Artificial intelligence and organizational change: a bibliometric mapping of AI as a tool and as an object of change (2000–2026)

Angelo Leogrande, Mauro Di Molfetta, Valeria Nortarnicola, Maria Giovanna Trotta, Antonio Volpe Plantamura and Gianluca Zaza

No zadne_v1, SocArXiv from Center for Open Science

Abstract: Research on artificial intelligence (AI) and organizational change is growing fast but fragmented. Two perspectives coexist: one uses AI, defined here as machine learning, natural language processing, generative AI and related intelligent systems, as a tool to diagnose, design, implement and monitor change; the other studies AI as the object whose adoption triggers change. We map the field and how the two perspectives relate. Of 1,402 Scopus records, a large language model applying a criterion calibrated on the author's judgment retained 525 documents (2000–2026). We combined performance analysis, co-citation, bibliographic coupling, keyword and topic analysis, and a coding of change phases. The field has grown by almost 70% a year since 2018, mostly through research on AI as an object; the share of studies using AI as a tool fell from 28% up to 2020 to 11% in 2024–2026. The two perspectives rest on largely separate references. Research on AI as an object forms eight research fronts; research on AI as a tool forms none, and almost half of its documents are disconnected from the main coupling network. Only 32 documents propose or evaluate AI as an instrument for managing change. Diagnosis dominates and studies that use AI across several phases of change are rare. These findings hold under alternative inclusion criteria, except the absence of a tool-based front, which reflects the narrow definition of AI adopted. We argue that the field lacks integration and validation rather than new algorithms, and propose an integrative framework with six propositions.

Date: 2026-10-20
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:zadne_v1

DOI: 10.31235/osf.io/zadne_v1

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