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Executive AI MBA

Where AI, capital, and institutional judgment converge

A closed forum on AI, capital, and long-term industrial governance 

The Executive AI MBA is not a conventional degree program, nor a classroom-based course of study. It is an aggregated executive formation designed for senior participants who engage with AI at the level of strategy, capital allocation, and institutional responsibility.

Rather than progressing through a fixed curriculum, participants complete the program by engaging across the Executive AI Forum series—held in Zurich, Tokyo, Dubai, and London—and by contributing to the intellectual output of SIAI through authorship and institutional participation. The program is structured to accommodate different time horizons, while maintaining a single standard of depth, seriousness, and contribution.

Completion of the Executive AI MBA signifies not the acquisition of tools, but the demonstrated ability to interpret AI within economic, industrial, and governance systems, and to contribute meaningfully to institutional-level discourse.

Full-Year track

The Full-Year Track is designed for participants who wish to complete the Executive AI MBA within a single academic cycle.

Participants in this track attend all four Executive AI Forums within the year, beginning with the Zurich forum in June and concluding with the London forum in March. Alongside forum participation, candidates are required to meet the program’s graduation requirements by contributing an original piece of analysis to the SIAI Business Review, published under Fellow status.

The Full-Year Track emphasizes continuity and synthesis across regions and institutional contexts. Upon successful completion of forum participation and review contribution, participants are formally conferred the Executive AI MBA and appointed as SIAI Fellows.

Part-Time track

The Part-Time Track is designed for senior participants who prefer a flexible, multi-year engagement.

Participants may attend the Executive AI Forums selectively across years, building exposure to different regional and institutional perspectives over time. There is no fixed sequence or annual requirement; progression is determined by depth of engagement rather than pace.

When a participant elects to complete the program, they are required to contribute an original analytical piece to the SIAI Business Review, at which point they are appointed as SIAI Fellows and formally conferred the Executive AI MBA.

The Part-Time Track allows participants to integrate the program into long-term professional responsibilities, while holding all candidates to the same standard of institutional contribution upon completion.


Executive AI MBA

at a glance

COUNCIL TRACK

3-5 DAY EVENT

EXECUTIVE TRACK

AI AT CONTROL LEVEL

CONFERENCE SESSION

BUSINESS ORIENTED

Two tracks

PART-TIME TRACK FOR MULTI-YEAR AND MODULE-BASED ENGAGEMENT

FULL-YEAR TRACK FOR SINGLE-YEAR AND CONSECUTIVE ENGAGEMENT

Executive AI MBA

Program Structure
How classes work
  • 3-hour Video-recorded classes per week (Required)
  • 1-hour support sessions per week  (Selective)
  • Final exam / term paper 1-week after the end of the course
  • Total 12 courses, 2 courses for 1 term
  • 1 term for 8 weeks
Admission
Admission

Class module : Online only

Credit : 60 ECTS / (Level / EQF 7)

Required documents 

  • Bachelor diploma and transcript (mandatory)
  • Graduate school diploma and transcript (if applicable)
  • Statement of Purpose
Course Curriculum
Course Curriculum

1 Year for 12 courses
1 Term for 8 weeks with 2 courses

Prep classes are available

  • LaTeX for assignments and paper writing
  • Programming prep for Python

Core Course Description

Admission Examination
Admission Examination
  • No official admission examination
  • Following documents will be thoroughly reviewed
    • Statement of Purpose
    • Undergraduate transcript

Please note that if you have not done any STEM education during your undergraduate or even in graduate studies, we recommend you to try MBA AI programs' business track or non-STEM AI MBA. Even if you have applied for PreMSc, if no record of mathematical training is found, the offer letter will be given to MBA programs.

