Day 2 (16 June 2026) - WorkshopsTuesday, 16 June 2026 - AT (Arabian Time, GMT+03:00)

Mindset and Culture

• Addressing the skills gap in the age of AI
• Preparing for the future landscape of HR
• Cultivating psychological safety and encouraging experimentation

Practical Implementation of GenAI for HR

• Myth-busting common misconceptions about AI
• Understanding and applying prompt engineering in HR contexts

Getting Started with AI in HR

• Defining a clear AI strategy for HR initiatives

Morning Learning Sessions

• Understand the difference between AI maturity and readiness
• Assess your organisation’s capabilities and identify key enablers

Interactive Knowledge Check (Individual Participation)

Engage in a short, instructor-led dialogue that revisits core readiness concepts. You will answer questions in real time, drawing on examples from your own organisation to connect theory with practice.

Continued Morning Learning

• Explore cultural, technical, and governance factors that influence readiness
• Learn how to sustain readiness and manage risk across transformation phases

Interactive Team Challenge

Work in groups to tackle practical readiness scenarios guided by the Instructor. Teams will discuss, prioritise responses, and present their thinking in a fast-moving format designed to build both confidence and clarity.

Lunch Break

Afternoon Practice & Collaboration

• Develop a tailored AI Readiness Assessment Document using CXO Transform templates and IntelliPrompts
• Validate and refine your assessments through guided dialogue with the AI Discussion Partner
• Create an actionable readiness improvement plan highlighting key enablers
• Conclude with a reflection linking readiness findings to Day 3’s focus on roles

Optional Evening Homework

You can take an online readiness test covering Day 2 material to deepen understanding and strengthen exam preparation.

Theme: Understand how trusted data and effective governance frameworks underpin every successful and accountable AI initiative

Session 1: Data as the Strategic Fuel of Intelligence

• How AI transforms raw data into insight and prediction?
• Understanding structured, unstructured, and personal data ecosystems
• Why decision quality depends on data quality?
• Business cases where weak data governance undermined AI outcomes

Session 2: Establishing Robust Data Governance

• Core principles: ownership, quality, access, lifecycle management
• Defining roles and accountability across data stewardship functions
• Aligning data strategy with organisational objectives and compliance expectations

Session 3: Managing Bias, Privacy, and Fairness

• How imbalance and human assumptions enter datasets and models?
• Practical approaches to detect, reduce, and monitor bias
• Transparency and explainability as enduring pillars of trust

Session 4: Governance in Practice

• Translating principles into project governance frameworks
• Setting measurable objectives, controls, and documentation standards
• Ensuring cross-functional oversight between technical, legal, and operational teams

Activities:


1. Data Chain: Delegates visualise how data moves through an organisation and where governance responsibilities sit
2. Data Detective: Teams identify problems in fictional datasets (bias, duplication, missing data)
3. Trust Factors Mapping: Participants explore what builds or erodes confidence in AI decision making
4. AI Governance Checklist – What questions leaders should ask when working with AI

• Global and regional success stories in smart city innovation
• IoT-enabled energy and mobility systems
• Healthcare transformation through AI and data integration
• Lessons learned and transferable practices