Artificial Intelligence (AI) for Leaders and Managers

Why Attend

Most organisations no longer ask whether to use AI; they ask which decisions it should support, who owns the results and how to stop pilots from stalling. Those are leadership questions, and this five-day LLMI course is built around them rather than around programming or data science.

Across the week, managers move from understanding what machine learning and generative AI can and cannot do, to choosing use cases with a clear business case, to setting the guardrails that keep AI decisions fair, explainable and compliant. Each day ends with a short leadership exercise, so by Friday every participant has drafted an AI adoption plan for their own department: priority use cases, the data they depend on, the risks to manage and the KPIs that will show whether the investment paid off.

The course suits leaders in government, energy, finance, healthcare and services who need to sponsor AI projects with confidence, question vendor claims and explain AI decisions to boards, regulators and staff. No technical background is required.

Course Objectives

Explain in plain business terms how machine learning, deep learning and generative AI create value, and where they fail

Select and rank AI use cases using value, data readiness, cost and risk criteria

Build a decision framework that combines AI recommendations with human judgement and accountability

Plan and lead cross-functional AI projects from pilot to enterprise-wide roll-out

Identify AI risks such as bias, privacy, security and over-reliance, and set controls for each

Draft an AI governance policy aligned with the organisation's strategy and regulatory environment

Define KPIs and an ROI model to measure the impact of AI initiatives

Lead the cultural change needed for teams to adopt AI tools responsibly

Target Audience

Chief executives, general managers and board members

CTOs, CIOs and digital transformation leaders

Heads of strategy, operations, finance, HR and marketing

Senior and middle managers sponsoring AI or automation projects

Public-sector leaders shaping AI policy and services

Programme and project managers responsible for AI initiatives

Course Methodology

Short expert briefings followed by facilitated leadership discussion

Industry case studies of AI successes and failures across sectors

Live demonstrations of AI and generative AI tools used for analysis and decision support

Group exercises on use-case selection, risk assessment and governance design

A personal AI adoption plan developed day by day and reviewed on the final day

DAY 1 : Unlocking AI’s Power – Transforming Business for the Future

Exploring Cutting-Edge AI Technologies and Innovations

How AI Fuels Disruption and Competitive Advantage

Global AI Adoption Trends Shaping Industries

AI’s Value Proposition: Turning Data into Business Insights

Defining Success: Key Metrics for AI-Driven Growth

DAY 2 : Mastering AI – Tools and Strategies for Professionals

Demystifying Machine Learning and Deep Learning

Navigating the AI Ecosystem: Essential Tools and Platforms

AI in Action: Enhancing Productivity and Problem-Solving

Data-Driven Strategies for Smarter Decision-Making

Real-World Success Stories: AI Transformations Across Industries

DAY 3 : AI-Powered Leadership – Driving Smart Decisions

Building Intelligent Decision-Making Frameworks

Leadership in the AI Era: Strategies for Seamless Adoption

Managing AI-Driven Projects Across Teams and Functions

Ethics, Compliance, and Trust in AI Implementation

Leading with AI: Lessons from Successful Industry Leaders

DAY 4: AI Risk & Governance – Balancing Innovation with Responsibility

Identifying and Controlling AI-Related Risks

Tackling AI Bias, Fairness, and Transparency Challenges

Crafting Robust AI Governance and Compliance Policies

Aligning AI Strategies with Long-Term Business Vision

Tools for Ensuring AI Integrity and Performance Monitoring

DAY 5 : The AI-Driven Future – Scaling Innovation and Impact

Building a Culture of AI-First Thinking and Innovation

Bridging the Gap: Collaboration Between AI Experts and Teams

Scaling AI Solutions for Enterprise-Wide Impact

Measuring AI ROI: Proving Value and Driving Continuous Growth

The Next Frontier: Emerging Trends Shaping the Future of AI