Hey everyone,
I wanted to open a discussion around the Yokohama release’s Agentic AI capabilities, especially as they relate to playbooks and internal user Knowledge Management (KM).
We’ve been actively working to align our Knowledge processes with Agentic AI behaviors—and seeing real traction when it comes to automating task execution, suggesting contextual knowledge, and driving action through AI-driven Playbooks.
Use Cases Being Explored:
AI-suggested knowledge articles tied to incidents and changes
Agentic AI Playbooks recommending actions based on CI/service data
AI agents identifying knowledge gaps from deflection data and unresolved tickets
Knowledge article creation and lifecycle managed within agent workflows
Challenges Being Addressed:
Ensuring AI-generated content aligns with KM standards like ISO 30401
Integrating KM actions into Agile 2.0 and release workflows
Maintaining governance without slowing down knowledge delivery
Key Learnings:
Agentic AI performs best when connected to contextual data through CSDM
KM roles and governance are critical to avoid irrelevant or unchecked AI output
Trusted, well-maintained knowledge bases are essential for AI to add real value
Would love to hear how others are using Agentic AI in the Yokohama release—or how you’re handling KM governance with AI agents in the mix.
Who's connecting AI Playbooks with KM, SPM, or Agile workflows?
