The past ten years have been exceptionally dynamic, as the abundance of information and advances in technology have fundamentally transformed both the tourism industry and tourism research. Social media has emerged as a key source of information about travel, while the rise of data science and cutting-edge machine learning models has led to the development of tools that offer unprecedented opportunities for businesses and researchers. Sentiment analysis is a powerful technique that extracts subjective information and emotions from customer-generated text. When done properly, it provides valuable insights into customer opinions. However, sentiment analysis often requires processing large volumes of data, something that can only be achieved with machine assistance. Modern artificial intelligence represents the most advanced application of machines to tasks that would be challenging or even impossible for humans. Today’s artificial intelligence relies on sophisticated models of artificial neural networks capable of handling vast amounts of data. With an appropriate human input, these neural networks can perform sentiment analysis more ef ectively than any other method. The purpose of this paper is to briefly describe how modern advanced models of artificial intelligence can be applied to sentiment analysis in tourism and to address the question of whether modern artificial neural networks, i.e. large language models, are indeed the most suitable methods for implementing sentiment analysis in this field.