Agentic AI in the Real World
AGAI 402
Survey how agentic AI is being deployed across industries today. From software engineering and scientific research to healthcare and finance, examine real-world use cases, the lessons learned, and the challenges that remain unsolved.
AI at Work in the World
Agentic AI is no longer a research topic. It is actively being deployed in software engineering, legal research, drug discovery, financial analysis, customer service, scientific literature review, and dozens of other fields. This course surveys those deployments — what works, what doesn't, and what the broader implications are.
Learning from Real Deployments
Theory is important, but real-world deployments teach lessons that laboratories cannot. This course examines real cases where agentic AI has delivered significant value, alongside honest accounts of where it has failed, produced harmful outputs, or required significant human oversight to remain useful.
What You Will Learn
You will survey real agentic AI deployments across software engineering, scientific research, healthcare, finance, legal research, and enterprise operations — analyzing what worked, what failed, and why. You will develop a framework for evaluating AI deployment opportunities and risks in any domain, understand the emerging regulatory landscape, and think clearly about the societal implications of the technology you are building.
Who This Course Is For
This course is the capstone of the curriculum — designed for practitioners who have completed the technical foundations and want to develop the broader judgment needed to deploy AI responsibly at scale. It is also a strong standalone course for technology leaders, policy professionals, and domain experts in industries where agentic AI is arriving now.
What you will learn
- Describe real-world deployments of agentic AI across industries
- Identify the factors that determine success or failure in AI deployments
- Evaluate the societal implications of widespread agentic AI
- Apply lessons from real deployments to your own projects
- Articulate the regulatory landscape for AI systems
Major topics
Why this course matters
Understanding how AI is actually being used — and where it struggles — gives you the perspective to build better systems, set realistic expectations, and think clearly about the larger implications of the technology you are building.
Course modules
AI in Technical Domains
Examine how agentic AI is changing software engineering, scientific research, and technical knowledge work. This module focuses on high-visibility deployments such as GitHub Copilot, Devin, AlphaFold, and research assistants, with attention to both productivity gains and real limitations.
AI in Enterprise and Services
Explore how agentic AI is being deployed in healthcare, legal work, finance, customer service, and enterprise operations. These domains show the value of AI assistance, but also reveal the importance of trust, privacy, auditability, and human accountability.
Society, Governance, and the Path Ahead
Move beyond individual deployments to the broader social, economic, legal, and regulatory implications of agentic AI. This module helps practitioners think responsibly about labor impact, accountability, liability, regulation, and the future of increasingly capable AI systems.
Common misconceptions
AI agents will automate all knowledge work immediately
Successful AI deployment requires no human oversight
AI regulation stifles innovation
The biggest risk from AI is science fiction-style superintelligence
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