Agile 2.0 for AI Innovation: Adapting Frameworks for Rapid Learning and Responsible Delivery
Learn how to evolve your Agile practices to meet the demands of AI development by aligning rapid experimentation with responsible governance at scale.
- 12:00 PM
Description
Artificial intelligence moves faster than traditional software development models and governance, blurring the line between research and production. Classic Scrum or Kanban cannot keep pace with fast-evolving models, data drift, and heightened ethical scrutiny. This session shows how to update your Agile playbook so cross-functional teams can experiment quickly, govern responsibly, and release AI features that keep adding value after launch. We will combine real-world case studies with actionable templates you can take back to your organization.
Learning Outcomes
By the end of the session, participants will be able to:
- Synchronize research and delivery through dual discovery-delivery loops that compress idea-to-value time.
- Build an AI-ready backlog and Definition of Done that now includes data lineage, model observability, and automated drift alerts.
- Embed lightweight bias, security, and copyright checks into every sprint while preserving velocity.
- Shift success metrics from velocity to outcome-based KPIs such as model accuracy stability, adoption rates, and ethical compliance scores.
- Scale AI agility across a product operating model using Lean Portfolio Management plus ModelOps to coordinate multiple squads and shared assets—regardless of remote or hybrid team structure.
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Additional Information
Location: ZoomContact: Events Team, events@uwebc.wisc.edu