ENGG 119 - AI in the Real World

Artificial intelligence has moved from research labs into the daily work of almost every field, particularly engineering and technology management. Whether you are building products, managing teams, overseeing supply chains, or analyzing data, AI is reshaping what is possible—and what is expected. Graduates entering roles as AI architects, technical leads, process, design, or R&D engineers, engineering managers, product/project managers, operations managers, consultants, and data/task analysts will be expected not only to leverage AI in the products and services they build, but also to lead the transformation of organizational processes into AI-native workflows that measurably improve productivity and decision-making. But what, exactly, is AI? How did it come to be, what can it actually do? Where does the hype end and the reality begin? How are organizations across industries experiencing the shift toward AI-native operations today? And what AI-powered foundational skills will the workplace demand of technology managers in the months and years ahead? This course addresses these questions across three interconnected parts: Part 1 (Foundations) builds AI literacy from the ground up. Through lectures and faculty-led discussions, this section covers the history of the field; the fundamental concepts and principles—from knowledge representation, search, and optimization to reasoning, language understanding, and neurosymbolic processing—that drive current core technologies such as large language models and agentic systems; how lessons learned continue to push the fast-evolving capabilities of AI; how AI systems are validated, improved, and managed; and the ethical and governance considerations that must accompany any deployment. Part 2 (AI in Industry) brings practitioners into the classroom through facilitated and engaging conversations, examining how AI is being leveraged in outputs (enhancing the products and services a firm offers) and inputs (improving the internal processes and productivity of work) in the commercial world today. Guests will span a variety of industries including manufacturing, digital products, healthcare, and financial services and will bring real world examples and challenges to the students around how AI is transforming products, services, and organizations. Students will engage deeply with these guests, building upon the insights and anecdotes shared via follow-up in-class discussions and debates. Part 3 (Hands-On Practice) puts these concepts into action and practice: student teams scope, prototype, and present AI-powered solutions to real business and engineering problems, emerging with tangible artifacts and the applied confidence to lead AI initiatives in their careers.

Coding experience and statistics/probability are required prerequisites ENGS 20 and (ENGS 27 or ENGS 93 or ENGG 193) or equivalents.