Executive Course · 6 Hours · 6 Modules

Making Data & AI Work

Why initiatives fail — and how to design for success

20, 22 & 24 September 2026 · 6:00–8:00 PM Kuwait Time · Virtual

200 KWD 90 KWD pilot cohort price
Join the Priority List Download Course Overview
Why This Course Exists

This is the course we wish we'd had earlier in our careers.

Built from more than a decade of experience across banking, Data & AI delivery, research and advanced study. It brings together the lessons that usually take years to learn.

We spent years learning them the hard way. You don't have to.

You'll leave with a practical framework: spot what goes wrong, know what to question, and design initiatives for success.

Audience

Who It's For

Designed for leaders and senior professionals involved in Data & AI initiatives — from sponsors and governance stakeholders to the practitioners delivering them.

Leaders & Non-Technical Stakeholders

Build the shared language and judgement to sponsor, challenge and govern Data & AI initiatives—without needing to master the technical details.

Data & AI Practitioners

Develop a broader view of what makes Data & AI initiatives succeed beyond the technology itself.

What You'll Gain

What You'll Leave With

Pre-Commitment Checklist

Better questions before committing

Diagnostic questions on scope, ownership and readiness, to ask before resources are committed.

Maturity Framework

A clearer view of where you stand

A structured way to assess your organisation's Data & AI maturity.

One-Page Approval Artefact

A stronger basis for what moves forward

A ready-to-use template for structuring and evaluating your next Data & AI initiative.

Course Structure

Six Modules

How enterprise data actually flows — from source systems to reports, dashboards, and AI.

A shared mental model of how enterprise data actually flows — from source systems, through pipelines and warehouses, to the reports, dashboards, and AI outputs. Maps the data stack layer by layer, clarifies who owns each layer, and contrasts the two common ways organisations build it out: bottom-up, one department at a time, versus top-down with full enterprise coverage from day one.

Understanding why initiatives that look simple on paper become unexpectedly complex in practice.

A real enterprise example tracing how complexity actually grows — from proof of concept to a fully governed platform — and why most initiatives get approved at the wrong stage. Leaves you a set of diagnostic questions for sizing initiatives honestly before committing budget.

Identify and name the patterns through which data and AI initiatives fail.

Names three failure patterns behind data and AI initiatives, moving past "poor execution" explanations: a data foundation failure, an organisational structure failure, and a human incentive failure — grounded in recognisable enterprise-setting scenarios.

A structured, honest assessment of where your organisation sits today and what it takes to advance.

A structured, honest maturity assessment. Places your organisation on a five-level maturity ladder — from fragmented and reactive to a full data/AI operating model — scored across five dimensions including governance, ownership, and AI lifecycle. A guided self-assessment exercise gives you a shared, defensible read of where you actually stand.

A practical decision framework for designing data and AI initiatives that succeed.

The course's decision framework: three gates — Should This Exist?, How Do We Build It?, and Are We Ready to Run It? — each designed to catch failure before it happens. You leave with a one-page approval artifact and the language to say no to initiatives that shouldn't move forward.

Providing a practical framework for evaluating GenAI's opportunities and risks.

A practical understanding of Generative AI for evaluating its opportunities and risks with a structured approach. Covers the fundamentals of modern GenAI, governance considerations, and evaluation techniques through real-world examples and hands-on activities.

Positioning

Why This Course Is Different

Go beyond awareness to build the judgement needed for real Data & AI decisions.

High Decision-Making Depth
Low High
Generic Awareness Broad, conceptual
Technical Training Deep, but narrow
Making Data & AI Work Applied decision-making depth
Technical Depth
Course Instructors

Learn From Practitioners

Built from real delivery experience — not theory, not vendor frameworks, and not isolated use cases.

Abdulrahman AlQallaf

Abdulrahman AlQallaf

Data & AI Consultant | Founder, Tatra Insight
linkedin.com/in/abdulrahman-alqallaf

12 years building Data & AI capabilities across leading banks in Kuwait.

National Bank of Kuwait, Boubyan Bank, and Gulf Bank. Built Kuwait's first AI-powered banking recommendation and spending-insights features at Boubyan Bank, and led enterprise data strategy at Gulf Bank.

Dr. Ahmad Alobaid

Dr. Ahmad AlObaid

AI Researcher & Consultant | Founder, RunzBuzz
linkedin.com/in/ahmadalobaid

PhD in AI with international public- and private-sector delivery experience.

PhD in AI, Universidad Politécnica de Madrid, with a Master's in Statistics from Universidad Carlos III de Madrid. AI researcher with hands-on experience across international public and private sector projects, including consulting for the European Commission in Brussels.

Open Enrolment

Register Your Interest

20, 22 & 24 September 2026 · 6:00–8:00 PM Kuwait Time · Virtual

200 KWD 90 KWD pilot cohort price

Joining the priority list gets you early access to secure your seat before booking opens to the public. If demand exceeds capacity, remaining seats are offered in order of registration.

Download Course Overview (PDF)

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