About the AI in Agile Delivery Playbook
This template supports teams in integrating AI into their agile practices across Discovery, Experimentation, Delivery, Reflection, and Scaling. It combines PMI research and step-by-step workflows with real examples and adaptable templates to help teams elevate agility through smarter decision-making and faster learning.
What this template helps you accomplish
Accelerate insights from customer research
Run tighter experiments that validate assumptions
Deliver increments more effectively and predictably
Reflect with depth to uncover growth opportunities
Scale insights across teams and leadership to align the organization
In each stage, AI is framed as a decision-support tool—not automation alone—to reinforce empowered, data-informed choices.
Who will benefit most
Ideal for:
Agile teams and Scrum Masters wanting to embed AI in their ways of working
Product managers or delivery leads seeking to enhance backlog refinement, prioritization, or flow visibility
Leaders, coaches, or transformation agents guiding teams to adopt AI-driven agility
Educators or facilitators looking for a structured, interactive board for workshops
You don’t have to be an AI expert. The board is built to be accessible for teams experimenting with AI tools, and scalable for practitioners who want to iterate.
How to use the board
Start at the “Start Here” section for orientation.
Choose a stage (Discovery, Experimentation, etc.) aligned to your current challenge.
Follow the step-by-step workflows. Copy them into your workspace and adapt as needed.
Use the Playground zone to prototype, test, and refine your version.
Capture learnings via embedded reflection prompts.
Share your customized workflows with colleagues or across teams.
Throughout, you’ll find research callouts, AI prompt libraries, and examples to help you get started fast.
Tips & best practices
Adapt, don’t adopt: Use the workflows as starting points and mold them to your context.
Pair AI + human judgment: Always surface AI-generated insights to teams for discussion—don’t treat them as final.
Iterate quickly: Use small experiments to validate new ideas before expanding.
Embed culture: Encourage transparency, psychological safety, and reflection as you scale AI use across teams.
