From Reception to Recognition: Post-COVID AI-Augmented Front Desk Operations and the Reconfiguration of Guest Experience
Chandramauli Dhaundiyal, Rekha Gupta · International Journal of Science and Research (IJSR) · 2025
The COVID-19 pandemic has catalyzed transformative shifts in front desk operations across the global hospitality industry. This paper investigates how AI-augmented systems-such as facial recognition, voice-assisted check-ins, and predictive service bots-have reconfigured the hotel guest experience in the post-pandemic era in India. Grounded in the Technology Acceptance Model (TAM) and supported by Parasuraman's SERVQUAL framework, this study proposes an integrated conceptual model that explores guest perceptions of AI's usefulness, ease of use, service quality, and trust. Using a dataset collected from 120 guests and 30 front desk employees in mid-scale Indian hotels, the paper analyzes attitudes toward AI-based systems post-COVID. Mixed-method analysis was conducted using descriptive statistics and thematic coding of interviews. The findings suggest a paradox: while AI enhances efficiency and reduces contact, it potentially undermines emotional warmth-a long-standing hallmark of hospitality. This tension leads to the concept of the