AI That Understands Your Business: Leveraging Capabilities and Taxonomies in a Knowledge Graph

Discover how knowledge graphs, business taxonomies, and capability models work together to enable AI systems to understand and connect content across disparate enterprise systems. This comprehensive session demonstrated how business taxonomies serve as strategic assets connecting business strategy to operational execution, while business capability models provide the stable organizing principle for enterprise content and semantic interoperability. Participants explored common vocabularies, ontologies, and reference content models brought together in an enterprise knowledge graph. Building on this foundation, the session explored how the knowledge graph can support AI applications, enhancing explainability, robustness, and semantic grounding in machine-learning systems. An outlook on neuro-symbolic AI was provided, illustrating how knowledge graphs can bridge symbolic reasoning and statistical learning.

• Explore how a knowledge graph connects content across organizational silos while maintaining governance controls.
• Learn taxonomy design principles that support multiple stakeholder needs simultaneously, enabling Business-IT alignment using common language that bridges organizational divides
• Apply domain-driven capability modeling as the organizing principle that provides stability amid constant organizational change
• Establish capability models as semantic framework that support strategic planning, transformation roadmaps, and technology rationalization

You can view the presentation slides for this session in the APQC Resource Library.