Artificial Intelligence Implementation in Project Management

Session

Information Systems

Description

In the modern business landscape, nearly a quarter of global economic activities are conducted through projects, yet around 35% of them fail to meet their goals. To improve project success rates, organizations utilize methodologies like PMBOK and PRINCE2, alongside Agile approaches, particularly in IT sectors. Recently, Artificial Intelligence (AI) has emerged as a transformative tool in project management, automating tasks, providing predictive analytics, and enhancing decision-making. Despite its benefits, AI introduces challenges such as algorithmic bias, transparency issues, and data privacy concerns. This paper discusses the impact of AI on project management, its implementation challenges, and the need for adaptive strategies to navigate these complexities.

Keywords:

Project management, Artificial Intelligence, PMBOK, PRINCE2, Agile, algorithmic bias, predictive analytics, automation

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-982-15-3

Location

UBT Kampus, Lipjan

Start Date

25-10-2024 9:00 AM

End Date

27-10-2024 6:00 PM

DOI

10.33107/ubt-ic.2024.298

This document is currently not available here.

Share

COinS
 
Oct 25th, 9:00 AM Oct 27th, 6:00 PM

Artificial Intelligence Implementation in Project Management

UBT Kampus, Lipjan

In the modern business landscape, nearly a quarter of global economic activities are conducted through projects, yet around 35% of them fail to meet their goals. To improve project success rates, organizations utilize methodologies like PMBOK and PRINCE2, alongside Agile approaches, particularly in IT sectors. Recently, Artificial Intelligence (AI) has emerged as a transformative tool in project management, automating tasks, providing predictive analytics, and enhancing decision-making. Despite its benefits, AI introduces challenges such as algorithmic bias, transparency issues, and data privacy concerns. This paper discusses the impact of AI on project management, its implementation challenges, and the need for adaptive strategies to navigate these complexities.