Certified AI Program Manager (C|AIPM)

Build a strong foundation in AI, ML, and Generative AI, with a clear understanding of how AI differs from automation and analytics, how it is adopted in real businesses, and the trends shaping enterprise AI transformation.

• Understand core AI concepts and business applications
• Learn the differences between AI, automation, and analytic
• Identify AI capabilities, data dependencies, and failure modes
• Learn the types of AI-ML, DL, Generative AI, and Agents
• Apply AI project life cycle, MLOps, and DataOps
• Analyze emerging AI trends and future opportunities

Assess your organization’s readiness for AI adoption by evaluating strategy, data, technology, workforce, and culture, while identifying capability gaps and adoption risks.

• Assess AI readiness across key dimensions
• Apply AI maturity models and benchmark capabilities
• Conduct AI readiness assessments
• Identify AI adoption risks

Identify, evaluate, and prioritize high-value AI use cases using structured discovery methods, feasibility analysis, and value-based decision frameworks to maximize business impact.

• Identify AI opportunities and assess business value
• Prioritize use cases based on ROI and feasibility
• Analyze build vs. buy vs. partner decisions for AI solutions

Define an AI strategy aligned with business vision and governance guardrails and build a prioritized roadmap to guide scalable and accountable AI adoption.

What You will Learn: •  •  •

• Develop AI strategy aligning with business goals
• Create AI roadmaps with dependency mapping
• Design AI operating models with clear roles and governance

Enable successful AI adoption by leading workforce change, building organizational AI literacy, and applying proven change management frameworks to embed AI into culture and daily operations.

• Lead AI adoption with effective change management
• Apply ADKAR and Kotter frameworks for AI initiatives
• Build AI training programs and a learning culture

Understand enterprise AI platforms, tools, and ecosystems, and learn how to evaluate, select, and integrate AI solutions securely within organizational IT environments.

• Evaluate AI platforms and tools for business fit
• Integrate AI tools with enterprise systems
• Ensure security and vendor maturity in AI tools

Design and implement AI governance, ethical guardrails, and compliance frameworks to ensure responsible, auditable, and missionready AI adoption.

• Establish AI governance policies and processes
• Implement ethical AI practices with bias awareness
• Navigate AI compliance and regulatory frameworks

Plan, execute, and scale AI pilots into enterprise deployments by applying structured governance, phased rollouts, and risk-aware adoption strategies.

What You will Learn: •  •  •

• Design and execute AI pilots with success metrics
• Manage phased rollouts and AI deployment readiness
• Scale AI adoption and mitigate expansion risks

Track AI adoption effectiveness, quantify business value, and communicate measurable impact to stakeholders using data-driven frameworks.

• Measure AI adoption effectiveness and skill progression
• Quantify business value through AI metrics
• Communicate AI value via dashboards and reports

Learn how to embed AI into core business operations by building the leadership, processes, and governance required to sustain long-term AI transformation and value creation.

• Ensure long-term AI transformation success
• Continuously improve AI adoption and adapt to new technologies
• Build leadership and a sustainable AI culture