This study addresses the complexities of adopting machine learning (ML) technologies across various industry sectors, despite their recognized benefits. It aims to conduct a bibliometric review of ML adoption, providing an in-depth analysis of how ML technologies have been developed and integrated across different fields. Employing bibliometric analysis with VOSviewer v.1.6.20 software and the Web of Science (WoS) database, this study explores trends in ML adoption. The implications of this research are significant, impacting both academic research and industry practices. Academically, it enriches the literature on ML by highlighting key works, trends, and gaps that could steer future research directions. For industry professionals, the study provides insights into effective ML adoption strategies and underscores the challenges that need addressing to fully leverage ML technologies.