In today’s highly competitive educational environment, institutions face increasing pressure to enhance their global presence and competitiveness and the integration of artificial intelligence (AI) into educational processes shows significant potential in improving institutional performance and student satisfaction. One promising application is the use of chatbots to address students’ growing demand for instant responses and efficient support services. The study develops the basis of a Quality Function Deployment (QFD) framework tailored to a Higher Education Institution (HEI) AI chatbot. Data collection is conducted through special focus group discussions involving 267 students, organized into 59 sessions. To process and analyze the data, a multi-method approach is employed, incorporating content analysis to identify recurring themes, word cloud visualizations to assess attribute frequency, descriptive statistical methods to summarize key findings, and an importance-frequency mapping technique to highlight critical service quality dimensions and their prioritization. The findings pinpoint students’ primary expectations, emphasizing the importance of authenticity, reliability, broad knowledge, accuracy, up-to-dateness, understandability, speed, accessibility, security and data protection. The results provide a foundation for the strategic integration of AI in higher education and offer actionable insights for chatbot design aligned with student priorities.