, customer engagement, and operational decision-making. The shift from descriptive digital tourism studies to strategic, AI-driven analytics highlights the potential for more personalized guest experiences and improved marketing outcomes. However, the findings also stress the need to address ethical issues and maintain a balance between automation and the human touch, which remains critical for memorable service in hospitality.

Practical takeaways

Invest in AI tools that leverage large volumes of structured and unstructured data to tailor products, promotions, and pricing strategies for improved conversion rates and customer loyalty.
Use AI-driven analytics to gain deeper insights into tourist behavior, enabling more effective personalized marketing and destination image management.
Implement AI-enabled smart tourism platforms and technologies like chatbots and virtual assistants to innovate guest experiences and streamline service delivery.
Prioritize responsible and transparent AI use by addressing ethical considerations, data privacy, and maintaining human-centric service to foster consumer trust and emotional engagement.

Adoption of Artificial Intelligence (AI) Technology in Enhancing Tourist Experience: A Conceptual Model

This article proposes a conceptual model for adopting Artificial Intelligence (AI) technology to enhance tourist experiences. It highlights the potential of AI to transform tourism by personalizing services, improving operational efficiency, and enriching guest interactions, offering practical insights for hospitality professionals aiming to leverage AI in their strategies.

Academic ResearchApril 2, 2026

Epicure: Multidimensional Flavor Structure in Food Ingredient Embeddings — LLM-Augmented Data Curation Reveals Culturally and Perceptually Grounded Dimensions in Food Embeddings

This paper demonstrates that AI-generated food embeddings encode far more culinary knowledge than previously understood — capturing not just taste, but texture, cultural identity, and chemical composition. By using LLMs to clean and consolidate a large ingredient dataset, the researchers recovered fifteen distinct flavor dimensions from vector representations alone, with cultural clustering achieving a 6.2× lift over baseline. For hospitality, the implication is that AI can now support meaningful, culturally grounded food personalization at scale — from menu engineering in hotel restaurants to dietary preference matching across guest profiles.

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