The way that humans and machines engage has changed significantly, particularly when it comes to cooperating and working together to accomplish goals in an organizational context. As a result, “human-machine teams” were created, found in both service-intensive sectors, where workers are coupled with chatbots and artificial intelligence (AI) tools and manufacturing, performing assembly and disassembly work. Inspired by the emergence of these new work teams and the surrounding opportunities and problems, this book chapter’s aim is to synthesize and analyze the literature by identifying publication trends, hotspots, themes, most impactful voices, and contexts, as well as a future research agenda on human-machine teams. The book chapter is grounded in a multi-technique bibliometric analysis, based on Scopus-retrieved data, following the rigorous PRISMA guidelines. It was found that machine learning systems and trust are the most frequently occurring keywords, while 2022 saw the highest number of publications. The results also have important implications for practitioners and managers who are showing an increasing interest in integrating human-machine teams into organizational structures, as well as the scientific community, which will continue to explore this area in the future.