Developing the GenAI Capabilities to Win
Enterprise Knowledge Graphs
Best Practices
Workshop
Make enterprise knowledge usable—so GenAI can deliver trusted answers
Knowledge graphs help GenAI deliver more accurate, explainable, and context-aware results when semantic structure is aligned to real business needs. This workshop helps teams.
Leave with a knowledge graph blueprint—role in GenAI, semantic priorities, platform criteria, and next.
The Challenge
Many organizations have valuable data, but lack a shared structure that makes knowledge discoverable and reusable across GenAI use cases.
- Semantics aren’t aligned to the business: Terms and relationships vary across teams, creating ambiguity and inconsistent outcomes.
- Use case integration is unclear: Knowledge graphs are built as data projects, but not connected to the.
- Platforms and ownership are fragmented: Tooling choices, governance, and cross-team collaboration aren’t defined, slowing adoption.
Without a semantic foundation, GenAI systems struggle to stay grounded—reducing trust and limiting scale.
Our Solution
We guide your team through a practical approach to define, evaluate, and plan enterprise knowledge graph capability.
- Knowledge Graph Role in GenAI Solutions: Define where knowledge graphs add value and how they support grounding, context.
- Semantic Layer Alignment: Align concepts, relationships, and definitions to business priorities and data realities.
- Ontology, Entity Linking, and Reasoning Capabilities: Identify the semantic techniques required to support priority use cases and outcomes.
- Platform Evaluation and Integration Approach: Establish criteria to evaluate platforms and plan how graphs integrate into GenAI.
- Cross-Functional Development Plan: Define collaboration, ownership, and governance needed to build and sustain the knowledge.
Area of Focus
- Defining the Role of Knowledge Graphs Within GenAI Solutions
- Aligning Semantic Layers with Business and Data Requirements
- Utilizing Ontologies, Entity Linking, and Reasoning Capabilities
- Evaluating Knowledge Graph Platforms and Integrating Them into Use Cases
- Planning Knowledge Graph Development Across Cross-Functional Teams
Participants Will
- Define where a knowledge graph will improve GenAI outcomes and why it.
- Identify priority semantic concepts and relationships to standardize across the enterprise.
- Clarify which ontology and reasoning capabilities are needed for key use cases.
- Establish platform evaluation criteria and an integration approach for GenAI workflows.
- Leave with a development plan and next steps to build knowledge graph.
Who Should Attend:
Solution Essentials
Format
Facilitated working session
Duration
2 Hours
Skill Level
Beginner to Intermediate
Tools
Slides, workshop templates, key worksheets, checklists, and collaboration tools.