ENMGT 5410

AI Value Generation for Engineering Management

Course Description

Course information provided by the 2026-2027 Catalog.

This course examines the role of artificial intelligence in engineering management, emphasizing its potential to enhance organizational decision-making while recognizing the conditions necessary for its successful application. In modern engineering enterprises, AI can expand managerial capacity by improving forecasting, optimizing processes, and supporting more adaptive strategies. Yet these benefits are not automatic; they require careful problem selection, reliable data, and managerial expertise to translate technical outputs from AI into effective action. Rather than being viewed solely as a mechanism for automation, AI should be understood as a catalyst for process redesign, engineering-centric business model innovation, and long-term competitiveness. At the same time, its integration into engineering practice demands attention to workforce adaptation, cultural readiness, and ethical accountability. Throughout the course, students will develop the ability to critically evaluate when and how AI can complement human judgment and other tools, ultimately preparing them to lead engineering organizations through technological transformation with both rigor and responsibility.

Last 4 Terms Offered (None)

Learning Outcomes

• Analyze and prioritize AI opportunities in engineering systems and processes by evaluating the underlying problem, data requirements, technical feasibility, and potential for measurable business value.
• Design AI-enabled improvements to engineering work, products, and processes by determining how AI can augment human expertise, redesign workflows, accelerate innovation, and improve engineering and operational outcomes.
• Evaluate and lead responsible AI adoption in engineering organizations by balancing technical performance and business value with workforce implications, safety, ethics, accountability, and long-term organizational readiness.

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