ONLINE COURSE

Agentic AI for Organizational Transformation

Leverage AI Agents to Elevate Efficiency and Innovate Models

Inquiring For
Work Experience

Empowering leaders to navigate the impact of Generative and Agentic AI

Digital transformation isn’t just digitizing workflows - it’s about reimagining operations, markets, and leadership with AI at the center. In this executive-level program, you’ll go beyond high‑level theory to acquire practical frameworks, tools, and governance strategies tailored for Generative and Agentic AI. Through hands-on exercises, real-world case studies, and expert instruction, you’ll learn to build AI‑powered systems responsibly and strategically - from prompt to impact.

What you will learn?

  • Understand the foundations of Generative and Agentic AI - how they work, how they differ, and how they apply to real organizational functions.

  • Design AI-integrated strategies using cloud infrastructure, APIs, and enterprise platforms to deliver real-world impact.

  • Build practical skills through hands-on mini-projects, including text, image, audio, or video generation with no prior coding required.

  • Address the risks and responsibilities of AI, from deepfakes and misinformation to legal compliance and ethical governance.

Why enroll in this course?

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Engage in two live sessions with MIT instructors, and up to eight live sessions with learning facilitators, industry experts, and peers.

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Networking opportunities establish professional connections with industry experts and your cohort.

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Access to rich supplementary resources provides additional materials and content for a more thorough educational journey.

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Navigate AI’s ethical and regulatory landscape with confidence, from bias and data privacy to frameworks like GDPR, CCPA, and HIPAA. 

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Join a global network of peers and professionals engaged in reimagining how AI drives impact at scale. 

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Bridge the gap between AI and business outcomes, without needing a technical background. 

Certificate

Certificate

All the participants who successfully complete their program will receive an MIT Professional Education Certificate of Completion, as well as Continuing Education Units (CEUs)*.

To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.

*The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.

To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.

Modules

*Modules and curriculum are subject to change 

Who is the course for?

This program is designed for mid-to-senior working professionals who understand the urgency of AI and want to lead its adoption effectively across their organizations. Whether you're shaping digital strategy, managing transformation initiatives, or advising others on innovation, this course gives you the frameworks to turn AI into actionable outcomes.  This program is ideal for: 

  • C-suite executives (CEOs, CIOs, CTOs, CMOs, COOs) aiming to make informed decisions about AI strategy and integration 

  • Business leaders and function heads driving digital innovation in operations, marketing, product, or strategy 

  • Managers and team leads modernizing workflows and aligning cross-functional teams with emerging technologies 

  • Technical professionals moving into leadership roles in digital transformation or innovation 

  • Consultants and advisors supporting clients through AI-driven change and adoption planning 

No prior experience with programming, coding or AI tools needed.

Instructors

MPE - Faculty - Abel Sanchez
Dr. Abel Sanchez

Executive Director of MIT’s Geospatial Data Center, Research Scientist; Center for Complex Engineering Systems, Sociotechnical Systems Research Center, under the Schwarzman School of Computer Science

MPE - Faculty - John R. Williams
Prof. John R. Williams

Professor of Information Engineering, Civil and Environmental Engineering and Director of MIT Geospatial Data Center, and a faculty member in the Center for Computational Science and Engineering part of the Schwarzman School of Computer Science

Didn't find what you were looking for? Schedule a call with one of our Program Advisors or call us at +1 857 7668188.

Register now and boost your professional trajectory.

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