Riyadh, KSA
Day 3 (17 June 2026) - Workshops - AT (Arabian Time, GMT+03:00)
Module 1 – AI Fundamentals for PM Work
Topics
- What an LLM is/does (practical mental model)
- Safe-use for PM content (confidentiality + redaction)
- Prompt structure: Task + Context + Constraints + Output format + QA
- Prompt precision (“missing details” = wrong outcome)
- Micro-demo: turn messy notes into a clean PM update
Capstone Step1 : Providing Entity Context and Challenges
Exercise: Map your daily work activities, data sources, and stakeholders to frame your AI use case.
Module 2: PM Workflow Frictions + AI Opportunity Mapping
Topics
- Choosing the right PM workflow (high-frequency, high-friction)
- Workflow deconstruction (steps, owners, handoffs)
- Opportunity mapping: where AI supports PM work (drafting, synthesis, QA, coordination)
- Risks/constraints (policy, data, approvals)
- Define “before vs after” success measures
Capstone Step 2: Define the Problem Statement
Exercise: List and prioritize your team’s top three AI-ready pain points as challenge statements.
Module 3: Problem Statement + Use Case Brief
Topics
- Problem statement: specific, measurable, owned
- Inputs/outputs: what the LLM will receive + produce
- Constraints: what can’t be shared, what must be approved
- Acceptance criteria: what “good” looks like
- Quick peer critique loop
Capstone Step: Ideation and Selection
Exercise: Using the 4-dimension canvas, plot current vs. AI-enhanced state for one core process.
- Frederik Haentjens - Workshop Leader & AI Strategist, Boxology
Morning Learning Sessions
- Examine executive, managerial, and technical roles in enterprise AI
- Understand accountability structures, governance layers, and ethical oversight
Interactive Knowledge Check (Individual Participation)
Take part in a facilitated question and answer session that explores the dynamics of leadership, accountability, and governance. You will be encouraged to reflect and share real-world experiences from your organisation.
Continued Morning Learning
- Learn how to establish and scale AI Centres of Excellence
- Explore how evolving roles support organisational transformation
Interactive Team Challenge
Participate in a collaborative group exercise where you respond to leadership and governance scenarios. Each team will propose how to clarify roles or resolve conflicts, leading to valuable discussion and shared learning.
Lunch Break
Afternoon Practice & Collaboration
- Build a Roles & Responsibilities Matrix using CXO Transform templates and IntelliPrompts
- Engage with the AI Stakeholder Simulator to explore influence and alignment challenges
- Work with the AI Career Strategist to explore evolving leadership roles and capability pathways
- Integrate outputs into an enterprise governance framework ready for implementation
Optional Evening Homework
You may complete an online test to reinforce learning and prepare for the certification exam.
- Rob Llewellyn - Founder & CEO, CXO Transform
Theme: Examine the global standards, regulatory expectations, and risk management practices that turn compliance into strategic assurance
Session 1: From Governance to Assurance
- How governance structures underpin regulatory compliance?
- Connecting ethical intent, data integrity, and assurance frameworks
- Viewing compliance not as a constraint, but as a strategic protection and differentiation
Session 2: The Global Regulatory Environment
- Overview of emerging frameworks: ISO/IEC 42001, UK GDPR, OECD AI Principles, EU AI Act
- Clarifying organisational accountability and chain of responsibility
- Regional trends shaping future compliance in the GCC, UK, and EU contexts
Session 3: Risk and Assurance in Intelligent Systems
- Key categories of AI risk: ethical, operational, reputational, and cybersecurity
- Designing proportionate controls, documentation, and audit trails
- Building a culture of informed risk ownership across leadership functions
Session 4: Operationalising Compliance
- Integrating AI oversight into existing corporate governance models
- Creating alignment across Legal, IT, HR, and Compliance teams
- Turning regulatory excellence into a competitive and reputational advantage
Activities:
- AI Compliance Challenge: Teams review a fictional AI rollout and identify compliance and privacy gaps
- AI Risk Radar: Groups map top AI risks and brainstorm practical controls
- Policy Builder: Participants design a short “AI Code of Conduct” template suitable for their organisation
- Approval Line: From a scenario, delegates discuss which organisational roles should be involved in approving or halting an AI project
- Darren Winter - Co-Founder of Duco Digital, Duco Digital Training
- The flow of data across connected environments
- Turning real-time insights into action and design decisions
- Predictive, personalised, and proactive experiences
- Frameworks for mapping data-to-experience ecosystems
- Hadi Aridi - Innovation Consultant, Informa Connect
- Deep learning in time series forecasting
- Introducing neural network
- Recurrent Neural Networks (RNN)
- Long Short-Term Memory (LSTM) networks
- Hands-on case studies
- Reusing saved models
- Saving models locally
- Importing saved models
- Using models for forecast
- Hands-on case studies
- RNN and LSTM case studies using live data
- Performance analysis using Lo-Code ML
- Downloading live annual performance data
- Conducting automated ratio analysis
- Using downloaded data in Lo-Code ML and Excel™
- Automated valuation using Lo-Code ML
- Mark To Market (MTM) analysis of portfolio
- Visualising portfolio performance
- Hands-on case studies
- Arif Ahmed - Director, South-Asian Management Technologies
- Veena Hingarh - Joint Director, South-Asian Management Technologies