Language and Generative AI: A New Paradigm of Organizational Research

Abstract Language is not merely a medium of communication but a constitutive force in organization management. Three decades after the first “linguistic turn” in organization studies, generative artificial intelligence (GenAI) and large language models (LLMs) are provoking a second, data -intensive turn that reconfigures the relationship between language, technology, and management. LLMs now operate as discursive actors that simulate, generate, and transform organizational communication. This paper advances algorithmic discourse research as a new paradigm for studying language in organizations. It reframes metthodological rigor as pluralistic and reflexive, combining computational scale with interpretive depth. It retains traditional standards of evidence while extending them to encompass ethical and contextual reflexivity, acknowledging that meaning, data, and validity are co -constructed. An integrated multilevel framework links micro -linguistic forms (lexical, metaphorical, modal), meso -level routines and narratives, and macro -level outcomes such as innovation, trust, and performance. The new paradigm expands the methodological and epistemological foundations of organizational research by positioning language as both data and process, and LLMs as analytic partners in the study of sensemaking. In doing so, it marks a shift from observing discourse to co -engaging with algorithmic language, opening new avenues for understanding how organizations think, communicate, and act in the age of AI.