AI in Business: for C-Level Executives and Managers

This course is designed for C-level executives, senior managers, and business leaders who are responsible for driving strategic decisions in their organizations. It is ideal for those seeking to understand how AI can be leveraged to enhance business outcomes, improve operational efficiency, and navigate the challenges of AI adoption at scale.

Objectives

1. Understand the key AI technologies and developments relevant to business leaders.
2. Identify and evaluate opportunities where AI can improve productivity, decision-making, customer experience and business performance.
3. Assess AI use cases based on potential business value, feasibility and risk.
4. Understand the capabilities and limitations of generative AI and AI assistants in the workplace.
5. Build a business case for prioritised AI initiatives and consider potential return on investment.
6. Recognise the key data, privacy, security, regulatory and ethical considerations involved in AI adoption.
7. Assess organisational readiness and identify the people, technology and governance requirements for successful AI implementation.
8. Lead AI adoption by addressing capability, culture, communication and resistance to change.
9. Develop priorities and practical next steps for an AI roadmap within their organisation.

Day 1: AI Strategy & Business Value — 4 hours

1. AI for Business: What Leaders Need to Know

• AI, machine learning and generative AI: what they are and what they are not
• The current AI landscape and key developments
• Where AI can create competitive advantage
• Opportunities and limitations of AI for organisations

2. Identifying High-Value AI Use Cases

• Where AI can improve productivity, customer experience and decision-making
• Examples across functions: finance, HR, marketing, operations and customer service
• From business problem to AI use case
• Evaluating potential impact, feasibility and risk

3. Generative AI in Practice

• What today’s AI tools can realistically do
• Practical examples of LLMs and AI assistants in the workplace
• Demonstrations: research, summarisation, content creation, analysis and workflow support
• Where AI can augment people rather than simply automate tasks

4. From AI Ideas to Business Value

• Prioritising AI opportunities
• Building the business case
• Understanding AI investment and ROI
• Executive discussion: Which AI opportunities should we pursue?

Practical activity: Participants identify and prioritise 2–3 AI use cases relevant to their organisation.

Day 2: Implementing AI Responsibly — 4 hours

1. From AI Strategy to Implementation

• What successful AI adoption requires
• Assessing organisational readiness
• Choosing between experimentation, piloting and scaling
• Building an AI implementation roadmap

2. AI Governance, Risk & Responsibility

• Data quality, privacy and security
• Bias, fairness and transparency
• Responsible use of generative AI
• Regulatory and compliance considerations
• Establishing appropriate governance and controls

3. People, Leadership & AI Adoption

• How AI changes the way teams work
• Building AI capability across the organisation
• Leadership’s role in successful adoption
• Managing resistance and encouraging responsible experimentation
• Creating an AI-ready culture

4. Executive AI Roadmap

• Defining priorities and next steps
• Selecting the right initiatives
• Identifying people, technology and governance requirements
• Measuring success
• Developing a 90-day AI action plan

Practical activity: Participants develop a high-level AI roadmap/action plan for their organisation.