Generative artificial intelligence for inclusive research

Purpose This paper aims to critically examine how generative artificial intelligence (GAI) may reshape inclusive research practices within hospitality and tourism, a field where methodological diversity, cross-cultural knowledge and marginalised stakeholder perspectives are central to scholarly inquiry. This study addresses a gap in tourism and hospitality scholarship, where the implications of GAI for inclusive and equitable knowledge production remain insufficiently theorised. Design/methodology/approach Adopting a critical conceptual approach, this paper integrates hospitality and tourism epistemologies with emerging AI ethics research. It synthesises interdisciplinary literature and draws on illustrative vignettes from hospitality- and tourism-related qualitative projects using AI-assisted analysis to develop a field-specific framework for inclusive GAI use. Research norms unless critically managed. Findings GAI presents meaningful opportunities for inclusion in hospitality and tourism research − such as reducing linguistic barriers for Global South scholars, supporting accessibility in data collection and enabling broader collaborative participation. However, its integration also introduces risks related to epistemic bias, cultural misrepresentation and the reinforcement of dominant Western research norms unless critically managed. Research limitations/implications The framework offers field-specific guidance for hospitality and tourism researchers integrating GAI into inclusive methodologies. For practitioners, it supports participatory destination planning and multilingual community engagement. For journals and institutions, it highlights the need for context-sensitive AI disclosure policies that reflect the socio-cultural complexity of hospitality and tourism research. Originality/value To the best of the authors’ knowledge, this paper is the first to develop a hospitality- and tourism-specific framework for critical GAI literacy aimed at enhancing inclusive research design, analysis and dissemination. It advances conceptual discussions by positioning GAI not merely as a technical tool but as a socio-technical force that may transform knowledge production within the field.