Agentic AI represents a fundamental shift in how intelligent systems operate within organizations, moving from reactive tools that respond to prompts toward proactive systems that anticipate needs, plan actions, and execute complex workflows autonomously. Consider the difference between a GPS that responds to a question about a route and a self-driving system that monitors conditions, adapts in real time, and arrives at the destination without constant input. This is the distance organizations must now prepare to navigate.

This program bridges strategic insight with hands-on application, grounded in the premise that we are entering an era of AI-driven enterprises where intelligent agents function not merely as tools, but as teammates embedded in the organizational fabric. We equip business leaders with the strategic frameworks and practical capabilities required to lead this transition responsibly.

Over several interactive days, participants move from foundational understanding to actionable strategy: clarifying where agentic AI creates value, designing pilot initiatives with appropriate safeguards, and constructing deployment playbooks that integrate risk, governance, and scaling considerations.

Upon successful completion of your course, you will earn a certificate of completion from the MIT Sloan School of Management. This course may also count toward MIT Sloan Executive Certificate requirements.

At the end of this course, you will be able to:

• Frame agentic AI with clarity and confidence, distinguishing proactive agents from reactive LLM systems.
• Identify high-value use cases across customer, operational, and risk contexts.
• Apply the "Tool vs. Teammate" framework to redesign organizational structures for a blended workforce.
• Design agent-based workflows responsibly, integrating scaffolding, orchestration, and human-in-the-loop oversight.
• Lead implementation and governance, defining role boundaries, escalation paths, and monitoring rhythms.
• Assess agentic risks related to trust, safety, and compliance through immersive simulations.
• Translate AI initiatives into enterprise value through a credible, board-ready ROI narrative.

This program ensures participants encounter agentic AI through direct experience. You won’t just hear about AI agents. You will build them.

Central to the experience are four integrated artifacts designed for immediate organizational use:

• Building an AI Agent: Participants use no-code/low-code platforms to construct a working agent, gaining grounded intuition by configuring goals, tools, and guardrails.
• Agentic AI Opportunities Audit: A structured prioritization framework to identify and evaluate high-impact, low-risk opportunities for autonomy within your organization.
• Agentic AI Business Model Canvas: A single-page strategic tool used to rapidly assess organizational fit, value propositions, and governance requirements before committing resources.
• Rogue Agent Simulation: An immersive crisis exercise where teams must triage a simulated agentic failure, redesign safeguards, and draft executive communications.

The journey culminates in the development of a Personalized Agentic AI Playbook. This board-ready deliverable integrates your use case definitions, technical architecture, risk assessments, and a phased deployment roadmap with a clear ROI narrative.



You will participate in small group discussions, examine case studies and models, and leave with valuable frameworks.

Learn more about the in-person course experience.

Learn more about the live online experience. 

This course is explicitly designed for leaders who need to lead agentic AI adoption, rather than build the systems themselves. It is ideal for:

• Senior executives responsible for AI strategy, digital transformation, or technology investments.
• Functional leaders in operations, finance, risk, or customer experience evaluating agentic workflows.
• CAIOs, CTOs, and CDOs building organizational agentic AI capabilities.
• Board members and general managers seeking to exercise informed oversight over agentic AI governance.