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

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.

Authors

Publication Details

Journal
ICST Transactions on Scalable Information Systems
Published
2025-05-23
DOI
https://doi.org/10.4108/eetsis.9376
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

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

Vijay Kanabar, Kalinka Kaloyanova
ICST Transactions on Scalable Information Systems
Impact of AI and Big Data on Business and Society
article

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

Vijay Kanabar, Kalinka Kaloyanova
article en

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.

ICST Transactions on Scalable Information SystemsVol. 12(3)
European Commission
Openalex Percentile: Top 87%
Impact of AI and Big Data on Business and Society
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