Artificial intelligence in leadership discourse (S&P 500 companies)

This study explores how artificial intelligence (AI) is framed in executive discourse related to leadership and decision-making. The empirical dataset includes 423 interviews with executives from companies listed in the S&P 500, totaling 3,779,645 words. The textual material was collected from the ProQuest database and analyzed using corpus-based lexical analysis with IRaMuTeQ software, which employs automated clustering and semantic classification on large textual datasets. The findings identify three main thematic clusters in executive discussions about AI: education, people, and market dynamics, which together make up 98.29% of the analyzed corpus. Instead of pinpointing causal factors for AI adoption, the results emphasize the predominant discursive frames leaders use when publicly discussing AI-driven organizational change. This study adds to research on AI-enabled leadership by providing extensive empirical evidence of how artificial intelligence is portrayed in executive communication and how these narratives shape leadership discourse on technological innovation.