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Executive AI Forum in London

Where AI, capital, and institutional judgment converge

An annual agenda-setting forum on AI, capital, and long-term institutional governance 

AI is increasingly treated as an operational matter—budgeted, delegated, and executed within existing organizational frameworks. Yet at the level of capital allocation, policy alignment, and institutional credibility, many of the most consequential questions surrounding AI remain unresolved. For senior leaders, the challenge is no longer whether AI will be adopted, but how its long-term implications should be interpreted, governed, and sequenced.

The Executive AI Forum in London is convened as the opening institutional forum of the year. Held at the close of the previous financial cycle and at the outset of the new one, the London event serves as a point of strategic recalibration—bringing together fellows, sponsors, and invited guests to reflect on the prior year and to frame the questions that will shape AI, capital, and governance decisions in the year ahead.

Unlike other city forums within the Executive AI series, the London event is designed primarily as an agenda-setting convening. Rather than focusing on inspection or exposure, it emphasizes synthesis, priority-setting, and institutional interpretation. The forum provides a structured environment in which senior participants can align perspectives on emerging risks, capital dynamics, and policy tensions before operational commitments are made elsewhere.

The London forum is jointly convened with The Economy Research, reflecting a shared commitment to rigorous, system-level analysis of AI’s economic and institutional implications. Together, the forum and conference aim to elevate the discussion beyond short-term trends, positioning AI within broader questions of industrial structure, financial cycles, and long-horizon governance.

The Patron Dinner is held during the the month of March, marking the first official convening of the year within the Executive AI series.

Patron Dinner

The Patron Dinner is a private, invitation-only gathering held alongside the London forum. It is designed as a setting for candid, off-the-record exchange among senior participants who play an ongoing role in the SIAI and The Economy ecosystems.

Invitations to the Patron Dinner are extended exclusively to:

  • SIAI Executive AI MBA participants
  • SIAI External Fellows of the year
  • SIAI institutional sponsors of the year
  • Distinguished guests invited through The Economy Research conference

The dinner is not a ceremonial event, but a working convening. Discussions focus on shared responsibilities in governance, capital stewardship, and institutional continuity, and on how insights from the forum and conference should inform action in the months ahead.

Conference Session

The Conference Session is a one-day public convening held as the central component of the London forum. It brings together distinguished speakers from research, policy, finance, and industry for focused discussion on themes that will define the AI and capital landscape over the coming year.

Rather than serving as a reporting or showcase event, the conference is structured around agenda formation. Presentations and panels emphasize forward-looking analysis—highlighting unresolved questions, structural constraints, and institutional trade-offs—rather than retrospective case studies or vendor-led narratives. The objective is to surface the issues that require sustained attention across the year, both within institutions and across jurisdictions.

The Conference Session is open to the public and free of charge. Attendance is subject to venue capacity and advance registration.


Executive AI Track

at a glance

COUNCIL TRACK

3-5 DAY EVENT

EXECUTIVE TRACK

AI AT CONTROL LEVEL

CONFERENCE SESSION

BUSINESS ORIENTED

London event

PATRON DINNER FOR SPONSORS, FELLOWS, AND DISTINGUISHED SPEAKERS

CONFERENCE SESSION FOR REGIONAL MARKET SPECIFIC UPDATES

MBA in AI & Big Data

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 : 90 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

Requirement for graduation

  • Coursework: 60 ECTS (12 courses)
  • Dissertation: 30 ECTS
    • Technical track: 20,000 words or above and technical interpretation of the topic
    • Business track: Case study equivalent to tech track's dissertation

Core Course Description

Tuition Fees
Tuition Fees
  • Application fee : CHF 200.- (Non-refundable)
  • Administration fee : CHF 2,000.- (Non-refundable)
  • Courses : CHF 3,000 per course
    – 2 courses per term (Bi-monthly payment)
    – 1 course for 5 ECTS*

Graduation requirements

  • Coursework – 60 ECTS* wth average 60% or above
  • Dissertation – 30 ECTS*
    • Tech track: 20,000 words academic essay or equivalent mathematical/programing application
    • Biz track: Case study equivalent to tech track's dissertation
    • 6 months support course (CHF 6,000)

*ECTS – European Credit Transfer and Accumulation System

Scholarship

  • If 70% or above in admission examination
  • RA/TA opportunities
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. Even if you have applied for tech track, if no record of mathematical training is found, the offer letter will be given to biz track.

English requirement
For non-native English speakers, should meet one of the following criteria

For non-native English speakers, should meet one of the following criteria by graduation

  • High school or University level diploma from an all-English program
  • TOEFL iBT 100/120 or above (with each section at least 21/30)
  • IELTS 7 or above (with each section at least 6.5/9)
  • Pass grade from SIAI’s internal English course

 

Internal English course

  • Course fee: CHF800
  • Course schedule
    • July~Aug (8 weeks)
    • Live session
    • 3 hours per week (usually weekend)

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 Forum (Private)


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 Forum 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 Forum 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.