In this paper the utilisation of neural networks is examined, focusing on an electronic tourist information query system as an example. The analysis begins with a review of the fundamental principles underlying the operation of neural networks, their distinctions from traditional programming, and the reasons they can be beneficial in such systems. Additionally, the work of OpenAI and their development of ChatGPT are considered, illustrating the potential applications of neural networks in real-world scenarios. The paper compares the capabilities of neural networks with dynamic parameter sets against hardcoded logic. An analysis of the impact of these approaches on the speed of system development and the number of possible parameter combinations is conducted. The study also describes the implementation of neural networks on the Node.js platform, demonstrating the practical aspects of this approach, and analysing specific examples of responses and reactions to unforeseen queries for which programming a response is unfeasible. The study includes an analysis of existing query systems and the development and implementation of a prototype system. Moreover, the paper encompasses a comparative analysis of experiment results. The findings corroborate the advantages of neural networks over traditional hardcoded logic, contributing to the enhancement of tourist services in the digital age.