ENHANCING GUEST EXPERIENCE: LEVERAGING ARTIFICIAL INTELLIGENCE IN CUSTOMER RESERVATION

Abstract

Artificial Intelligence (AI) in hotel reservation systems is gaining attention for its potential to enhance customer experience, streamline repetitive processes, optimize pricing strategies, and deliver personalized offers. AI can analyze visitor data to provide tailored recommendations and adjust staffing, inventory, and pricing based on anticipated demand. These data-driven decisions can improve service quality and help hotels differentiate themselves from competitors. Additionally, AI reduces operational costs related to reservation management and customer support, enhances scalability during seasonal fluctuations, and encourages innovation aligned with current market trends. This study investigates hotel guests’ experiences with AI-powered reservation systems, utilizing surveys and interviews to assess effectiveness and identify areas for improvement. The study was conducted among guests aged 18 and above at Astrotel Novaliches, with a total of 50 participants selected through simple random sampling to ensure fairness and reduce bias. A researcher-developed questionnaire, validated by experts and formatted with a Likert scale, was used to gather data on guest profiles, AI usage, feedback, and suggestions. Ethical standards, including informed consent and data privacy, were strictly followed throughout the data collection process. The results revealed that most guests were aged 28 to 32 and preferred making reservations via voice calls. While many expressed trust in AI to handle their data, they were uncertain about its ability to predict their preferences. Furthermore, a significant number of respondents did not favor the use of chatbots. These findings suggest a mixed reception of AI in reservations, with users showing interest in convenience but also demonstrating a continued preference for human interaction. The findings indicate that although artificial intelligence enhances booking accuracy and personalization, challenges remain in the form of technical issues, privacy concerns, and limited trust in AI’s predictive capabilities. Guests continued to value human interaction, particularly in payment processing and preference-based services. The study recommends further refinement of AI systems, increased guest education on AI capabilities, and maintaining human support to strike a balance between automation and personal service.