Abstract
Purpose
This systematic literature review identifies, analyzes, and synthesizes research on customer value creation and artificial intelligence (AI) in tourism and hospitality (T&H), and, based on this synthesis, develops an integrative framework clarifying how AI shapes value creation and co-creation.
Design/methodology/approach
An advanced query containing 65 keywords yielded 123 records from Web of Science and 252 records from Scopus for publications dated 2001 to February 2025. Using bibliometric techniques and systematic review procedures, we examined authorship, outlets, citations, keywords, theories, countries, and methods.
Findings
The network analysis produced six clusters: AI, value co-creation, machine learning, service robots, customer-perceived value, and deep learning. Publication trends show rapid post-2020 uptake of AI in T&H. The framework maps AI design features to value mechanisms (functional, hedonic, social, emotional, epistemic and economic) and to attitudes, intentions, use behavior, and performance outcomes, and identifies AI-related moderators (e.g. literacy, privacy salience, algorithm aversion, self-efficacy and anthropomorphism sensitivity).
Research limitations/implications
The study highlights the need for methodological variety and offers scholars avenues for future research.
Practical implications
For practitioners, results provide a roadmap for adopting AI to enhance experience and efficiency while addressing key concerns such as personalization, privacy, and service integration. The framework also serves as a diagnostic tool to prioritize AI investments by tracing how design choices activate customer value and translate into use and outcomes.
Originality/value
The review combines bibliometrics with a systematic review structured by the Theory–Context–Characteristic–Methodology (TCCM) perspective, introducing a framework that renders AI’srole in value creation explicit.