Amid growing global and local environmental challenges, organizations are increasingly required to strengthen employees’ green literacy—knowledge, attitudes, and practices that enable sustainable decision-making in the workplace. This study explores the potential of an Artificial Intelligence (AI)-based training strategy to enhance employee green literacy within organizational settings in Makassar, Indonesia. Guided by a qualitative research design, the study employed semi-structured interviews, focus group discussions, and participant observation with employees, managers, and training practitioners across diverse sectors, including hospitality, manufacturing, and services. Thematic analysis was applied to interpret participants’ experiences and uncover patterns of meaning. Findings reveal that AI features such as personalization, real-time feedback, and flexible accessibility significantly foster employee engagement by increasing trust, motivation, and perceived relevance of training. Employees valued the integration of local examples, which not only enhanced contextual learning but also reflected Makassar’s socio-cultural realities. Sectoral differences further highlighted the need for industry-specific adaptations, with hospitality workers emphasizing guest-facing sustainability practices, while manufacturing employees focused on operational efficiency and waste reduction. Importantly, the study demonstrates that AI-based training contributed not only to individual knowledge gains but also to collective workplace sustainability culture through shared initiatives and values. This research underscores the dual role of AI as both a technological enabler and a catalyst for cultural transformation when combined with ethical oversight and human facilitation. For organizations and policymakers in Makassar, the findings highlight the potential of AI-driven training to align workforce development with broader green city strategies, fostering resilient, ecologically responsible, and future-ready communities.
                        
                        
                        
                        
                            
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