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Purpose: To examine the use of artificial intelligence in the tourism industry and evaluate its impact on operational efficiency and service quality in the context of smart tourism. Design/Methodology/Approach: The study combines an analysis of 32 tourism enterprises operating in the European market with a survey of 124 consumers conducted in 2024–2025. Artificial intelligence adoption was assessed through the level of operational process automation, and content analysis of enterprise reports and platform analytics was used to measure performance before and after implementation. Research Limitation: The study is limited to European tourism enterprises and a relatively small consumer sample. Future research should include broader geographical coverage and longitudinal analysis. Findings: Artificial intelligence significantly improved operational performance. Average service time decreased from 18.6 to 11.2 minutes, automation increased from 27.4% to 61.8%, and customer interaction intensity rose from 1.8 to 2.6 contacts per user. Consumers reported high satisfaction with service quality and personalisation, although trust in intelligent systems remained moderate, indicating that behavioural barriers still constrain the full benefits of AI adoption. Practical Implication: The findings support the adoption of hybrid service models that combine artificial intelligence with human interaction. Social Implication: Effective AI implementation can improve service accessibility, customer satisfaction, and the sustainable development of smart tourism. Originality/Value: The novelty lies in an integrated model linking the share of AI-automated processes with operational variables (service time, customer contacts) and consumer variables (service quality, personalisation, trust).
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Katyukha et al. (2026) studied this question.
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