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AI Learning Over Time • Cohort-Based

Cohorts and Workshops

These offerings are designed for groups who want to build practical AI capability together over time—using a repeatable, outcomes-focused approach. Explore the options below, then visit each class page for the full details.

  • Team Activation — align on goals, tools, and guardrails.
  • AI Audit — assess readiness, risks, and highest-value use cases.
  • AI + Scrum Cohorts — build habits across roles with hands-on practice.
  • AI for Scrum Teams — practical, role-based workflows your team can adopt.
Tip: If you’re not sure where to start, choose AI Audit first—then map a cohort plan from the findings.

Ready to start?

Pick your next step—start with free learning, watch the videos, or browse the full course catalog.

Prefer Virtual or On-Site delivery for your team? See Corporate Training Offerings.

Search Results

8 Feb 2026

AI For Scrum Product Owners - February 17. 2026

Author: Rod Claar CST  /  Categories: AI for Scrum Product Owners  / 

Event date: 2/17/2026 9:00 AM Export event

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  • Remaining: 12
  • Price: $0.00
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AI for Scrum Product Owners

Use GenAI as a practical co-pilot for product work: refine stories and acceptance criteria, improve backlog ordering, sharpen stakeholder communication, and strengthen product strategy with AI-assisted insights.

Who it’s for

Product Owners, Product Managers, and agile practitioners who want to streamline PO workflows with AI—including Business Analysts, Project Managers transitioning to agile, Scrum Masters supporting Product Owners, and agile teams integrating AI into day-to-day delivery.

Enrollment
Investment
$299

Live virtual, interactive (instructor-led)

 

Private In-Person (up to 18 students + travel): $499

Format
Live Virtual

Hands-on workshop with real-time instruction and collaboration

Duration

4 hours (half-day workshop)

Delivery

Live virtual (instructor-led)

Pacing

Single-session workshop

Outcomes
  • Use prompt-engineering patterns to generate PO-ready artifacts: story drafts, acceptance criteria, release notes, and stakeholder updates.
  • Improve backlog ordering with AI-assisted discovery: clarify outcomes, uncover hidden dependencies, and surface risk/assumptions.
  • Strengthen product strategy using AI for market/competitor synthesis, roadmap narrative, and hypothesis-driven planning.
  • Run higher-signal Scrum events with AI support (planning, reviews, retros): better inputs, tighter facilitation assets, cleaner outputs.
  • Apply guardrails for responsible AI use (privacy, bias, transparency) when working with product, customer, and team information.

 

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