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In Part 2 of this Q&A series stemming from questions in the webinar, Managing Your AI Teammate, Eric Naiburg continues the conversation with Darrell Fernandes, diving deeper into how AI is reshaping the way Scrum Teams work.
Together, they explore practical applications of AI in Scrum — from drafting and refining user stories to strengthening Definitions of Done and improving Gherkin statements. Darrell shares how AI can help teams create clearer, more consistent, and testable backlog items, while also warning against over-reliance.
Eric and Darrell examine AI’s impact on team dynamics, including how meeting-recording tools can summarize conversations, capture action items, and support retrospectives. They also address the human side of adoption: differing mental models, fear of change, and the critical role Scrum Masters play as enablers — not gatekeepers — of AI experimentation.
Finally, they tackle a topic many teams overlook: total cost of ownership. As AI capabilities expand, Product Owners must understand infrastructure, data, and operational costs to avoid unintended financial consequences.
If you're navigating how to thoughtfully integrate AI into your Scrum Team — balancing opportunity, risk, and cost — this episode offers practical insights and grounded guidance.
By Scrum.org4.8
1313 ratings
In Part 2 of this Q&A series stemming from questions in the webinar, Managing Your AI Teammate, Eric Naiburg continues the conversation with Darrell Fernandes, diving deeper into how AI is reshaping the way Scrum Teams work.
Together, they explore practical applications of AI in Scrum — from drafting and refining user stories to strengthening Definitions of Done and improving Gherkin statements. Darrell shares how AI can help teams create clearer, more consistent, and testable backlog items, while also warning against over-reliance.
Eric and Darrell examine AI’s impact on team dynamics, including how meeting-recording tools can summarize conversations, capture action items, and support retrospectives. They also address the human side of adoption: differing mental models, fear of change, and the critical role Scrum Masters play as enablers — not gatekeepers — of AI experimentation.
Finally, they tackle a topic many teams overlook: total cost of ownership. As AI capabilities expand, Product Owners must understand infrastructure, data, and operational costs to avoid unintended financial consequences.
If you're navigating how to thoughtfully integrate AI into your Scrum Team — balancing opportunity, risk, and cost — this episode offers practical insights and grounded guidance.

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