Organisations face numerous challenges when evaluating investments in AI initiatives, including uncertainty about their potential value, difficulty prioritising use cases, and navigating the complexities of operational integration, data readiness, and ethical concerns. Without a structured approach, organisations risk making misaligned investments that fail to deliver meaningful impact and outcomes.
This course tackles these challenges by providing participants with practical AI use case evaluation frameworks that enable a systematic and holistic assessment of AI initiatives. Through real-world examples and case studies, participants will learn to evaluate, prioritise, and select AI use cases based on factors such as return on investment, strategic alignment, data and model requirements, integration complexity, operational impacts, and legal and ethical considerations. This structured approach ensures informed and effective decision-making for AI adoption in both public and private sector organisations.
By the end of this course, participants will be able to:
- Identify and prioritize AI use cases based on organizational needs.
- Assess the technical, operational, and financial feasibility of AI solutions.
- Evaluate value creation through ROI, strategic alignment, and business impact analysis.
- Apply frameworks to justify and prioritise AI investments.
- Communicate AI use case evaluations effectively to stakeholders.