Drawing from multiple client engagements across sectors, Tesfaye and DeMay shared patterns and lessons learned from initiatives where KM, Data Management, and AI teams are working together to create a more connected and intelligent enterprise. They highlighted the growing need for integrated strategies that bring together semantic modeling, content management, and metadata governance to enable intelligent automation and more effective knowledge discovery.

The presentation emphasized how KM professionals can lead the way in designing sustainable semantic architectures, building cross-functional partnerships, and aligning programs with organizational priorities and AI investments. Presenters also explored how roles are shifting from traditional content stewards to strategic enablers of enterprise intelligence.

Session attendees walked away with:

• Insight into how KM roles are expanding to meet enterprise-wide data and AI needs;
• Examples of how semantic layers can enhance findability, improve reuse, and enable automation;
• Lessons from organizations integrating KM, Data Governance, and AI programs; and
• Practical approaches to designing cross-functional operating models and governance structures that scale.

The post The Evolution of Knowledge Management & Organizational Roles: Integrating KM, Data Management, and Enterprise AI through a Semantic Layer appeared first on Enterprise Knowledge.