study

This course is designed for:

• Leaders and managers responsible for setting direction, governance and oversight for AI use
• Decision-makers seeking to understand the capabilities, limitations and opportunities of AI.
• Leaders responsible for evaluating and overseeing AI adoption within their organisation.
• Organisations at the beginning of their AI journey looking to develop a strategic and responsible approach to implementation.

Day 1: Leading AI Transformation

Explore the leadership responsibilities involved in AI adoption, including organisational culture, change management, ethics, wellbeing and sustainability. Participants will examine the role of AI strategy in driving successful transformation.

Day 2: Building an AI Strategy

Learn how to develop a robust AI strategy aligned with organisational vision, values and objectives. Topics include governance, policy development, capability planning, data and technology considerations.

Day 3: Identifying Opportunities

Discover how to identify high-value opportunities for AI and automation, assess potential benefits and risks, and begin developing evidence-based business cases for investment.

Day 4: From Strategy to Action

Focus on implementation planning, including feasibility assessments, cost-benefit analysis, pilot methodologies, solution evaluation and stakeholder engagement.

Day 5: Future-Proofing Your AI Strategy

Explore approaches to measuring success, monitoring governance and compliance, managing unintended consequences, and continuously evolving your AI strategy to respond to future developments.

By the end of the course you will be able to:

1. Provide organisational leadership in setting AI policy and strategy. Including business cases, detailing implications for the workforce, organisational perception and sustainability to inform decision making.
2. Evaluate opportunities for AI-driven improvement using qualitative and quantitative evidence, including the assessment of risk.
3. Define, document and communicate an AI strategy aligned to organisational goals, values and risk appetite.
4. Assess viability and risk through AI use cases and pilots, identifying investment areas balancing productivity gains against feasibility, impact and organisational readiness.
5. Engage stakeholders to build support for AI strategy and adoption, including non-technical audiences.
6. Critically evaluate and monitor. Implementing adaptations, including responses to emerging AI technologies and trends.

Each day combines expert-led teaching with practical application and discussion. Sessions typically include: 

• Interactive activities and discussions 
• Expert briefings and theory 
• Real-world case studies 
• Industry guest speakers 
• Practical workshops 
• Action planning and workplace application exercises 

This approach ensures participants can immediately apply their learning within their own organisation. 

Participants are required to complete a short skills assessment at the end of day five consisting of short-answer questions to demonstrate the knowledge and skills gained during the course.