Language and Generative AI: A New Paradigm of Organizational Research

Language is not merely a medium of communication but a constitutive force in organisation 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 organisational communication. This paper advances algorithmic discourse research as a new paradigm for studying language in organisations. 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 organisations think, communicate, and act in the age of AI.

 

CONTRIBUTION TO KNOWLEDGE: This research advances organization studies by establishing algorithmic discourse research as a new paradigm for analysing language in the age of generative AI. It reconceptualises large language models (LLMs) as discursive actors shaping organizational sensemaking, extending discourse theory to account for human–algorithm co-construction of meaning. The study develops an integrated multilevel framework linking linguistic forms to organizational outcomes and redefines methodological rigour in AI-mediated contexts through pluralistic, reflexive approaches combining computational scale with interpretive depth.

ORIGINALITY: The work moves beyond the first linguistic turn by theorising LLMs as active participants in organisational communication rather than neutral tools. It offers a novel multilevel framework connecting micro-level language features to meso routines and macro outcomes such as innovation and trust. By positioning language as both data and process in AI-enabled environments, it marks a conceptual shift from analysing discourse to co-engaging with algorithmic language.

SIGNIFICANCE: The research addresses the rapid integration of GenAI into organizational communication and strategy. It provides a coherent framework for understanding how AI-mediated discourse shapes legitimacy, trust, and performance. By foregrounding ethical and contextual reflexivity, it informs debates on digital transformation and responsible AI governance relevant to scholars, practitioners, and policymakers.

RIGOUR: The study combines computational text analysis with interpretive, context-sensitive inquiry, maintaining established standards of validity while extending them to algorithmic settings. It embeds ethical reflexivity and methodological transparency into research design and ensures theoretical coherence across analytical levels.

LINK TO MY IMPACT: The research informs responsible AI implementation and organisational communication strategy by providing analytical tools to assess how AI-generated discourse affects decision-making and stakeholder relations. It contributes to emerging governance frameworks by strengthening understanding of transparency, accountability, and trust in AI-enabled organisational environments.