Tuition Fees
Tuition Fees
  • Application fee : CHF 200.- (Non-refundable)
  • Administration fee : CHF 2,000.- (Non-refundable)
  • Courses : CHF 1,650 per course
    – 2 courses per term (Bi-monthly payment)
    – 1 course for 5 ECTS*

Advance to MSc requirements

  • Coursework – 60 ECTS* wth average 60% or above
  • STA511 and STA512 - Average 60% or above

*ECTS – European Credit Transfer and Accumulation System

Q&A

The technical track shares most of undergraduate STEM education required for AI/Data Science, which is also taught at PreMSc AI/Data Science. This is the most chosen program by students who look for a quick study for AI/DS without grad school level Math & Stat. Course materials are mostly at Junior to Senior years of undergraduate programs in the US top research schools. Many parts of our lecture notes are publicly shared (check above 'Lecture Note' link) so as to help students to understand what we teach and what are the examination questions. For business track, since we do not assume students to be well-equipped to STEM's math, we replace examinations with essays. The biz track is for students to look through what real AI/Data Science field is running, and be conversant to data scientists.
Students must earn 50% or above on average in coursework and should pass dissertation. Grading scale of the school is available from school's regulation. Students must finish the coursework within two years and should pass dissertation in the following year
Students can choose to write dissertation during the 2nd semester or after the coursework. If to finish the dissertation by the end of 2nd semester, the graduation will be September of the year, otherwise September of the following year. The dissertation support course offers total 6 meetings with students. Students are to meet instructors via online meeting and all conversations will be recorded for personal and peer review purposes.
We do not expect students to be software engineers. We want students to be a data/research scientist with scientific programming skills. How fast you type codelines or how long code have you debugged, for example, are irrelevant experience for us. We want students to convert mathematical reasoning to program code to materialize thought experiments. Most courses provide sample codes for assignments and examinations.
There only are two course differences between two programs. BUS502 and BUS503 are focused on BigData-based model optimization, which are typical in IT sectors. In-depth discussions of recommendation engine, multi-touch attribution models are well-known examples that are shared between AI Marketing and Data Science, for example. BUS504 and BUS505 are for Finance track courses that covers recently adopted financial models in Corporate Financd and Financial Investments. It is not like we help you to create an AI model that beats fund managers. We focus more on comparing traditional financial theories with new approaches that are, in fact, only an extension of old models. In the end, AI/Data Science is just computationally heavy statistics. We help students to understand that.
AI Engineers from technologically 2nd-tier institutions think running AI code libraries is AI/Data Science. We want our students to pre-check the data to identify potential correlations that may affect denseNet's performance, thus propose a revised model to either re-design the NeuralNet or change the data structure accordingly. At the end of the day, all good models are DGP (Data-Generating-Process) optimised variations of existing models, not a copy of other company's working code. This is our version of 'Critical Thinking'
Computer programming indeed is essential in every sub-discipline at SIAI, but students are given ample amount of study materials. For starters, Issues in Computer Programming (OPT101) , a short prep course given to all incoming students, covers a number of programming issues that are basics for later courses. In addition to that, for every problem set and term paper, a set of guideline code lines are given so as to provide right direction.
Unfortunately, as an online business school, we do not provide any offline support for learning. However, students are free to ask to the course forum. Professors and TAs are available within a short reach of forum posting.

Executive AI MBA


Clarity on AI, before strategy becomes irreversible.

AI is now discussed as if its strategic implications were already understood: budgets allocated, vendors selected, and institutional commitments quietly made. Yet for many organizations, the most consequential decisions around AI are being taken under conditions of incomplete information, misaligned incentives, and public narratives that discourage honest reassessment. Once capital, regulation, or reputation is committed, reversing course becomes costly—sometimes impossible

The Executive AI MBA exists to address this moment. It provides a closed setting in which senior participants can examine AI before decisions harden into doctrine. Discussions are grounded in economic constraints, statistical limits, and institutional realities that rarely appear in public forums. Rather than promoting adoption or resisting it, the forum focuses on understanding where AI genuinely changes outcomes—and where it does not.

For participants responsible for long-term strategy, capital allocation, or policy design, the value of the forum lies in recalibration. It offers a rare opportunity to stress-test assumptions, compare institutional perspectives, and regain strategic clarity before commitments become path-dependent. The result is not consensus, but sharper judgment—aligned with the responsibilities that senior roles actually carry.

Participation in the Executive AI MBA is by invitation only, or through nomination by partner institutions.

Access to institutional-grade judgment about AI — before capital, policy, or reputation is committed

Be AI leader not follower!
Department Contact Info

Executive AI MBA Program

[email protected]

Mon – Fri 9:00 A.M. – 6:00 P.M.