Abstract
Artificial Intelligence (AI) functionalities have helped improve the working lives of the human population in sectors like the health sector, education sector, industries and tourism. Emerging economies, in particular, have been exploring the potential of AI to transform their tourism and hospitality sectors. This research paper aimed to examine the use of pre-trained AI models in the tourism and hospitality industries in emerging economies. The study presented a literature review of the current state of AI in the tourism and hospitality industries, including its opportunities and challenges. It then proposed the use of a pre-trained AI model, specifically the Bidirectional Encoder Representations from Transformers (BERT) model, to help address some of the challenges facing the tourism and hospitality sectors in emerging economies. BERT is a language model that can be fine-tuned for a range of natural language processing (NLP) tasks such as sentiment analysis, entity recognition and text classification. The paper discussed the potential applications of BERT in the tourism and hospitality sectors, such as analysing customer feedback, enhancing chatbot interactions and improving search engine optimization (SEO) for tourism websites. The Recall-Oriented Understudy for Gisting Evaluation (ROUGE) was used to evaluate the accuracy of the chatbot model that was used in this study. In conclusion, this research paper suggested that pre-trained AI models, such as BERT, can offer valuable insights and solutions in improving customer satisfaction in the tourism and hospitality industries in emerging economies.