Context-Aware Conversational AI for Intelligent Travel Planning and Smart Tourism
Keywords:
Conversational AI, Intelligent travel planning, Large language models (LLMs), Natural Language Processing (NLP), Recommendation systems, Retrieval-augmented generation, Smart tourismAbstract
Artificial Intelligence (AI) has significantly transformed smart tourism by enabling intelligent, personalised, and context-aware travel planning. Recent advancements in Natural Language Processing (NLP), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and recommendation systems have enhanced conversational travel assistants by supporting itinerary generation, destination recommendation, and real-time decision-making. This article reviews recent developments in context-aware conversational AI for intelligent travel planning and smart tourism. Existing approaches are analysed based on recommendation techniques, conversational capabilities, contextual awareness, and personalisation. The review also examines key challenges, including data sparsity, limited real-time adaptability, multilingual interaction, privacy and security concerns, and the fragmentation of tourism-related services. Furthermore, emerging technologies such as multimodal AI, agentic AI, and knowledge-enhanced recommendation systems are explored as promising approaches for developing more adaptive and intelligent tourism applications. The study highlights significant research gaps in current conversational travel systems, particularly in maintaining continuous context, integrating diverse real-time data sources, and providing reliable personalised recommendations. Overall, the review emphasizes the potential of context-aware conversational AI to create scalable, adaptive, and user-centric travel-planning systems that can improve decision-making and enhance the overall tourist experience.
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