A New Course on "Artificial Intelligence for Engineering Managers" - Objectives, Teaching Methods and Structure
- Conference
- Location
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Montreal, Quebec, Canada
- Publication Date
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June 22, 2025
- Start Date
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June 22, 2025
- End Date
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August 15, 2025
- Conference Session
- Tagged Division
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Engineering Management Division (EMD)
- Tagged Topic
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Diversity
- Page Count
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11
- DOI
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10.18260/1-2--55374
- Permanent URL
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https://peer.asee.org/55374
- Download Count
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6
Paper Authors
Edwin R Addison North Carolina State University at Raleigh
Dr. Edwin Addison is a Professor of the Practice at NC State University in the Department of Industrial and Systems Engineering and in the Engineering Online program as well as the Master of Engineering Management Program. He teaches courses in Product Management, Entrepreneurship, and Artificial Intelligence.
Dr. Addison was a serial entrepreneur, venture capitalist, and adjunct professor for 35 years before his current appointment. He started five companies in IT and the Life Sciences (all based on AI), successfully funded four of them, exited from three of them, was named "Entrepreneur of the Year" in two of them, and has one still standing. In addition to start-up companies, Dr. Addison previously worked for Westinghouse Electric Corporation, Booz Allen and Hamilton, and IQVIA.
Ed Addison has a BSEE from Virginia Tech, an MSEE and MS BME from Johns Hopkins, an MBA from Duke, and a JD from Purdue, and he completed a sabbatical year at MIT in Artificial Intelligence on the BG Lamme Scholarship, where he received the Certificate of Advanced Engineering Studies. He received a teaching award from Johns Hopkins University. He previously taught at Johns Hopkins University, Stevens Institute of Technology, the University of San Diego, and the Jack Welch Management Institute before his current appointment at NC State University.
Ed resides in Raleigh NC, with his wife Karen of 18 years. He has six grown children and 15 grandchildren. Ed is a licensed Airline Transport Pilot, a jazz pianist, and an active competitive swimmer.
Abstract
The course Artificial Intelligence for Engineering Managers has been offered four times, and this paper showcases its bold vision, pioneering teaching strategies, agile structure, and critical lessons learned through real-world delivery. As one of the first courses of its kind, it empowers engineering managers with a robust understanding of artificial intelligence (AI) and machine learning—without requiring technical programming skills. Participants are equipped to confidently lead AI initiatives and drive transformative change within their organizations. Through a deep dive into AI methodologies—including machine learning, deep learning, and natural language processing—students develop critical thinking and practical skills to evaluate when and how AI can unlock organizational value. Beyond foundational concepts, the course offers strategic insights into data sourcing, project planning, and resource estimation, essential for executing successful AI initiatives. Sometimes delivered through a dynamic inverted classroom model, students engage with thought-provoking lectures online, then apply theory to practice in lively, interactive sessions. Activities include solving real-world machine learning challenges, architecting the adoption of large language models (LLMs), and developing comprehensive AI management roadmaps. The curriculum underscores how AI is revolutionizing industries, reshaping economies, and redefining the workforce, while emphasizing the ethical imperatives necessary for responsible deployment. This paper highlights the course’s most effective elements, illustrating how its innovative structure and targeted learning objectives prepare engineering managers to lead AI-driven innovation with strategic vision.
Addison, E. R. (2025, June), A New Course on "Artificial Intelligence for Engineering Managers" - Objectives, Teaching Methods and Structure Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--55374
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