AI for Product Managers: Strategy, Integration, and Governance
This one-day advanced course equips experienced product managers with the knowledge and frameworks to evaluate, integrate, and govern AI capabilities across the product lifecycle.
Description
This one-day advanced course equips experienced product managers with the knowledge and frameworks to evaluate, integrate, and govern AI capabilities across the product lifecycle. Participants progress from AI and machine learning foundations through product development lifecycle application, ethics and bias mitigation, implementation strategies, metrics and performance evaluation, regulation and compliance, to strategic AI planning — culminating in a capstone that synthesizes a strategic AI product plan. The course aligns to the AI+ Product Manager certification (AI CERTs), preparing participants for the certification exam. Each session includes instruction, discussion-based activities with real-world product scenarios, and formative assessment. An optional session on AI Agents for Product Management extends coverage to emerging agentic AI capabilities.
Who This Course Is For
- Product Owners seeking to integrate AI into product strategy and roadmap decisions
- Product Designers evaluating AI-driven features and user experiences
- Business Managers responsible for AI investment and go/no-go decisions
- IT Professionals transitioning to product-focused AI roles
- Product managers targeting the AI+ Product Manager certification credential
What You Will Learn
- Explain the fundamentals of artificial intelligence and machine learning — including how AI systems work, their capabilities, limitations, and applications — in terms relevant to product strategy and feasibility assessment.
- Apply structured frameworks to lead AI product development from ideation through prototyping and testing, integrating AI capabilities into the product lifecycle.
- Evaluate ethical implications of AI products and apply bias identification and mitigation strategies to product management decisions.
- Plan and execute AI integration into existing products, managing stakeholder communication and organizational change to ensure successful AI adoption.
- Define AI-specific key performance indicators and evaluate AI model and product performance using appropriate metrics and evaluation frameworks.
- Navigate the AI regulatory landscape and develop compliance strategies that integrate regulatory requirements into product development processes.
- Synthesize AI product management knowledge into a strategic AI product plan, evaluate future AI trends, and prepare for the AI+ Product Manager certification exam.
- Evaluate agentic AI capabilities and plan product strategies that leverage autonomous AI agents for product management workflows.
Course Outline
- AI Foundations for Product Leaders
- The AI Product Development Lifecycle
- AI Ethics, Bias, and Responsible Product Decisions
- AI Implementation Strategies and Stakeholder Management
- AI Metrics and Performance Evaluation
- AI Regulation and Compliance for Products
- Future Trends and Strategic AI Planning — Capstone
- AI Agents for Product Management _(Optional)_
This is a high-level overview. For the complete syllabus with detailed topics and lab descriptions, request the full syllabus.
Prerequisites
- 3+ years of product management, product ownership, or related business role experience
- Working knowledge of Agile and Scrum practices from the product side
- Familiarity with product lifecycle concepts (ideation, prototyping, launch, iteration)
- Basic understanding of business strategy and stakeholder management
- No programming or data science experience required — the course is conceptual and strategic, not technical implementation
Delivery Options
- Live, instructor-led
- Virtual instructor-led
Bring This Course to Your Team
This course is delivered as private, instructor-led training for teams and organizations. Contact us for a quote, scheduling, and group options.