Research on organizational structure witnessed a hiatus from the mid-1980s to the 2010s, primarily due to challenges in accessing comprehensive multi-firm structural data. We address this challenge by introducing a novel, hand-collected dataset of top management team compositions of S&P 500 firms between 1993 and 2020. Alongside providing the original role titles, we use generative Artificial Intelligence (AI) to categorize executives’ titles into six role groups and 12 hierarchical levels, allowing easier comparisons of structures across and within firms. Our findings not only align with prior research but also offer insights into industry-specific structural changes, functional distributions within organizations, and the evolution of executive roles over time. This work also highlights the potential of generative AI as a tool to empirically investigate key strategy questions.
