Certified AI Program Manager (C|AIPM) Training

The Certified Artificial Intelligence Program Manager (C|AIPM) by EC-Council is a globally recognized certification designed for professionals responsible for leading, governing, and managing enterprise-level AI initiatives.
It equips participants with the skills to align AI strategies with organizational goals, manage cross-functional teams, and ensure ethical and sustainable AI deployment.

Successful participants will receive the EC-Council Certified AI Program Manager (C|AIPM) certification — validating their ability to strategically manage, govern, and scale AI programs across organizations worldwide.  

• Executives, program and project managers (CIOs, CTOs, CDOs)

• AI and data strategy leaders

• Consultants and transformation specialists

• Anyone responsible for implementing or supervising AI initiatives

Upon completion, participants will be able to:

• Design and implement enterprise AI programs aligned with business objectives

• Oversee AI project lifecycles (from ideation to implementation)

• Manage data governance, compliance, and ethical considerations

• Lead multi-disciplinary teams in AI-driven transformations

• Assess AI ROI, maturity, and continuous improvement metrics

• Develop organizational frameworks for AI governance and leadership

1. Introduction to AI Program Management

• AI fundamentals, evolution, and strategic importance

• The role of AI in digital transformation

• Organizational readiness and roadmap creation

2. Managing AI Projects and Programs

• AI project lifecycle: planning, execution, monitoring, delivery

• The ecosystem of data, models, and algorithms

• Integrating AI into business operations

3. Data, Technology, and Infrastructure

• Data management and quality governance

• AI technology stack and MLOps principles

• Security and compliance in AI systems

4. Ethics, Governance, and Risk Management

• Responsible AI principles: fairness, transparency, accountability

• Global AI regulations (EU AI Act, GDPR, etc.)

• Risk assessment and mitigation frameworks

5. Strategic AI Leadership

• Building and managing an AI Center of Excellence (CoE)

• Change management for AI adoption

• Leading human-AI collaboration initiatives

6. Measuring Success and ROI

• Key performance indicators (KPIs) for AI

• ROI evaluation and impact measurement

• AI maturity assessment and benchmarking