Becoming an AI Product Manager
Gain a comprehensive understanding of how product management, design and AI intersect to create and deliver successful, human‑centric AI products.
AED 1,000.00
AED 2,000.00
About this course
About this Course:
3-day course covering the full spectrum of AI-enabled product discovery and development.
You’ll learn to:
- Clarify key AI vision between executives and tech teams
- Lead cross‑functional teams, implement AI methodologies
- Embed agile/kanban practices tailored to AI
- Translate AI complexity into product strategy
- Mitigate risk with data quality, performance, and ethics
- Communicate KPIs and report on outcomes
Key Topics:
- Fundamentals of AI and data in product management
- Product lifecycle for AI
- Team roles: data scientists, engineers, designers
- Structuring an AI product team
- AI requirements docs for executive buy-in
- KPIs for AI outcomes
- Explaining “black box” AI
- Ethics, compliance, and bias
Course Modules:
DAY 2: Getting AI Product-Market Fit
Morning – Validating Needs
- The UX of data
- Opportunity mapping AI solutions
- Agile vs Kanban for AI
Afternoon – Defining Requirements
- Low code, no code vs Enterprise AI
- Scoping AI solutions
- Case Study: AI product roadmap
DAY 3: Delivering the AI Solution
- Explaining the black box
- Mitigating risk, governance, ethics, privacy
- Evaluating KPIs for AI performance
Course modules
DAY 1: The role of AI Product Management
Morning – Strategy & Lifecycle
- The AI Product Manager - Myth-busting & evolution
- Mapping AI into Product/Design lifecycle
- Getting to an AI Product Strategy
Afternoon – Team Foundations
- Meet your team: Data Science, Engineering, ML
- Architecting the Team for AI B2C/B2B
- Interactive Case Study
DAY 2: Getting AI Product-Market Fit
Morning – Validating Needs
- The UX of data
- Opportunity mapping AI solutions
- Agile vs Kanban for AI
Afternoon – Defining Requirements
- Low code, no code vs Enterprise AI
- Scoping AI solutions
- Case Study: AI product roadmap
DAY 3: Delivering the AI Solution
- Explaining the black box
- Mitigating risk, governance, ethics, privacy
- Evaluating KPIs for AI performance
- Product Managers & Owners
- Want to translate business goals into AI features
- Need to collaborate effectively with data scientists, engineers, and designers
- Looking to understand the AI lifecycle and integrate it into product management frameworks
- UX and CX Professionals
- Designers or customer experience leads who need to align AI capabilities with user needs
- Want to apply design thinking in the context of AI and data-driven experiences
- Business Leaders and Strategists
- Anyone shaping digital product strategy who wants to include AI as a growth lever
- Executives and consultants communicating AI vision across teams
- Agile/Project Managers
- Professionals managing cross-functional AI teams
- Those aiming to adapt Agile or Kanban practices for AI-specific workflows
- Non-Technical Stakeholders Working With AI
- Professionals who don’t code but need to understand how to:
- Define AI requirements
- Align stakeholders
- Ensure ethical, user-centric outcomes
- Report on AI performance and business value
- Professionals who don’t code but need to understand how to:
