TRANSFORMATION OF THE DIGITAL TOURISM SYSTEM: FROM INTELLIGENT AGENTS TO AGENTIC AI
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
The purpose of the paper is to examine the structural and functional transformation of the digital tourism ecosystem during the transition from traditional intelligent assistants, such as LLM-based chatbots, to a new paradigm of Agentic Artificial Intelligence. The subject of the present study is the qualitative transition from passive digital tools that rely on continuous human prompts to subjective systems characterised by autonomous planning, multi-agent coordination, and independent execution of complex service chains. The research methodology is based on a systems approach and organisational theory, using comparative analysis of artificial intelligence architectures to highlight the functional evolution of the industry. The methodological framework underpinning this study is predicated on the cyclical Action Research model, which encompasses planning, action, observation, and reflection. This model elucidates the iterative reasoning and self-repair capabilities of Agentic systems. Furthermore, the study employs the notion of multi-agent orchestration to model the interaction between specialised digital entities and proposes a conceptual model for assessing the socio-economic and ethical aspects of AI implementation, balancing human interests, environmental sustainability, economic profit and long-term development potential. The primary objective of this study is to provide a conceptual justification for the transition from auxiliary service tools to full-fledged digital management entities in tourism. The article provides a comprehensive overview of the conceptual features of Agentic AI, advances a functional model for its application in the tourism sector, and posits that these systems have the capacity to autonomously manage fragmented tourism services, including logistics, accommodation, and insurance, into a unified, personalised, and self-correcting service chain. The analysis determines that Agentic AI represents a fundamental change in the design of intelligent systems, going beyond the linear processing typical of traditional chatbots. The key conclusion is that Agentic AI serves as an integral element of the management subsystem, capable of implementing the full cycle of classic management functions, such as strategic planning, dynamic organisation through orchestration, and iterative control through feedback loops. The study concludes that Agentic Artificial Intelligence is defined not simply as a technological upgrade, but as a new paradigm of digital management integrated into the complex socio-economic processes of the global tourism industry, marking a transition from auxiliary service tools to autonomous digital workers.
How to Cite
##plugins.themes.bootstrap3.article.details##
agentic artificial intelligence, intelligent assistants, digital transformation, tourism, orchestration of multi-agent systems, Action Research
Abou Ali, M., Dornaika, F., & Charafeddine, J. (2025). Agentic AI: A comprehensive survey of architectures, applications, and future directions. Artificial Intelligence Review, 59(1). https://doi.org/10.1007/s10462-025-11422-4
Acharya, D. B., Kuppan, K., & Divya, B. (2025). Agentic AI: Autonomous intelligence for complex goals – A comprehensive survey. IEEE Access, 1. https://doi.org/10.1109/access.2025.3532853
Agency. (2026). In Cambridge Dictionary. https://dictionary.cambridge.org/uk/dictionary/english/agency
AiNews UA. (2025). Mindtrip AI – trevel-platforma na bazi ShI [Mindtrip AI – AI-based travel platform]. https://ainews.com.ua/ai/mindtrip-ai-trevel-platforma-na-bazi-shi/
Ali, F., & Ali, L. (2025). Agentic AI in hospitality and tourism: Opportunities, risks, and research pathways. Journal of Travel Research. https://doi.org/10.1177/00472875251392915
Ambr AI. (2025). How Skyscanner’s Ambr AI pilot led to global roll out [Case study]. https://www.ambr.ai/case-studies/skyscanner-cs
AP News. (2025, January). What does ‘agentic’ AI mean? Tech’s newest buzzword is a mix of marketing fluff and real promise. https://apnews.com/article/518d6ae159d1f4d3343e98a456cb5221
Arunkumar, S. (2025). A systematic literature review on agentic AI insights in hospitality industry. International Journal of Research & Technology, 13(S4), 459–474. https://ijrt.org/j/article/view/798
Bandi, A., et al. (2025). The rise of agentic AI: A review of definitions, frameworks, architectures, applications, evaluation metrics, and challenges. Future Internet, 17(9), 404. https://doi.org/10.3390/fi17090404
