The rapid proliferation of Generative Artificial Intelligence (GenAI) is fundamentally reshaping how tourists plan, experience, and reflect upon their travel activities. However, research on tourist trust in GenAI remains limited, particularly lacking an integrated and systematic theoretical framework. This paper pursues two objectives: (1) to critically synthesise foundational theories on trust, technology acceptance, and AI in tourism; and (2) to propose an integrated theoretical framework for studying tourist trust in GenAI, encompassing trust dimensions, multi-level antecedents, and multi-dimensional behavioural outcomes. The framework is grounded in three core theoretical pillars: the integrative trust model (Mayer et al., 1995), the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2012), and the theory of human trust in AI (Glikson & Woolley, 2020). The proposed framework extends existing models by incorporating two GenAI-specific dimensions - perceived algorithmic transparency and perceived data security - into the trust construct, while identifying three antecedent groups and four behavioural outcome categories with clear theoretical foundations. The paper concludes with a discussion of theoretical contributions, implications for empirical research, and directions for future investigation.