ARTIFICIAL INTELLIGENCE IN HOSPITALITY EDUCATION: A MULTI-INSTITUTIONAL ANALYSIS OF STUDENT’S AWARENESS, PERCEPTIONS AND PERCEIVED USEFULNESS IN INDIA

Rajesh Sathiamoorthy; Ankita Sakhuja Sharma

doi:10.29121/shodhkosh.v7.i10s.2026.8180

Authors

Rajesh Sathiamoorthy Faculty of Hospitality Management and Catering Technology, MS Ramaiah University of Applied Sciences, Bengaluru 560054, Karnataka, India
Ankita Sakhuja Sharma Faculty of Hospitality Management and Catering Technology, MS Ramaiah University of Applied Sciences, Bengaluru 560054, Karnataka, India

DOI:

https://doi.org/10.29121/shodhkosh.v7.i10s.2026.8180

Keywords:

Artificial Intelligence (AI), Hospitality Education, Career Readiness, Student Perception

Abstract [English]

The rapidly evolving landscape of Artificial Intelligence (AI) technology integration in the hospitality industry affects service delivery, operational efficiency, and future decision-making. On the contrary, the current pedagogical approach, especially in emerging countries, creates challenges for students as they adapt to an AI-dominated workplace. Therefore, this study explores the awareness, perceptions, and usefulness of AI among hospitality students in relation to their career readiness for an AI-powered workplace. A quantitative cross-sectional survey was adopted using a structured questionnaire on a sample of 489 hospitality students enrolled in 16 institutes across eight states in India. The data were collected by administering an instrument with five-point Likert-scale items assessing students' awareness, perceptions, and perceived usefulness of AI. Data were statistically analyzed using descriptive statistics, and reliability analysis was assessed through Cronbach’s alpha test. The outcomes demonstrated moderate to high level awareness (Mean ≈3.8 ±1.2) which signifies discourse knowledge related Chatbot, Robotics and Predictive Analysis application of AI tools by the students’ sample group also revealed perceptively positive view on AI (Mean ≈3.9 ±1.1), increased quality services and operational consideration though subtly being concern about job displacement rather than other responded areas perceived usefulness revealed higher marks (Mean ≈4.05 ±1.1), specifically Career Progression as well as for Acquisition Reliability analysis shows Cronbach alpha value as 0.979 indicate the acceptable range to get overall overview on use of Artificial intelligence in Enterprise. However, this paper argues that good norms or intuitive trends within the socioeconomic gap transition for development, between behavioural predispositions about the rapid advancement of science and practice, and educational and theoretical aspects, flanking the demographic generational curve, are resourcefully viable, given the apparent relationship between individual maturational situational variables and institutions.

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