About
Despite significant investment in artificial intelligence, many enterprise AI initiatives fail to deliver meaningful business value. This course equips participants with the strategies to move AI from experimentation to scalable results.
Grounded in APQC’s research and real-world best practices, the course examines the most common reasons efforts stall, including misaligned strategy, weak data and process foundations, and organizational resistance, and provides practical ways to address these challenges. Participants will learn how to align AI with business goals, identify high-value use cases, strengthen data and process readiness, and lead the change required for successful adoption.
Through guided discussions and hands-on activities, participants will assess readiness, prioritize initiatives, and develop actionable plans to support sustainable adoption across the organization. By the end of the course, participants will be prepared to lead AI initiatives that deliver impact, reduce risk, and support long-term innovation.
Target Audience
- Business leaders, executives, and functional heads responsible for driving AI or digital transformation initiatives
- Strategy, innovation, and transformation professionals tasked with identifying and scaling new capabilities
- Product leaders, program sponsors, and project owners overseeing AI use cases and implementation
- Managers bridging business and technical teams who need to guide AI efforts without deep technical expertise
You Will Learn
- Analyze common causes of underperformance in enterprise AI initiatives and distinguish patterns associated with low-impact outcomes
- Define AI use cases and construct problem statements aligned to specific business and operational objectives
- Assess the readiness of organizational data and process foundations to support AI implementation
- Evaluate the impact of AI on workflows, roles, and responsibilities and determine required adjustments
- Apply leadership and change management practices to support effective AI adoption
- Develop practical action steps to prepare teams and stakeholders for AI-
enabled ways of working