What you'll learn

Agentic AI is transforming the finance industry. In this course, Agentic AI in Finance, you’ll learn how agentic AI differs from traditional rule-based automation and why autonomy, planning, tool use, and multi-step reasoning are valuable for modern financial workflows. First, you’ll explore how regulations and internal controls shape the design of financial agents, including adverse-action obligations, audit trails, approval thresholds, permissions, and escalation procedures. Next, you’ll examine risks such as bias, privacy violations, automation bias, agent hijacking, and cascading errors, and learn how testing, monitoring, and meaningful human review can reduce them. Finally, you’ll explore practical use cases across financial services, corporate finance, investment management, personal finance, and agentic commerce by examining real-world examples from Klarna, Ramp, Bloomberg, Morgan Stanley, Workday, Stripe, and Mastercard. When you’re finished with this course, you’ll be able to identify appropriate finance use cases for AI agents, explain what makes a workflow truly agentic, map the components of a controlled agent workflow, and describe how to deploy agentic AI in finance while maintaining accountability, compliance, and human oversight.