South Asian Journal of Social Studies and Economics

The hospitality industry sits at an uneasy junction in the global sustainability agenda. It generates substantial environmental and social costs through energy use, water consumption, food waste and labour-intensive operations, yet its economic model depends on continued growth in guest volume and service intensity. Artificial intelligence (AI) has emerged as a technology capable of easing this tension, by optimising resource consumption, forecasting demand, personalising guest experience and reshaping employment structures. This review synthesises published evidence on how AI applications are reshaping environmental, social and economic dimensions of sustainability within hotels, restaurants and tourism destinations. Drawing on a structured narrative search of peer-reviewed literature, the review organises findings around four themes: environmental resource management, workforce and social equity, revenue and demand management, and generative AI in guest-facing and destination-level contexts. The evidence shows that AI delivers measurable efficiency gains in energy, water and food-waste management, and that predictive and generative tools are increasingly woven into destination-level sustainability planning. At the same time, the literature points to persistent tensions around job displacement, algorithmic fairness, data governance and the energy footprint of AI infrastructure itself. The review concludes that AI's contribution to hospitality sustainability is conditional rather than automatic, resting on organisational readiness, workforce reskilling and regulatory oversight. Future work should prioritise longitudinal, cross-cultural evidence and closer scrutiny of the environmental cost of AI systems themselves.