Leading Successful Enterprise AI Initiatives
Course Description
This course helps organizations move enterprise AI efforts beyond experimentation and toward consistent, measurable results. Participants will examine why many AI initiatives stall or fail and learn how to position AI as a core business capability rather than a standalone technology project. Drawing on APQC research and practical examples, the course focuses on using AI to solve real business problems, strengthening data and process foundations, and preparing people for new ways of working. Interactive discussions and activities enable participants to evaluate AI readiness, prioritize high-value use cases, and apply proven practices that support sustainable AI adoption across the organization.
Learning Outcomes
By the end of this course, participants will be able to:
- 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
Audience
- Process Improvement and Operational Excellence Professionals who want to leverage AI to improve processes, productivity, and decision-making.
- IT and Data Professionals supporting AI infrastructure, governance, and data readiness.
- Program and Project Managers leading cross-functional AI initiatives.
- Business Unit Leaders and Managers responsible for identifying high-value AI use cases within their teams.
As an IACET Accredited Provider, APQC offers a range between .4 and .8 CEUs for this course that comply with the ANSI/IACET Continuing Education and Training Standard.
Syllabus
-
- Intro
- Completion requirements
- Logistics/Guidelines
- Topic Overview/Agenda
- Learning outcomes
-
- Describe the current state of enterprise AI adoption
- How AI expectations differ from realized value
- Characteristics of effective enterprise AI use
- Quiz
-
- How unclear strategy undermines AI initiatives
- Risks of technology-driven AI efforts
- Organizational barriers to successful AI adoption
- Quiz
- Discussion
-
- How to identify high-value AI opportunities
- How to define success measures for AI initiatives
- How to align AI initiatives with organizational strategy
- Approaches for piloting and scaling AI solutions
- Quiz 2
- Discussion
-
- The role of data quality and governance in AI
- How process clarity affects AI performance
- The role of leadership and governance in sustaining AI efforts
- Why foundational issues must be addressed before automation
- Quiz 3
- Activity 3
-
- How AI changes work, roles, and workflows
- Best practices for managing change and building skills
- The role of leadership and governance in sustaining AI efforts
- How to embed AI as a long-term organizational capability
- Quiz
- Activity 3
-
- Wrap-Up
- Additional Resources
- Thank You and wrap-up
- Close Out Video
- Course Evaluation