AI in Academia: Breakthrough or Black Box Threat to Scientific Integrity?

Abstract

In recent years, the emergence of generative artificial intelligence technologies in the field of academic research has represented one of the fastest and most pervasive changes in the recent history of management sciences. Within an extremely short time span, tools capable of generating text, analyzing large amounts of data, and supporting complex decision-making processes have become firmly embedded in the daily practices of researchers, reviewers, and editors. This transformation is not merely technological: it affects the epistemological, ethical, and methodological foundations of management research.

Leading international scientific journals have taken a stance through guidelines and editorial policies, acknowledging both the transformative potential of AI and its systemic risks, as well as the need to govern its use responsibly. A shared principle clearly emerges from these documents: artificial intelligence can be a powerful support tool for research, but it cannot and must not replace the critical judgment, responsibility, and creativity of the researcher.