CAS AI Use Case & Business Validation

The CAS is designed for specialists and executives from companies and organizations who wish to implement AI but have little to no experience in executing concrete AI projects. It specifically targets individuals from business units, as well as project and product managers and decision-makers who prepare, evaluate, or oversee AI initiatives.

No advanced technical knowledge is required as a prerequisite. The focus is on methodological competencies for informed decision-making, rather than the technical implementation of AI models.

After completing this CAS in Artificial Intelligence (AI) Use Case & Business Validation, participants will be able to:

• Identify and Define AI Opportunities: Systematically spot relevant AI use cases within their organization and formulate them clearly, avoiding vague or overly ambitious definitions.
• Validate Business Value: Rigorously assess the potential business impact and ROI of AI initiatives before any significant technical investment is made.
• Assess Feasibility and Risk: Evaluate the practical feasibility of AI projects and conduct systematic risk analyses regarding data quality, ethics, and implementation challenges.
• Bridge the Gap Between Strategy and Execution: Make informed, evidence-based decisions on whether to proceed, pivot, or halt AI projects, directly addressing the common causes of early-stage AI failure.
• Apply Structured Methodologies: Utilize proven frameworks to navigate the early, critical phases of the AI lifecycle, ensuring that business problems are correctly analyzed and matched with appropriate AI solutions.

Ultimately, participants will gain the methodological competence to lead AI initiatives with confidence, ensuring that resources are only committed to projects with a validated business case and a clear path to success

• Identify and structure AI use cases derived from complex business problems
• Systematically evaluate the suitability of business challenges for AI implementation
• Apply structured methodologies for precise problem definition and solution formulation
• Utilize critical thinking and analysis to assess opportunities and risks effectively
• Communicate use cases clearly to stakeholders through oral and written presentations
• Collaborate in teams to bridge perspectives between business units and technology experts

• Validate AI use cases by assessing business value, feasibility, and risks within organizational contexts
• Apply structured frameworks to evaluate the viability of AI initiatives and develop evidence-based Go/No-Go recommendations
• Utilize critical thinking and data analysis to solve complex problems and formulate robust validation strategies
• Communicate validation results and strategic recommendations effectively to diverse stakeholders in oral and written formats
• Collaborate in interdisciplinary and international teams to analyze real-world cases and bridge differing perspectives
• Demonstrate self-reflection and ethical responsibility when making high-stakes decisions regarding AI implementation