Mitigate AI Business Risk: A Guide for Senior Leaders and Executives
42mGeneral2025-06-20
Authors
Andreas Welsch
Course details
Business leaders are under pressure from their boards and competitors to innovate and boost outcomes using AI. But this can quickly lead to starting AI projects without clearly defined, measurable objectives or exit criteria. In this course, instructor Andreas Welsch outlines the risks of sunk costs and missed opportunities, with practical insights on overcoming complex business challenges related to AI adoption. Learn how to implement proven risk mitigation strategies for starting, measuring, and managing AI projects. Along the way, get tips and techniques to optimize resourcing for projects that are more likely to succeed.
Learning objectives
Recognize the importance of aligning AI projects with business goals to improve success rates.
Identify opportunities where AI can add measurable value to organizational goals.
Evaluate AI projects for strategic alignment and feasibility, ensuring investments are resource efficient.
Prioritize AI projects by establishing criteria based on potential business impact.
Implement a risk mitigation framework to monitor AI project progress, set KPIs, and ensure accountability for desired outcomes.
Learning objectives
Recognize the importance of aligning AI projects with business goals to improve success rates.
Identify opportunities where AI can add measurable value to organizational goals.
Evaluate AI projects for strategic alignment and feasibility, ensuring investments are resource efficient.
Prioritize AI projects by establishing criteria based on potential business impact.
Implement a risk mitigation framework to monitor AI project progress, set KPIs, and ensure accountability for desired outcomes.
Skills covered
AI for Business FoundationsBusiness StrategyArtificial Intelligence for BusinessBusiness Analysis and StrategyLeadership and ManagementOne-Off
Concepts
0. Introduction
- 01 - Recognizing the importance of AI risk mitigation
1. Understanding AI s Business Value Potential
- 02 - Identifying business value opportunities in AI projects
- 03 - Assessing strategic fit and feasibility
- 04 - Prioritizing high-impact AI projects
2. Defining Success Criteria for AI Projects
- 05 - Establishing clear business outcomes
- 06 - Setting key performance indicators (KPIs)
- 07 - Creating a framework for monitoring progress
3. Implementing Governance for AI Projects
- 08 - Building AI project accountability
- 09 - Documenting decision-making processes
- 10 - Identifying common AI project risks
- 11 - Implementing risk control mechanisms
4. Creating an AI Project Exit Strategy
- 12 - Defining exit criteria for AI initiatives
- 13 - Assessing project viability during execution
- 14 - Executing a managed exit strategy
Conclusion
- 15 - Applying AI business risk mitigation
- 16 - Next steps in AI risk mitigation