Consumer adoption of agentic-AI in hospitality: A mixed-method study on its facilitators and inhibitors
Rajasshrie Pillai, Brijesh Sivathanu, Nripendra Pratap Rana, Robin Nunkoo, Meehee Cho · International Journal of Hospitality Management · 2026
This study investigates the enablers and barriers influencing the acceptance of Agentic AI in the hospitality sector using a mixed-methods research design. In the first phase, thirty-two in-depth interviews were conducted with hospitality managers to identify the key drivers and barriers of Agentic AI adoption. Based on these insights, a theoretical model grounded in Behavioral Reasoning Theory (BRT) was developed and subsequently validated through a survey of 980 consumers. The findings reveal that autonomy, personalization, social influence, and perceived usefulness are the primary drivers of Agentic AI adoption, whereas technological anxiety, perceived privacy risk, perceived hallucination, and traditional barriers impede its acceptance. This study contributes to the literature on advanced technology adoption in hospitality by extending the application of BRT to the context of Agentic AI. It also offers practical insights for hospitality managers and technology developers seeking to design and implement Agentic AI solutions that effectively promote consumer adoption.