Generative artificial intelligence as a catalyst for employee happiness and sustainable performance in green hotel management

Purpose This study aims to empirically examine the impact of generative artificial intelligence (GAI) on employee happiness within green hotel environments in Spain. By analyzing 221 eco-hotels, it explores how GAI influences the awareness of key sustainability indicators, environmental performance, process management, and sustainability – and how these, in turn, affect employee happiness. Employee happiness is directly related to occupational well-being and job satisfaction, fostering greater motivation, lower turnover and improved service quality. The study explores how advanced technologies foster sustainable, competitive and human-centered workplaces in hospitality, addressing gaps in happiness management research. Design/methodology/approach This study uses a mixed-method approach combining focus group insights and PLS-SEM analysis of 221 Spanish Ecostars-certified green hotels, examining how generative AI impacts employee happiness, environmental performance, management processes and sustainability, providing a novel framework for Industry 5.0 competitiveness. Findings The study confirms that generative AI positively influences employee happiness in green hotels by enhancing process efficiency, sustainability and environmental awareness. GAI improves management processes (61.6% variance), supports sustainable practices and enables fulfilling work. Environmentally driven performance significantly increases happiness, validating GAI and sustainability as key predictors for a competitive, responsible tourism sector. Originality/value This first EU study links generative AI to employee happiness in Spain’s green hospitality sector, validating a PLS-SEM model that shows GAI fosters pro-environmental behavior, operational efficiency and well-being, challenging the view of AI as purely job automation.