Transformative Role of Artificial Intelligence in the Hotel Industry of Jammu, Kashmir, and Ladakh Post Article 370: Opportunities and Challenges

This paper analyses the adoption of Artificial Intelligence (AI) in the hotel sector of Jammu, Kashmir, and Ladakh (JKL) using a synthesis of theoretical perspectives on the subject by combining the Technology Acceptance Model (TAM) and the Diffusion of Innovation (DOI) theory. Whereas AI-driven change in the hospitality sector has been a widely researched topic in urban and technologically developed markets, little has been done to examine adoption dynamics in geographically marginalized and infrastructure-sensitive tourism economies. The study uses qualitative secondary data research design in which it systematically synthesizes peer-reviewed literature, government reports, regional tourism statistics and policy documents. The results show that perceptions of usefulness expressed in terms of revenue optimization, efficiency, personalization, and predictive maintenance is a major influence on adoption intention. Such attributes of diffusion as relative advantage and observability that are owed to DOI promote diffusion further, especially in competitive tourism settings. Adoption is however regulated by structural factors such as infrastructural differences, SME dominance, skill limitations in the workforce and seasonality effects in tourism which increase perceived complexity and financial risk. The research extends the adoption theories of innovation by adding structural moderators to the TAM-DOI model and offers region-specific findings on digital transformation in the peripheral hospitality systems. The results can help AI-hospitality literature by providing a context-based theory-based account of the technological diffusion in developing tourist destinations.

Artificial Intelligence, Hospitality Industry, Technology Adoption, Innovation Diffusion

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