Portland, Oregon
June 23, 2024
June 23, 2024
June 26, 2024
Engineering Management Division (EMD)
Diversity
17
10.18260/1-2--47700
https://peer.asee.org/47700
92
Sakhi Aggrawal is a Graduate Research Fellow in Computer and Information Technology department at Purdue University. She completed her master’s degree in Business Analytics from Imperial College London and bachelor’s degree in Computer and Information Technology and Organizational Leadership from Purdue University. She worked in industry for several years with her latest jobs being as project manager at Google and Microsoft. Her current research focuses on integrating project management processes in undergraduate education. Her main goal is to understand how work management and product development practices widely used in industry can be modified and adapted to streamline undergraduate STEM education.
Paul Thomas is a clinical assistant professor in the Department of Computer and Information Technology at Purdue University. His research interests are in software modeling, gamification, and active learning.
Background: The rapid evolution of Artificial Intelligence (AI) has opened up numerous avenues for automating various tasks in diverse industries. Project management, a crucial element in engineering education, can greatly benefit from AI tools, such as chatbots and virtual assistants. ChatGPT, a variant of the GPT series known for its conversational capabilities, exemplifies the growing prominence of AI in everyday applications, becoming almost synonymous with accessible AI. As the boundaries of what AI can achieve are continually pushed, engineering education must also evolve alongside these advancements. Through this research, we aim to align the current industry usage of AI in project management with academic approaches.
Purpose: The purpose of this study is to understand the current usage and perceptions of industry professionals about AI tools in project management tasks. The specific research questions are: (1) What factors influence the usage of AI tools in project management practices? (2) How are project managers currently using AI tools? (3) What are their perceptions of these tools?
Methods: A survey was designed to gauge industry professionals' usage and perceptions regarding AI's tools in project management tasks and included questions to gather demographic data. This survey was shared across multiple project management groups on LinkedIn over a three-month duration, attracting 113 responses. A cleaning process was implemented to remove any invalid responses. A correlational analysis was performed on the quantitative data. Concurrently, qualitative data was thematically analyzed to gain insights into usage and perceptions surrounding AI.
Results: The study revealed a growing trend among project management professionals in leveraging AI tools for a variety of tasks, including project planning, task assignment, tracking, and crafting emails, reports, and presentations. A strong correlation was observed between familiarity with ChatGPT and its likely usage in project management tasks. While some participants found AI tools convenient and efficient, they were frustrated with potential inaccuracies and the need for specific input prompts. Overall, industry professionals demonstrated the usage of AI in project management, with a notable emphasis on task automation and aid in data-driven decision-making.
Implications: The study findings depict the current usage of AI tools in project management and suggest opportunities to update project management curricula to include AI-focused content, practical applications, and ethical considerations of AI. Educators are recommended to provide hands-on experiences with AI tools, aligning academic teachings with current industry practices. This alignment is essential for preparing engineering graduates to meet the demands of a workplace increasingly reliant on AI.
Aggrawal, S., & J. Thomas, P. (2024, June), Investigating the Industry Perceptions and Use of AI Tools in Project Management: Implications for Educating Future Engineers Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47700
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