The Artificial Intelligence (AI) specialization prepares you to lead the responsible adoption of AI in modern organizations. Designed for students from a wide range of academic and professional backgrounds, it approaches AI through an applied information management lens that connects technology, strategy, governance and organizational decision-making. 

You will build the skills to evaluate AI systems, design low-code solutions and assess the risks, opportunities and strategic value of generative AI in real-world settings.

This specialization pairs well with the Data Science specialization for those seeking more technical career paths or Program/Product Management & Consulting for those with interests in strategic roles.

Students solely interested in learning about artificial intelligence without the scaffolding of Information Management curriculum and additional electives or specializations, may want to consider the Information School's Graduate Certificate in Artificial Intelligence for Organizations.

Availability: Residential and online; daytime and evening classes

“You’re going to learn more than using ChatGPT or Claude or Gemini. You're gonna learn the concepts of how to build out a project, how to sell it, and then how to do it.”

— Calvin Brooks, ‘25

Skills you will develop 

• Understand opportunities and challenges with generative AI systems and learn how to responsibly use, configure and deploy generative AI.
• Create AI agents and workflows that integrate with business processes.
• Design and implement governance frameworks and policies for responsible AI deployment.
• Calculate and demonstrate return on AI investment and organizational implementations.

Elective courses in the Artificial Intelligence specialization

This specialization consists of three courses that will help you train a managerial lens on artificial intelligence. Courses in this specialization are not sequenced and can be taken out of order.

Learn more about the core, elective and Capstone/practicum courses in the MSIM curriculum. 

• IMT 521 Artificial Intelligence Foundations | 4 credits 
  Explores the neural architectures, learning methodologies and computational principles that enable modern AI systems, while critically examining their fundamental capabilities and limitations and potential impact on organizations and an organization's stakeholders. A significant focus is placed on responsible AI frameworks, including ethical considerations, fairness principles and mechanisms for ensuring accountability and transparency.
• IMT 522: Governing Artificial Intelligence: Managing Change, Risk, and Innovation | 4 credits
  Provides theoretical and practical introduction to applying responsible AI frameworks, conducting risk assessments and designing governance structures that transform regulatory compliance into competitive advantage.
• IMT 523 Implementing and Managing Generative Artificial Intelligence Systems | 4 credits 
  Introduces the design and implementation of generative AI systems, including prompt engineering, responsible AI practices, and the design, development and ongoing management of AI based enterprise applications. Explores AI implementation with low- and no-code tools.

New course offerings in AI will be added as the fast-changing needs of organizations shift and faculty expertise develops; these will generally be made available to residential students as Special Topics & New Courses.

Current students should review their handbook to learn about how previous artificial intelligence specialization courses fit into the finalized model.

Career outcomes

Students who specialize in Artificial Intelligence will find roles with titles including AI product manager, AI researcher, data governance analyst, product data analyst and risk and compliance analyst.