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

Year: 2025

Type: article

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.

Source: ICST Transactions on Scalable Information Systems

DOI: 10.4108/eetsis.9376

Authors: Vijay Kanabar, Kalinka Kaloyanova

Institutions: Boston University, Sofia University "St. Kliment Ohridski"

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: European Commission, NextGenerationEU

Awards: G2566934999, G4188552653, G6591462519