Appiah-Kubi, P., & Zouhri, K., & Lee, Y. (2025, June), Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams.  Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . https://peer.asee.org/57155

\bibitem{asee_peer_57155}
  Appiah-Kubi, P., \& Zouhri, K., \& Lee, Y. (2025, June), \emph{Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams.}
  Paper presented at 2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada .
  https://peer.asee.org/57155

Philip Appiah-Kubi, Khalid Zouhri, and Yooneun Lee.  "Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams.".  2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada , 2025, June.  ASEE Conferences, 2025.  https://peer.asee.org/57155 Internet.  19 Aug, 2025

\bibitem{asee_peer_57155}
  Philip Appiah-Kubi, Khalid Zouhri, and Yooneun Lee.
  "Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams.".
  \emph{2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada , 2025, June}.
  ASEE Conferences, 2025.
  https://peer.asee.org/57155 Internet.  19 Aug, 2025

@INPROCEEDINGS{asee_peer_57155
author = "Philip Appiah-Kubi, Khalid Zouhri, and Yooneun Lee"
title = "Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams."
booktitle = "2025 ASEE Annual Conference \& Exposition "
year = "2025"
month = "June"
address = "Montreal, Quebec, Canada "
publisher = "ASEE Conferences"
note = {https://peer.asee.org/57155}
}

TY  - CPAPER
AB  - The transformative potential of artificial intelligence (AI) has yet to be fully embraced by both academia and industry. While many have adopted and applied AI technologies, there remains skepticism regarding their role in shaping the future of work. Recently, attention has been focused on understanding the ethical use and implications of AI. Though progress has been made, much work is still required to ensure that AI serves the common good. One undeniable fact, however, is the significant impact AI is already making. The integration of AI into workplaces is transforming organizational operations. When implemented effectively, AI can enhance efficiency, automate repetitive tasks, and enable informed, timely decision-making. Technologies such as neural networks and natural language processing streamline tasks and improve customer interactions. In industries like manufacturing and logistics, engineering managers are using AI to optimize supply chains, improve product quality, and reduce downtime. They also leverage AI for predictive maintenance, performance evaluation, and project monitoring and control. Despite this progress, ethical concerns and limited knowledge about AI's potential may hinder its early adoption in engineering. This paper reviews engineering management students’ perceptions of AI in workload distribution, performance monitoring, and enhancing collaboration in engineering teams. Preliminary findings reveal concerns about job displacement, data privacy, and transparency. While many see the potential benefit of AI in a collaborative workspace, a significant number of the respondents express their lack of readiness to accept AI integration for performance monitoring and workload assignment. Thus, since many engineering students are eventually going to graduate and become engineering managers, who may utilize AI tools, engineering educators and researchers must continue to explore ways to enhance students’ familiarity and proficiency with AI systems.
AU  - Philip Appiah-Kubi
AU  - Khalid Zouhri
AU  - Yooneun Lee
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - Students' Perception of Artificial Intelligence Applications in Workload Distribution, Performance Monitoring, And Improving Collaboration in Engineering Teams.
UR  - https://peer.asee.org/57155
ER  -