TY - JOUR
T1 - Exploring How Artificial Intelligence (AI) Can Enable Sustainability in the Hospitality Industry
AU - Filimonau, Viachaslau
AU - Ashton, Mark
AU - Derqui, Belen
AU - Hernandez-Maskivker, Gilda
N1 - Publisher Copyright:
© 2025 The Author(s). Sustainable Development published by ERP Environment and John Wiley & Sons Ltd.
PY - 2025/8/9
Y1 - 2025/8/9
N2 - The hospitality industry, encompassing operations from hotels and resorts to restaurants and event venues, faces increasing pressure to integrate sustainability into its core business practices. The rapid proliferation of artificial intelligence (AI) offers potential to make the industry more sustainable, but this potential remains empirically underexplored. This study bridges this knowledge gap by introducing the convergence innovation framework, a concept defining the fusion of distinct domains to create novel solutions, to examine the integration of AI within hospitality operations for enhanced sustainability across environmental, social, and economic dimensions. Through semi-structured interviews with 35 senior industry professionals in the United Kingdom and Spain, the study reveals that, beyond well-known efficiency gains, AI can mitigate environmental impact through proactive optimisation of energy and water consumption, dynamic waste minimisation systems, and intelligent building management that adapts to real-time conditions. AI can improve social sustainability by personalising guest experiences tailored to eco-friendly preferences and enhancing staff well-being through optimised operational tasks. Economically, AI holds opportunities for precision in supply chain management and demand forecasting, leading to waste reduction and cost savings. These findings offer empirically grounded insights for hospitality organisations to strategically capitalise on the convergence of AI and sustainability, promoting resilience and competitive advantage in a rapidly evolving hospitality market.
AB - The hospitality industry, encompassing operations from hotels and resorts to restaurants and event venues, faces increasing pressure to integrate sustainability into its core business practices. The rapid proliferation of artificial intelligence (AI) offers potential to make the industry more sustainable, but this potential remains empirically underexplored. This study bridges this knowledge gap by introducing the convergence innovation framework, a concept defining the fusion of distinct domains to create novel solutions, to examine the integration of AI within hospitality operations for enhanced sustainability across environmental, social, and economic dimensions. Through semi-structured interviews with 35 senior industry professionals in the United Kingdom and Spain, the study reveals that, beyond well-known efficiency gains, AI can mitigate environmental impact through proactive optimisation of energy and water consumption, dynamic waste minimisation systems, and intelligent building management that adapts to real-time conditions. AI can improve social sustainability by personalising guest experiences tailored to eco-friendly preferences and enhancing staff well-being through optimised operational tasks. Economically, AI holds opportunities for precision in supply chain management and demand forecasting, leading to waste reduction and cost savings. These findings offer empirically grounded insights for hospitality organisations to strategically capitalise on the convergence of AI and sustainability, promoting resilience and competitive advantage in a rapidly evolving hospitality market.
KW - artificial intelligence
KW - business ecosystem
KW - convergence
KW - organisational innovation
KW - sustainability
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_univeritat_ramon_llull&SrcAuth=WosAPI&KeyUT=WOS:001546183800001&DestLinkType=FullRecord&DestApp=WOS_CPL
UR - https://www.scopus.com/pages/publications/105012894231
U2 - 10.1002/sd.70146
DO - 10.1002/sd.70146
M3 - Article
SN - 0968-0802
JO - Sustainable Development
JF - Sustainable Development
ER -