Making Data & AI Work

80%

Time Lost to Bad Data

80% of data scientists' time is spent on data quality issues,
not building machine learning models.¹

20%

Revenue Lost to Bad Data

20% of revenue is lost to data that was never right at the source.¹

Most Data & AI initiatives don't fail because of technology — they fail because they lack clarity: no shared understanding of how enterprise data actually works, no clear view of complexity and common failure patterns, and no reliable way to assess maturity and know what is needed to advance to the next stage. This course builds that clarity and provides a practical framework for building initiatives that succeed.

¹ Redman, T.C., "Seizing Opportunity in Data Quality," MIT Sloan Management Review, 2017.

Audience

Who It's For

Designed for leaders and senior professionals who sponsor, approve, govern or deliver Data & AI initiatives.

Best suited to assistant manager level and above, or equivalent.

Leaders & Non-Technical Stakeholders

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

Data & AI Practitioners

Connect delivery decisions with business priorities, governance requirements and leadership expectations.

Course Structure

Six Modules

01

Foundations

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

02

The Complexity Gap

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

03

Patterns of Failure

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

04

Where Are You Today?

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

05

How to Design for Success

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

06

Generative AI in Practice

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

Grounded in Practice

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

You Leave With

Clarity and an honest assessment of where your organisation stands today.
A practical framework for designing what's next.

Positioning

Why This Course Is Different

Generic Awareness Courses

Broad introduction to Data & AI concepts. Builds awareness, but limited operational depth.

Technical Training & Certifications

Deep focus on tools and methods. Builds technical skill, but skips governance and decision-making.

This Course

Applied governance depth, built for sponsors, leaders, and practitioners. Builds judgment and a shared decision framework.

Course Instructors

Learn From Practitioners

Abdulrahman AlQallaf

Senior Data & AI Professional

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

AI Expert

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.

Schedule This Course

Bring a shared Data & AI decision framework to your organisation

Download Course Overview (PDF)