The Role of Generative AI in Driving Sustainable Digital Transformation and Organizational Performance

Authors

  • Waqeem Akram M.Phill, University of the Punjab Author
  • Zeeshan Ali M.Phill, Higher Education Department Author
  • Shumaila Akram BBA (hons), Higher Education Department Author
  • Shehar Bano Ph.D, Universitas Islam Internasional Indonesia (UIII) Author

DOI:

https://doi.org/10.59075/b1dazr60

Keywords:

Generative AI, Sustainable Digital Transformation, Organizational Performance, Systematic Literature Review, Conceptual Framework

Abstract

Generative Artificial Intelligence (GenAI) is becoming a widely understood as a transformative capability that changes the organizational strategy, operations and sustainability efforts. Although the idea of AI and digital transformation has become increasingly popular, the literature has seldom explored the niche of GenAI in facilitating sustainable digital transformation and promoting organizational performance. This research paper fills this gap with a systematic literature review (SLR) of 138 peer-reviewed articles that have been published between the years 2020 and 2025 and have been located in Scopus and Web of Science in accordance with PRISMA protocol. Six themes were identified in the thematic analysis: strategic implementation of GenAI, operational efficiency and automation of processes, data-driven decision-making, human-AI cooperation, ethical and governance, and performance outcomes of sustainability. It is based on these insights that an integrative conceptual model is created that shows how sustainable digital transformation brought about by GenAI adoption mediates organizational performance with the moderators being ethical governance and human-AI collaboration. The research enhances theory, offers management, and gives future research of GenAI in business directions.

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Published

2025-12-20

How to Cite

The Role of Generative AI in Driving Sustainable Digital Transformation and Organizational Performance. (2025). The Critical Review of Social Sciences Studies, 3(4), 2983-2996. https://doi.org/10.59075/b1dazr60