09 Feb, 2026
If you’re wondering how the UVA MSBA program incorporates AI into the curriculum and classroom, this post is for you! Recently on The Darden Report, faculty from the program shared insights into how the program has embedded artificial intelligence into its curriculum since day one, and how it prepares students with the essential AI skills organizations now demand.
“The MSBA is intentionally designed as a fully integrated analytics and AI curriculum in which every module builds toward a real organizational application,” said Raj Venkatesan, Co-Academic Director of the program and Darden’s Ronald Trzcinski Professor of Business Administration.
Venkatesan, along with Jingjing Li, MSBA Co-Academic Director and McIntire’s Andersen Alumni Associate Professor of Commerce, said the UVA MSBA program’s AI learning strategy is built on five pillars:
- Develop skills in the latest AI and machine learning systems.
- Teach AI and analytics as an end-to-end system, not isolated skills.
- Emphasize real-time, real-organization AI challenges.
- Prepare students to lead AI initiatives, not just execute them.
- Integrate AI into a robust organizational strategy, including change management and value realization.
“Graduates acquire technical, strategic, and leadership capabilities required to drive AI-enabled innovation inside complex organizations,” Venkatesan said.
The program is divided into five modules, each concluding with a team capstone project. Across modules, students develop skills in analytics, AI, data engineering, strategy, communication, and project design. The capstones are sponsored by real organizations that require students to build AI-powered applications that address the real needs of sponsor organizations. Together, the modules and capstone projects progress from relatively simple to increasingly complex as students learn and develop skills. The students are often able to apply their learning from courses and projects back to their work immediately.
For example, one student working in health care built an NLP model for patient feedback inspired by the Module 4 FDA adverse drug reaction project. The effort delivered major time savings for the student’s clinical operations team.
“Students solve progressively more sophisticated AI problems…It is not enough to teach how to build models,” said Li. “Organizations need business leaders who understand how AI reshapes culture, operations, customer experience and strategy.”
Read the full story to learn more about each of the five modules and how faculty continue to evolve the program curriculum to keep up with advances in the industry.