Keywords
service personalization
serviceology
hotel industry
entrepreneurial innovations
digital ecosystems
customer loyalty
smart hospitality
How to Cite
Abstract
The article explores personalization based on artificial intelligence (AI) as a catalyst for entrepreneurial innovations in the hotel industry. It examines current trends in the transformation of hotel services from reactive models of customer care to contextualized and predictive journeys, where guest needs are anticipated before being explicitly expressed. The use of machine learning algorithms, natural language processing systems, embedding representations, and multi-criteria recommendation models enables the creation of personalized services that are integrated into the overall guest experience and enhance its emotional value. Special attention is given to the integration of heterogeneous data sources in real time, including transactional, behavioral, and contextual factors, as well as the application of social robots and digital concierges within hotel spaces. The article emphasizes the ethical and legal dimensions of personalization, including algorithmic transparency, data privacy, and user control over personalization parameters. The literature review demonstrates that current scientific approaches focus not only on technical solutions but also on building long-term trust, customer loyalty, and the economic efficiency of enterprises. At the same time, several research gaps have been identified, including the lack of longitudinal studies, insufficient metrics for evaluating the «contextuality» of the guest experience, and the challenges of scaling innovative systems. The article holds practical value for hotel chains and small businesses, as it proposes a comprehensive approach to AI implementation that integrates technical, ethical, and behavioral aspects. Its conclusions can serve as a foundation for designing digital transformation strategies, enhancing competitiveness, and ensuring sustainable development of hospitality enterprises. AI-based personalization is conceptualized as a powerful driver of business models, capable of generating new revenue streams, optimizing costs, and expanding customer segments. Thus, the article combines scientific and practical perspectives, offering a conceptual framework for entrepreneurial innovations in the hospitality industry.
References
McKinsey & Company. The future of personalization – and how to get ready for it. URL: https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-future-of-personalization-and-how-to-get-ready-for-it (дата звернення 10.09.2025).
Shambour M., Abu-Shareha M., & Abualhaj M. Personalization in Hospitality: A Review of Techniques and Applications. Journal of Hospitality and Tourism Technology, 2022. Vol. 13(4), Р. 567-586. DOI: https://doi.org/10.1108/JHTT-09-2021-0194
Li Y. Research on a Hotel Collaborative Filtering Recommendation Algorithm Based on the Probabilistic Language Term Set. Mathematics. 2023. Vol. 11, № 19. DOI: https://doi.org/10.3390/math11194106
Aravani S., Pintelas P., & Pintelas E. BERT-Based Sentiment Analysis for Hotel Reviews. Journal of Hospitality and Tourism Technology. 2024. Vol. 15(2), Р. 345-358. DOI: https://doi.org/10.1108/JHTT-04-2023-0156
Sadeghian M., Goharian M., & Ghasemzadeh F. Hotel2Vec: A Neural Network-Based Approach for Hotel Recommendation. Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI). 2019. Р. 1-7.
Said S., & Al-Hyari K. Ethical and Practical Challenges of AI in Hospitality. Tourism Management. 2023. Vol. 85, Р. 1-10. DOI: https://doi.org/10.1016/j.tourman.2023.104-115
Kim M. Lim S. AI-powered personalized recommendations and pricing: Moderating effects of ethical AI and consumer empowerment. International Journal of Hospitality Management. 2025. DOI: https://doi.org/10.1016/j.ijhm.2025.103862
Nira R. A. AI-Driven Hyper-Personalization in Hospitality: Application, Present and Future Opportunities, Challenges, and Guest Trust Issues. International Journal of Research and Innovation in Social Science (IJRISS). 2025. Vol. 9, № 4. P. 5562-5573. DOI: https://doi.org/10.47772/IJRISS.2025.90400397
Ivanov S. Social Robot Privacy Concern (SRPC): Rethinking Privacy Concerns within the Hospitality Domain. International Journal of Hospitality Management. 2024. Vol. 122. DOI: https://doi.org/10.1016/j.ijhm.2024.103862
Saxena S., Gupta S., & Kumar, R. Economic Implications of AI-Powered Personalization in Hospitality. Journal of Revenue and Pricing Management. 2024. Vol. 23(3), Р. 234-245. DOI: https://doi.org/10.1057/s41272-024-00345-6
Upmann P. AI Governance in the Hospitality Industry. AIGN Global. 2025. URL: https://aign.global/ai-governance-consulting/patrick-upmann/ai-governance-in-the-hospitality-industry (дата звернення 10.09.2025).
McKinsey & Company (2025), “The future of personalization – and how to get ready for it”, available at: https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-future-of-personalization-and-how-to-get-ready-for-it (Accessed 10 September 2025).
Shambour, M., Abu-Shareha, M. and Abualhaj, M. (2022), “Personalization in hospitality: A review of techniques and applications”, Journal of Hospitality and Tourism Technology, vol. 13, no. 4, pp. 567–586, DOI: https://doi.org/10.1108/JHTT-09-2021-0194
Li, Y. (2023), “Research on a hotel collaborative filtering recommendation algorithm based on the probabilistic language term set”, Mathematics, vol. 11, no. 19, DOI: https://doi.org/10.3390/math11194106
Aravani, S., Pintelas, P. and Pintelas, E. (2024), “BERT-based sentiment analysis for hotel reviews”, Journal of Hospitality and Tourism Technology, vol. 15, no. 2, pp. 345–358, DOI: https://doi.org/10.1108/JHTT-04-2023-0156
Sadeghian, M., Goharian, M. and Ghasemzadeh, F. (2019), “Hotel2Vec: A neural network-based approach for hotel recommendation”, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), pp. 1–7.
Said, S. and Al-Hyari, K. (2023), “Ethical and practical challenges of AI in hospitality”, Tourism Management, vol. 85, pp. 1–10, DOI: https://doi.org/10.1016/j.tourman.2023.104115.
Kim, M. and Lim, S. (2025), “AI-powered personalized recommendations and pricing: Moderating effects of ethical AI and consumer empowerment”, International Journal of Hospitality Management, DOI: https://doi.org/10.1016/j.ijhm.2025.103862.
Nira, R.A. (2025), “AI-driven hyper-personalization in hospitality: Application, present and future opportunities, challenges, and guest trust issues”, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9, no. 4, pp. 5562–5573, DOI: https://doi.org/10.47772/IJRISS.2025.90400397
Ivanov, S. (2024), “Social robot privacy concern (SRPC): Rethinking privacy concerns within the hospitality domain”, International Journal of Hospitality Management, vol. 122, DOI: https://doi.org/10.1016/j.ijhm.2024.103862
Saxena, S., Gupta, S. and Kumar, R. (2024), “Economic implications of AI-powered personalization in hospitality”, Journal of Revenue and Pricing Management, vol. 23, no. 3, pp. 234–245, DOI: https://doi.org/10.1057/s41272-024-00345-6.
Upmann, P. (2025), “AI governance in the hospitality industry”, AIGN Global, available at: https://aign.global/ai-governance-consulting/patrick-upmann/ai-governance-in-the-hospitality-industry (Accessed 10 September 2025).