Beyond the hype: Organisational adoption of Generative AI through the lens of the TOE framework–A mixed methods perspective

  • Laurie Hughes*
  • , Fern Davies
  • , Keyao Li
  • , Senali Madugoda Gunaratnege
  • , Tegwen Malik
  • , Yogesh K. Dwivedi
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

It is widely accepted that the impact of Generative Artificial Intelligence (GenAI) has been nothing short of transformational, with tangible impacts on industry, education, healthcare and government. But beyond the headlines, how are organisations actually using GenAI, what are the key challenges experienced by decision makers and has the reality on the ground matched the hype? This study adopts a mixed-methods approach, utilising the Technology-Organisation-Environment (TOE) framework to reveal greater insights to how organisations are adopting GenAI, the drivers that affect decision making and the key challenges associated with greater use of the technology. This research adopts a mixed method approach incorporating an explorative qualitative step with industry participants followed by a survey of 304 (three hundred and four) decision makers from a cross section of industry sectors from around the world including: North America, Europe, Africa, Australia and Asia, to gain further insight to the underlying factors that drive GenAI adoption. The research model was validated using Structural Equation Modelling (SEM) and reveals the intricate and inherent complexities related to greater levels of GenAI adoption. The analysis highlights the critical role of change capacity of the organisation in moderating complexity and staff skills. This research provides valuable and timely insights for senior management and policy makers that are attempting to better understand the interdependencies and perspectives on the key challenges facing organisations looking to deliver greater impact on organisational performance through GenAI.

Original languageEnglish
Article number102982
JournalInternational Journal of Information Management
Volume86
DOIs
StatePublished - Feb 2026

Bibliographical note

Publisher Copyright:
© 2025 The Authors

Keywords

  • Generative Artificial Intelligence
  • IS/IT adoption
  • Technology-Organisation-Environment framework

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Marketing
  • Library and Information Sciences
  • Artificial Intelligence

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