Journal of Artificial Intelligence and Data Science

Öz

Machine learning is enabling transformative changes in the tourism industry. Various machine learning algorithms and models can detect patterns in huge amounts of data for the prediction process, recommendations, and decisions without any coding or programming. The tourism sector generates massive data through sources as such online reviews and ratings, social media activity, traffic information, and customer relationship management records. Machine learning is poised to unlock insights and opportunities from this data. This paper provides an overview of how machine learning is currently influencing and may shape the future of tourism. Techniques for predictive analytics, personalized recommendation systems, computer vision, natural language processing, and more are powering applications to improve customer experiences, optimize and automate operations, gain competitive advantage, and support sustainability. Current applications are discussed, including demand forecasting, personalized travel recommendations, automated photo filtering, sentiment analysis of tourism reviews, chatbots for customer service, and others. Emerging opportunities are explored, as machine learning may enhance smart tourism for destinations through intelligent transportation, customized experiences, optimized resource allocation, and improved accessibility. Challenges exist regarding data quality, privacy, bias, and job disruption. However, machine learning is expected to become an integral tool for data-driven, personalized, and sustainable tourism. Overall, this review paper aims to synthesize the state of machine learning in tourism by highlighting current applications, opportunities, considerations, and likely future trends. The conclusions point to machine learning as a catalyst for innovation in tourism that may significantly transform the visitor experience, business operations, and destination management in the years to come.