Enhancing Stakeholder Analysis with AI: A Comparative Study of Productivity and Quality in the Educational Context

Vijay Kanabar; Kalinka Kaloyanova

doi:10.4108/eetsis.9376

Authors

Vijay Kanabar Boston University
Kalinka Kaloyanova Sofia University "St. Kliment Ohridski"

DOI:

https://doi.org/10.4108/eetsis.9376

Keywords:

Stakeholder Analysis, Information System Development, System Analysis and Design Project Management, Generative Artificial Intelligence, AI

Abstract

This paper examines the application of generative artificial intelligence in stakeholder management while studying the business aspects of software development and project management in two different universities. It explores a novel intersection of AI with software development and project management practices, offering valuable insights for both academia and industry. By investigating how students use AI alongside traditional methods under supervision, this study evaluates the effectiveness, quality of results, and creativity of students’ project assignments in identifying stakeholders and defining communication strategies. The findings suggest that AI can enhance work completion speed and contribute to greater project success due to a more complete identification of stakeholders and formulation of innovative stakeholder engagement strategies. There is a consensus, within this context, that while AI can be invaluable for project stakeholder management, human judgment remains essential.

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