IESE's AI Curriculum Rebuild: 18 Courses, 40+ AI Sessions

Published August 2026. Updated October 20, 2026 · By the EPR Editorial Team. Part of EPR's education coverage.

IESE Business School is rebuilding its full-time MBA around AI, with the redesigned program starting in September 2026. AI now runs through 18 first-year courses and more than 40 AI-integrated sessions, and IESE scored 72.0 in the 5W AI Business School Index 2026, ranking #19 of 60 schools and #3 in Europe. Its highest dimension score, 80, is for AI curriculum integration, which is the dimension a rebuild like this is meant to move.

• What did IESE announce?
• How does the case method change?
• What are the numbers behind the rebuild?
• How did IESE score in the AI Business School Index?
• Why does rewriting beat adding electives?
• What can other schools and brands learn?
• Where does this fit in EPR's education coverage?
• Frequently asked questions

What did IESE announce?

IESE announced a comprehensive redesign of its MBA in May 2026, for students starting in September 2026. The school describes the aim as preparing leaders to redesign work, lead human and AI systems, and make decisions under technological uncertainty, while strengthening managerial judgment. Deputy Dean Marc Badia said the school chose not to "bolt AI onto a couple of electives and call it a transformation."

The new curriculum is built around three capability areas that students develop in sequence.

How does the case method change?

IESE keeps the case method as the foundation and changes what a case asks of the student. Cases now routinely include an AI-generated analysis as an object of evaluation, not as the answer. Students frame the problem, judge whether the AI reached the right conclusion, make a decision with their own judgment at stake, and defend it in front of peers and faculty.

The redesign is organized around the dilemmas graduates will face on the job:

• Who is accountable when AI-augmented financial analysis is wrong?
• Where do the ethical limits fall when AI is used to shape consumer behavior?
• What does apprenticeship look like when AI does the work that used to train junior managers?
• What does competitive advantage mean when AI keeps resetting industry cost structures?

Associate Dean Evgeny Kaganer framed the logic simply: managerial work is deciding what to do, getting it done, and judging the results, and AI accelerates the middle step while making the first and last more valuable.

What are the numbers behind the rebuild?

Students also build a portfolio of applied work across the program, from AI audits and agentic workflow blueprints to prototype products for new business ideas, so they graduate with evidence of what they can do. Pre-program courses give every student a technical baseline, and second-year electives and projects deepen it.

How did IESE score in the AI Business School Index?

IESE scored 72.0 in the 5W AI Business School Index 2026, which ranks 60 schools in 14 countries on six equally weighted dimensions. That puts IESE at #19 overall and #3 in Europe, behind London Business School (79.5) and INSEAD (78.0), and just ahead of schools such as Anderson/UCLA, Tepper/Carnegie Mellon, McCombs/UT Austin and Oxford Saïd. Disclosure: 5W publishes the index, and Everything-PR News LLC is owned by a shared interest group that shares common ownership with 5W. The index measures AI readiness, not overall MBA quality, and 5W reports a margin of about 2.5 points.

The pattern is clear. Curriculum integration is IESE's strongest dimension, and the three dimensions at 68 are where the next gains are available. The index's own report card for London Business School lists, as a watch item, whether it will execute an IESE-style rebuild. See the Top 20 report cards and the full study at 5wpr.com.

Why does rewriting beat adding electives?

An AI elective teaches students about AI, and a redesigned core course teaches them to work inside it. When every first-year course treats AI as part of the operating environment, a student meets AI in finance, operations and strategy, not only in a specialist class. That matches the school's own framing: AI leadership is a challenge in every function, not a specialist topic.

The approach also has a communications benefit. A school that can say what changed, where and how many courses it touches gives rankings, journalists and AI engines specific facts to cite, which is the same discipline that earns citation share for any institution.

What can other schools and brands learn?

1. Change the core, not the catalog. Integration across required courses reaches every student, where electives reach the self-selected few.
2. Define the capability, then teach it. IESE named three capability areas, which makes the program easy to explain and to assess.
3. Keep what works. The case method stayed the foundation, with AI added as an object of judgment.
4. Bring the faculty along. A hackathon that drew 85 of 120 professors shows the redesign was built with the people who teach it.
5. Publish the specifics. Numbers such as 18 courses and 40-plus sessions are easy to verify and to cite.

Where does this fit in EPR's education coverage?