Northwestern IEMS Announces AI-Augmented Decision Systems Major

Northwestern’s Department of Industrial Engineering and Management Sciences (IEMS) will launch one of the nation’s first undergraduate majors of its kind in fall 2027 to prepare students for a workplace that is increasingly shaped by data and AI.

The major in AI-augmented decision systems (AI-ADS) will train students to integrate modern machine learning—including generative AI, reinforcement learning, and learning from unstructured data—into end-to-end decision systems for fields such as finance, logistics, health care, energy, and the nonprofit sector. The program combines foundational AI and machine learning skills with the mathematical and analytical tools needed to decide how to act on them. The major is part of McCormick’s Bachelor of Science in Engineering, and students from any Northwestern school can add it as a second major. 

“AI can now do far more than predict outcomes. It can develop software and even help prove theorems. The harder problem is decision-making in complex systems, where a model’s output is only one input into the actions an organization has to own. This major trains students to embed generative and agentic AI into larger decision systems, together with statistics, risk analysis, and optimization, so that people, not models, remain accountable for the actions these systems inform,” said Simge Küçükyavuz, David A. and Karen Richards Sachs Professor of Industrial Engineering and Management Sciences and chair of IEMS.

AI-ADS builds on the strengths of Northwestern’s IEMS department, home to the nation’s No. 5-ranked undergraduate industrial engineering program. The department’s longstanding strengths in operations research, optimization, analytics, and the study of complex systems position it to bring these disciplines together in this new focal area. Students will learn from IEMS faculty who are internationally recognized for their work in optimization, stochastic modeling, statistical machine learning, and AI.

The curriculum for the new major emphasizes design that centers on human judgment and expertise, where students learn to treat accountability as a foundational engineering principle, ensuring that AI augments—rather than replaces—human agency. The program prepares graduates to steward and govern AI where it has the greatest impact: in organizational and societal decision-making.

The major arrives amid growing demand for workers with expertise in data science and operations research. The US Bureau of Labor Statistics projects 35 percent growth in data scientist jobs and a 12 percent increase in operations research analyst positions from 2025 to 2035.

According to the Financial Times, demand for “forward-deployed engineers” has surged 800 percent, reflecting a growing need for professionals who can turn advances in AI into practical results. These engineers combine technical expertise with an understanding of complex operations, integrating AI models into organizations to solve critical problems and drive measurable outcomes.

“Our students won’t just learn how AI models work. They’ll learn when to trust them, how to combine them with mathematical models, and how to keep people at the center of every decision. By the time they finish their client project, they’ll have applied their new skills to work with a real organization,” said Jill Wilson, professor and associate chair for undergraduate education.

In the program, students build a foundation in computer science, data engineering, statistics, probability, optimization, and machine learning. They explore techniques ranging from neural networks and reinforcement learning to transformers and AI agents, learning how to extract useful information from complex data and incorporate those predictions into mathematical models. Then, they apply those skills to problems such as turning market data and financial news into investment portfolios that balance risk and cost, reading demand signals from customer messages and traffic reports to optimize inventory and routing across a supply chain, and combining medical images with clinical notes to design treatment plans that spare healthy tissue.

They learn how interactive agents can help develop and refine models in response to user feedback, ultimately bringing prediction and optimization together to build systems for a range of industries. The major also requires an ethics course and includes a client project, in which students apply AI-enabled decision-making to a real organization’s problem.

Students who are interested in the major may fill out this form to learn more.