Training Course: Integrated generative artificial intelligence for leaders and supervisors: Data-driven leadership and digital transformation – Riyadh (KSA), 13–17 Dec 2026

Introduction:

Integrated generative AI for leaders and supervisors is the use of generative artificial intelligence, such as large language model assistants, across a leader's everyday work: analysing data, preparing decisions, communicating with teams and steering digital transformation in a unit. This one-week course is for leaders, supervisors, team leaders, department heads and professionals moving into supervisory roles, and each delegate leaves with an AI-enabled leadership and adoption roadmap for their own unit. It is taught at practitioner level with no coding required, combining short briefings with practical exercises every day on real management tasks and closing with a capstone workshop on responsible AI adoption.

Course Objectives:

• Explain how generative AI differs from traditional AI and how large language models produce answers, including their capabilities and limits
• Write structured prompts that turn AI assistants into reliable support for reports, analysis, summaries and team communication
• Apply AI to data analysis, forecasting, SWOT and scenario analysis to support data-driven strategic decisions
• Design KPIs that measure the value, adoption and risk of AI initiatives in a unit
• Lead teams through AI-driven digital transformation by closing skills gaps, managing resistance and building human–AI collaboration
• Develop an AI use policy and an adoption roadmap that address ethics, privacy, compliance and risk

Target Audience:

• Leaders and senior managers who set direction for a function and decide where generative AI should and should not be used
• Supervisors and team leaders who organise daily work and decide which tasks AI assistants can support and how outputs are checked
• Department heads who own budgets and performance and decide which AI initiatives to fund, pilot or stop
• Specialists and professionals moving into supervisory roles who must judge how far to rely on AI analysis when preparing recommendations
• Digital transformation, strategy and performance staff who shape AI adoption plans and decide how progress and risk are measured

Course Outline:

Day 1: Generative AI Fundamentals for Leaders and Supervisors

• Traditional AI vs Generative AI: Prediction and Classification Compared With Content Generation
• How Large Language Models Work: Training Data, Tokens, Probability and Context Windows Without the Maths
• Capabilities and Limits: Hallucinations, Bias, Outdated Knowledge and When Human Judgement Must Decide
• Leadership Opportunities: Efficiency, Insight, Innovation and Better Employee and Customer Experience
• Practical Exercise: Mapping Current Unit Tasks to AI Opportunity and Risk Levels

Day 2: Strategic Prompting and AI Assistants for Management Work

• Prompt Structure for Leaders: Role, Context, Task, Format and Constraints
• AI Assistants as Examples: Gemini, ChatGPT and Copilot Compared for Everyday Management Tasks
• Reports and Summaries: Drafting Performance Reports, Briefing Notes and Meeting Summaries With AI
• Communication Support: Team Messages, Change Announcements and Stakeholder Updates Reviewed by the Leader
• Practical Exercise: Weak vs Strong Prompts and Iterative Refinement of a Management Report

Day 3: AI-Supported Data-Driven Decisions and Strategic Planning

• Data-Driven Leadership: Moving From Intuition-Only Decisions to Evidence-Based Choices
• AI-Assisted Data Analysis: Trends, Patterns and Anomalies in Operational and Performance Data
• Forecasting and Scenario Analysis: Testing Best, Expected and Worst Cases With AI Support
• SWOT and Risk Assessment: Generating, Challenging and Prioritising Strategic Options
• Practical Exercise: Defining KPIs and a Decision Brief for a Unit Strategic Initiative

Day 4: Leading Teams and Digital Transformation in the Age of AI

• Skills Gap Analysis: Assessing Team AI Literacy and Planning Targeted Upskilling
• Human–AI Collaboration: Deciding Which Tasks to Automate, Augment or Keep Human
• Change Management: Handling Resistance, Fear of Job Loss and Communicating the Case for Change
• Innovation Culture: Safe Experimentation, AI Pilots and Learning From Failed Trials
• Practical Exercise: Building a Change and Communication Plan for an AI Pilot

Day 5: Responsible AI, Governance and Capstone Adoption Roadmap Workshop

• AI Ethics Principles: Transparency, Accountability, Fairness and Human Oversight
• Data Privacy and Confidentiality: What Information Must Never Be Entered Into Public AI Tools
• AI Use Policy and Governance: Approved Tools, Roles, Review Steps and Compliance Checks
• AI Risk Management: Risk Register, Controls and Escalation for AI-Supported Work
• Capstone Workshop: Each Team Builds and Presents an AI Adoption Roadmap for Its Unit

Skills You Will Gain:

• Generative AI Literacy
• Strategic Prompt Writing
• AI-Assisted Reporting
• Data-Driven Decision Making
• Scenario and SWOT Analysis
• AI KPI Design
• AI Change Leadership
• AI Governance and Risk Control

Why Attend This Course:

• From seeing generative AI as a technical topic for IT to using it confidently in daily leadership and supervisory work
• From vague one-line requests to AI tools to structured prompts that produce reports and analysis worth acting on
• From decisions based on habit and intuition to choices supported by AI-assisted data analysis, scenarios and clear KPIs
• From scattered, unmanaged AI experiments to an AI-enabled leadership and adoption roadmap with policy, roles and risk controls

Conclusion:

Generative AI changes how leaders gather evidence, prepare decisions and guide their teams, but its value depends on leaders who know where it helps, where it misleads and how to govern its use. The course makes clear how generative AI differs from traditional AI, how a strong prompt differs from a weak one, and how AI-supported analysis differs from a final human decision. It suits leaders, supervisors, team leaders, department heads and professionals moving into supervisory roles who want one connected method for prompting, data-driven decisions, team transformation and responsible AI governance.

Frequently Asked Questions (FAQ):

Do delegates need technical or coding skills for a generative AI for leaders course?

No. The course works at a non-technical level and needs no coding. Delegates should be comfortable using everyday office software and bring examples of their own reports, decisions and team tasks, which feed the practical exercises each day.

Which AI tools are used in generative AI training for leaders and supervisors?

General-purpose AI assistants such as Gemini, ChatGPT and Copilot are used as examples. The prompting methods, decision techniques and governance steps are tool-neutral, so delegates can apply them to whichever approved AI assistant their organisation uses.

How does generative AI support data-driven leadership?

Generative AI helps leaders summarise data, spot trends, compare scenarios and draft decision briefs far faster than by hand. The leader still checks the evidence, questions the output and makes the final call, using KPIs to track whether decisions deliver the expected results.

What do delegates take back from a generative AI for leaders course?

Each delegate takes back an AI-enabled leadership and adoption roadmap for their unit: priority use cases, a prompt library for management tasks, KPIs for AI initiatives, a change and communication plan, and AI use policy points covering privacy, review steps and risk controls.