Over the past decade, diversity in organizations has become a central theme of management practice and research. Given the importance of the top management team (TMT) for firms, management scholars have increasingly examined the role of diversity for TMTs by shedding light on its antecedents, contingencies, and consequences. These endeavors have led to a meander of studies published in academic journals. As diversity grows and becomes ever more important in all parts of an organization, it is important to take stock of current research and navigate the meander to identify current conceptual gaps and pave theoretical pathways forward. In this study, we combine a literature review with a machine learning approach, i.e., topic modeling, to structure the research landscape of diversity in TMTs. For our topic modeling, we analyzed the text of 1,454 articles published in peer-review journals between the years 2010 and 2021. Our findings provide an overview of the research landscape of diversity in TMTs and its 19 topics, and carve out four communities of topics – i.e., (1) TMT characteristics, (2) TMT responsibilities, (3) dimensions of diversity, and (4) quantitative empirical research. By combining a qualitative and a quantitative literature review, this study contributes to the literature about diversity in TMTs by identifying current research streams and underrepresented topics, and providing directions for future research.