Artificial Intelligence is rapidly establishing itself as the cornerstone of contemporary product management, fundamentally altering how teams identify customer needs, craft solutions, and navigate decision-making processes. Much like the advent of electricity transformed industrial capabilities, AI is redefining the lifecycle of product creation, validation, and evolution.
This live, instructor-led course, available both online and onsite, is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to leverage AI to elevate their ownership practices and reinforce the rigor of their strategic decisions.
Upon completion of this program, participants will be equipped to:
- Grasp the core principles of Artificial Intelligence and clearly distinguish between traditional AI and Generative AI (GenAI).
- Implement the seven key stances of a Product Owner, including the emerging Orchestrator role, utilizing AI to amplify each stance—whether as a Visionary, Experimenter, or Customer Representative.
- Hone effective prompting techniques, viewing AI tools not merely as utilities, but as intelligent collaborators with distinct specialized capabilities.
- Enhance customer insight by developing AI-assisted personas for hypothesis testing and discovery, all while preserving genuine, direct engagement with end-users.
- Formulate and articulate a compelling product vision using structured methodologies like the 3x3 Framework, employing AI to refine and visualize strategic narratives.
- Leverage Generative AI capabilities to fast-track prototyping and hypothesis validation, such as rapidly generating mock-ups or conceptual product designs.
- Strengthen product decision-making by applying AI tools to analyze, prioritize, and assess features against criteria of value, feasibility, and user impact.
- Offload or automate routine administrative tasks—such as email management, stakeholder coordination, and meeting notes—via AI, thereby freeing capacity for high-level strategic and creative work.
- Facilitate informed discussions on AI ethics, algorithmic bias, and data security to ensure responsible and sustainable integration of AI technologies.
- Identify and architect high-value AI use cases specifically aligned with unique product requirements and organizational contexts.
- Explore and experiment with approximately 20 diverse AI tools and models, ranging from productivity assistants and prototyping platforms to generative solutions for video, imagery, and code.
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