Skip to main content
  • Home
  • Executive AI Forum - Dubai

Executive AI Forum in Dubai

Where AI, capital, and institutional judgment converge

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

Across industries, AI is often discussed as if its strategic direction were already settled—technologies selected, systems deployed, and outcomes assumed. In practice, however, many organizations continue to face gaps between ambition and execution, particularly where AI intersects with legacy infrastructure, organizational processes, and long-term capital planning.

The Executive AI Forum in Dubai is convened in response to this reality. It brings together senior leaders who must evaluate AI not as a standalone technology initiative, but as part of a broader system encompassing industrial structure, governance capacity, and long-horizon decision-making.

This forum is neither a training program nor a product showcase, and it differs fundamentally from conventional academic or industry conferences. It is designed as a closed, analytical setting in which participants examine AI from first principles—economic constraints, statistical limits, organizational incentives, and recurring implementation failures that are often underrepresented in public discussions. The objective is not to promote adoption, but to enable more accurate strategic judgment about where AI meaningfully contributes to productivity, resilience, and institutional continuity.

The Dubai forum is organized around two complementary components: the Executive Track and a Conference Session. While distinct in format, both address the same core questions at the intersection of AI, capital allocation, and institutional responsibility. Together, they provide a structured environment for senior participants who oversee strategy and execution, and who carry accountability for long-term outcomes rather than short-term technological experimentation. Earlier Zurich event's Council Track participants are invited to a separate event at Saadiyat.

The Executive Track is held during the final week of December, followed by a single-day Conference Session on the final day of the program.

Executive track

The Executive Track is structured as a guided exposure to real-world AI deployment across industrial and institutional contexts relevant to the Japanese economy. Rather than focusing on technical instruction, the track emphasizes observation, contextual explanation, and strategic interpretation—supporting executives who must integrate AI into complex organizations with established processes, workforce structures, and regulatory considerations.

Similar in spirit to executive inspection programs used in advanced manufacturing and infrastructure policy, the track centers on how AI systems operate in practice. Participants engage through briefings, site-anchored discussions, and applied case perspectives, developing the ability to assess implementation claims, operational risks, and organizational readiness at the level of executive decision-making.

Selected Executive Track participants are invited to closed dinner discussions held alongside the program. These sessions are designed to facilitate candid exchange among senior peers under conditions of discretion, with a focus on shared challenges in governance, coordination, and long-term execution.

Conference Session

The Conference Session is a one-day convening held on the final day of the Executive Track. It brings together forum participants and invited speakers for a focused exchange on structural themes emerging from the week’s discussions.

While more open in format than the Executive Track, the conference maintains the same analytical orientation. Presentations and discussions emphasize system-level perspectives on AI—covering capital investment cycles, institutional adaptation, and policy coordination—rather than short-term trends or vendor-specific solutions. Selected regional experts will be invited for though-provoking idea sharing and event analysis within the region.

Together, the Executive Track and Conference Session form a cohesive forum that supports informed judgment on AI as an element of long-term industrial and institutional strategy.

The Conference Session is open to the public and free of charge for all visitors.
Attendance is subject to venue capacity and advance registration. The Executive Track remains invitation-only and is separate from the Conference Session.


Executive AI Track

at a glance

COUNCIL TRACK

3-5 DAY EVENT

EXECUTIVE TRACK

AI AT CONTROL LEVEL

CONFERENCE SESSION

BUSINESS ORIENTED

Dubai event

EXECUTIVE TRACK FOR CASE STUDIES, BUSINESS APPLICATIONS, AND INSIGHTS

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.