Vatankhah, S.Bamshad, V.Arici, H.E.Duan, Y.Q.2024-06-082024-06-082024.01.010264-2069https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=dspace_ku&SrcAuth=WosAPI&KeyUT=WOS:001236028200001&DestLinkType=FullRecord&DestApp=WOS_CPLhttps://hdl.handle.net/20.500.12597/33240This study employs a systematic literature review (SLR) combined with bibliometric analysis to investigate the ethical implementation of Artificial Intelligence (AI) in the service industries. This research uncovers key challenges such as privacy, bias, transparency, and accountability, emphasizing the critical need for ethical AI practices in service sectors handling sensitive customer data. Findings reveal that AI's ethical implementation is crucial in areas like decision support, customer engagement, automation, and new service development. The analysis provides actionable insights into enablers, including ethical guidelines, human oversight, comprehensive training, and adaptive organizational culture, which are essential for unlocking AI's potential and mitigating risks. The study offers a roadmap for future research, advocating interdisciplinary collaboration, customer co-creation in ethical frameworks, and sector-specific policy adaptation, ultimately aiming to build responsible and trustworthy AI in the service industries.eninfo:eu-repo/semantics/openAccessArtificial intelligenceethicsdata privacytransparencyresponsible AIArticle10.1080/02642069.2024.23590770012360282000011743-9507