I can’t travel without ChatGPT: Trends, insights, and future research directions of Gen AI in travel planning

Generative artificial intelligence (Gen AI), particularly ChatGPT, is fundamentally reshaping travel planning in tourism and hospitality. Despite rapid adoption, scholarly understanding remains fragmented and theoretically constrained. This study provides the first systematic review dedicated exclusively to Gen AI in travel planning. Using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) and PRISMA protocols, 39 empirical studies were critically analyzed through the (theory-context-characteristics-method) TCCM framework to synthesize theoretical foundations, methodological approaches, principal findings, and research gaps. The review confirms that Gen AI enhances personalization, multilingual interaction, and decision efficiency, while significantly influencing traveler cognition, preferences, and behavioral intentions. Trust, privacy, and perceived usefulness emerge as central mediating mechanisms within dominant frameworks such as technology acceptance model (TAM) and theory of planned behavior (TPB). However, the literature remains heavily anchored in cognitive-utilitarian paradigms, with limited integration of affective, relational, resistance-based, and socio-technical perspectives. To advance theoretical development, this study proposes an integrated conceptual framework that reconceptualizes Gen AI adoption as a multidimensional, ecosystem-embedded process. By bridging fragmented theoretical streams and identifying underexplored linkages, the review establishes a stronger platform for cumulative scholarship. The study also outlines governance and design imperatives to support calibrated trust and sustainable value creation in AI-enabled travel planning.