Bandi, A., Kongari, B., Naguru, R., Pasnoor, S., & Vilipala, S. V. (2025). The rise of agentic AI: A review of definitions, frameworks, architectures, applications, evaluation metrics, and challenges. Future Internet, 17(9), 404. https://www.mdpi.com/1999-5903/17/9/404
Botti, V. (2025). Agentic AI and multiagentic: Are we reinventing the wheel? arXiv. https://arxiv.org/abs/2506.01463
Data Appeal. (2025). The 7 travel tech trends that will matter in 2026. https://datappeal.io/the-7-travel-tech-trends-that-will-matter-in-2026/
Diadiuk, I. Y., & Levchenko, L. V. (2025). Action research: Metodolohiia dlia praktychnoho vplyvu [Action research: Methodology for practical impact]. Zhytomyr Polytechnic State University. https://learn.ztu.edu.ua/mod/resource/view.php?id=220623
Dwivedi, Y. K., et al. (2025). Artificial intelligence agents and agentic systems in hospitality and tourism: Challenges, opportunities and research agenda. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-02-2025-0287
Ekstrom, S. (2025). AI for sustainable and responsible tourism: Insights from AI governance and ethics. Learn Tourism. https://blog.learntourism.org/ai-for-sustainable-and-responsible-tourism-insights-from-ai-governance-and-ethics
Grand View Research, Inc. (2025). AI in tourism market size & share. Industry report, 2030. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-tourism-market-report
IBM. (2025). What is agentic AI? https://www.ibm.com/think/topics/agentic-ai
Ilieva, G., Yankova, T., & Klisarova-Belcheva, S. (2024). Effects of generative AI in tourism industry. Information, 15(11), 671. https://doi.org/10.3390/info15110671
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
McKinsey. (2025). Seizing the agentic AI advantage. QuantumBlack. https://www.mckinsey.com/capabilities/quantumblack/our-insights/seizing-the-agentic-ai-advantage
Milton, T. (2023). Artificial intelligence in tourism: A review of trends, opportunities and challenges. International Journal for Multidimensional Research Perspectives, 1(2).
Muver, V. (2026). Arkhitektura vzaiemodii spetsializovanykh AI-ahentiv dlia vykonannia dovhotryvalykh avtonomnykh zadach [Architecture of interaction of specialized AI agents for performing long-term autonomous tasks]. DOU. https://dou.ua/forums/topic/57492/
Nisa, U., et al. (2025). Agentic AI: The age of reasoning – A review. Journal of Artificial Intelligence. https://doi.org/10.1016/j.jai.2025.08.003
OECD. (2024). Artificial intelligence and tourism: G7/ OECD policy paper (OECD Tourism Papers, No. 2024/02). OECD Publishing. http://dx.doi.org/10.1787/3f9a4d8d-en
Orq.ai. (2025). Langchain vs CrewAI: Comparative framework analysis. https://orq.ai/blog/langchain-vs-crewai
Ovsiienko, S. (2025). Agentic AI ta liudyna: praktychnyi plan perekhodu do Hibrydnykh Tsilei Rozvytku [Agentic AI and humans: A practical plan for the transition to Hybrid Development Goals]. SPEKA. https://speka.ua/artificial-intelligence/gibridni-cili-rozvitku-yak-si-zminit-dosyagnennya-globalnix-cilei-vm42x3
Petkov, P. (2024). The effects of artificial intelligence on tourism industry. UTMS Journal of Economics, 15(2), 218–228.
Prashant, D. S. (2025). Agentic AI: A quantitative analysis of performance and applications. Journal of Advances in Artificial Intelligence, 3(2), 132–140. https://doi.org/10.18178/jaai.2025.3.2.132-140
Sagor, R. (2011). The action research guidebook: A four-stage process for educators and school teams (2nd ed.). Corwin.
TechRadar. (2025). Garbage in, agentic out: Why data and document quality is critical to autonomous AI’s success. https://www.techradar.com/pro/garbage-in-agentic-out-why-data-and-document-quality-is-critical-to-autonomous-ais-success
Tussyadiah, I., & Miller, G. (2019). Perceived impacts of artificial intelligence and responses to positive behaviour change intervention. Tourism Management, 70, 297–305.
Verkalets, I. (2025). AI agents and the future of online travel agencies. COAX Software. https://coaxsoft.com/blog/ai-agents-and-the-future-of-online-travel-agencies
Wang, L., et al. (2025). Large Action Models: From inception to implementation. Transactions on Machine Learning Research. https://doi.org/10.48550/arXiv.2412.10047
Wang, S., et al. (2025). Artificial intelligence in tourism: A systematic literature review and future research agenda. Sustainability, 17(20), 9080. https://www.mdpi.com/2071-1050/17/20/9080
This work is licensed under a Creative Commons Attribution 4.0 International License.