Developing the GenAI Capabilities to Win
Enterprise Knowledge Graphs
Best Practices
Workshop
Turn Enterprise Knowledge Into Leverage
This executive-level workshop helps leaders understand how enterprise knowledge graphs can support GenAI initiatives by improving alignment between business intent, data, and decision-making. Designed for sponsors and operators shaping GenAI strategy, it focuses on clarifying where knowledge graphs add value and how to plan for them responsibly across the enterprise.
To win, leaders need more than isolated GenAI experiments—they need a shared understanding of how enterprise knowledge graphs enable scalable, trusted outcomes.
The Challenge
As GenAI adoption accelerates, organizations struggle to translate interest in knowledge graphs into clear, business-aligned direction:
· Unclear business role – Leaders lack a shared view of how knowledge graphs actually support GenAI outcomes, leading to over- or under-investment.
· Semantic misalignment – Business concepts, data definitions, and analytical needs drift apart, creating confusion and friction across teams.
· Fragmented ownership – Knowledge graph efforts emerge in silos, with no agreed governance or cross-functional coordination.
· Platform-first thinking – Tool and platform discussions happen before use cases, success criteria, or integration needs are clear.
· Scaling uncertainty – Teams struggle to plan how knowledge graph capabilities should evolve as GenAI use cases expand.
Success requires clear leadership alignment on the role, value, and operating model for enterprise knowledge graphs in GenAI.
Our Solution
A fast-paced, leadership-oriented working session designed to clarify direction, build alignment, and define actionable next steps.
· 1:1 Discovery Sessions – Short, executive-level conversations to ground the workshop in current GenAI priorities, data realities, and organizational constraints.
· Enterprise Knowledge Graph Scan or Assessment – A lightweight diagnostic to baseline understanding of knowledge graph readiness, value expectations, and decision gaps.
· Executive Briefs – Decision-oriented briefs outlining best practices, common pitfalls, and practical considerations for enterprise knowledge graphs in a GenAI context.
· 2-Hour Group Working Session – A facilitated leadership session to align on the role of knowledge graphs, explore priority use cases, and pressure-test assumptions.
· Recommended Next Steps – Clear, prioritized actions to guide knowledge graph planning, ownership, and integration across teams.
Moving leaders from abstract interest to shared understanding and confident next steps.
Area of Focus
· Defining the role of knowledge graphs in a GenAI context
· Mapping semantic layers to business and data needs
· Exploring ontology, entity linking, and reasoning concepts
· Evaluating platforms and use case integration considerations
· Planning knowledge graph development across teams
Participants Will
· Clarify strategic role – Establish a shared view of how enterprise knowledge graphs support GenAI goals and business outcomes.
· Align semantic priorities – Identify which business concepts and data domains matter most for near-term GenAI use cases.
· Assess readiness gaps – Surface organizational, governance, and coordination gaps that limit effective knowledge graph adoption.
· Evaluate use case fit – Align on where knowledge graphs are most valuable—and where simpler approaches may suffice.
· Define ownership model – Clarify cross-functional roles and decision rights for knowledge graph development and evolution.
· Prioritize next steps – Leave with a short list of practical, leadership-approved actions to move forward.
· Reduce execution risk – Build shared context that prevents fragmented or misaligned investments.
Who Should Attend:
Solution Essentials
Format
Virtual or in-person
Duration
2 Hours
Skill Level
Beginner to Advanced (non-technical friendly)
Tools
Optional discussion guides, readiness checklists, and planning templates