Purpose: AI functions as a sophisticated instrument that enhances the development of green human resource management (GHRM) and management procedures. This research examines how AI and green transformational leadership influence GHRM, the promotion of a green innovation culture, and the adoption of low-carbon behavior in the hospitality sector. Design/methodology/approach: This investigation applies a partial least squares structural equation modeling method to deepen the insights into the impact of AI and green transformational leadership on GHRM, green innovation culture, and low-carbon behavior. The authors conducted an anonymous survey with 35 items, targeting 569 participants from various hotels in Vietnam. Findings: The outcomes imply that AI has a complex role, favorably impacting the culture of green innovation and promoting low-carbon behavior, with green transformational leadership and GHRM serving as intermediaries within the hotel industry. Practical implications: AI facilitates GHRM, consequently improving green transformational leadership by addressing environmental concerns and implementing green practices in Vietnamese hotels. Therefore, the incorporation of AI into the low-carbon behavior practices will motivate employees to take part in environmental preservation and sustainable progress in the field of the hospitality industry. Originality/value: The study concludes that the cultural benefits associated with green innovation and low-carbon behavior, which arise from AI, are predominantly implemented through effective leadership in green transformation and GHRM within the hospitality industry. This research broadens the use of the resource-based view and ability–motivation–opportunity theory in the context of green operations. Additionally, it offers a strategic framework for fostering a culture of green innovation and low-carbon behavior in hotels.

AI serves as a smart and efficient instrument for advancing green human resource management (GHRM) and enhancing operational efficiency. This dual advantage fosters green employee behavior and supports green finance (GF), thereby striving for sustainable performance within the hospitality sector. This paper investigates the influence of AI and GHRM on employee green behavior (EGB), GF, and the sustainable performance (SP) of hotels. A PLS-SEM model is employed to deepen the understanding of how AI and GHRM affect EGB, GF, and SP. A survey conducted anonymously included 39 questions and was distributed to 915 participants from different hotels in Vietnam. The results of the study indicate that AI positively influences GF and SP, with GHRM and EGB acting as mediating factors. As a result, the research underscores the important and significant function of AI as a driving force for both GHRM and GF. A crucial insight from the study is that the advantages linked to GF and SP that stem from AI are mainly achieved through GHRM and EGB, which are vital for promoting SP within the hospitality sector.

AI plays a pivotal role in facilitating green servant leadership and green human resource management by enabling data-driven decision-making, optimizing resource allocation, and fostering a culture of sustainability. This study investigates the effects of AI and green servant leadership on green human resource management, employee green innovation behaviors, and hotels' environmental performance. PLS-SEM was employed to examine AI's effects on environmental performance and the relationships among green servant leadership, green human resource management, and employee green innovation behaviors. An anonymous questionnaire comprising 35 items was administered to 923 managers and employees from hotels across Vietnam. Findings from the standardized model reveal that AI exerts the most significant influence on green service leadership (β = 0.579). Additionally, AI positively influences green human resource management and employee green innovation behaviors, with green servant leadership acting as a mediator. Furthermore, AI enhances environmental performance through the sequential mediating roles of green servant leadership and employee green innovation behaviors. This study provides valuable insights into integrating AI with green servant leadership to enhance green human resource management, foster employee green innovation behaviors, and improve environmental performance in hotels. This study extends the Resource-Based View (RBV) and Social Learning Theory (SLT) by integrating both perspectives into a unified research framework. The findings provide practical guidance for hotels to optimize resource utilization, promote environmentally sustainable practices, and improve environmental performance, thereby supporting long-term sustainable development.

This study investigates the influence of AI and digital innovation on green product innovation, low-carbon behavior, and sustainable performance within small and medium-sized enterprise. Drawing on a mediation framework, it examines the mediating role of digital innovation between AI and green product innovation, and the mediating effect of green product innovation linking AI with low-carbon behavior and sustainable performance. The study further explores the sequential mediation of digital innovation and green product innovation. Using partial least squares structural equation modeling (PLS-SEM), data were collected from 1,336 respondents representing SMEs in developing economies. The results indicate that AI significantly and positively affects digital innovation and green product innovation. Digital innovation acts as a key mechanism through which AI strengthens green product innovation, while green product innovation mediates the effects of AI on low-carbon behavior and sustainable performance. These findings highlight the strategic value of AI-enabled digital innovation in advancing environmental sustainability. The study offers theoretical and practical implications for managers and policymakers, showing how SMEs can leverage AI and digital innovation to foster innovation and sustainable performance.

Purpose AI functions as a strategic tool to advance green human resource management (GHRM) and boost operational efficiency. This paper examines the impact of AI and GHRM on corporate social responsibility (CSR), low-carbon behavior (LCB), and the financial performance (FP) of hotels. Design/methodology/approach The study utilized a PLS-SEM model to examine the impact of AI and GHRM on LCB, employee performance, and financial efficiency. An anonymous survey consisting of 32 questions was conducted with 882 participants from various hotels in Vietnam. Findings Three measurement items (GHRM4, LCB4, and LCB6) were eliminated because of insufficient external loading coefficients. The standardized model indicated that AI exerts a considerable impact on GHRM (β = 0.632) and CSR. AI influences FP through the mediating roles of GHRM and LCB. Furthermore, LCB positively contributes to the effect of GHRM on FP. Originality/value The research provided significant insights regarding the role of integrating AI with GHRM as a crucial element in assisting hotels to bolster their CSR, encourage LCB, and enhance their FP. Subsequently, it is essential to further elaborate and integrate AMO theory alongside social responsibility theory. Hotels will refine their resource utilization to foster green initiatives among staff, aiming to lower operational expenses, minimize waste, and strengthen their sustainable competitive edge within the framework of digital and ecological transformation.