AI assistants have transformed individual productivity, but true organizational impact requires moving beyond user-centric experiences. This talk explores how workspace-centric architectures enable teams to collaboratively manage knowledge, conversations, documents, and AI capabilities within shared contexts. Attendees will gain practical insights into designing scalable permission models, context-aware AI systems, and collaborative workflows that make AI more useful for teams, not just individuals. The session focuses on architectural patterns, design decisions, and lessons learned that can be applied across enterprise AI and collaboration platforms.

Organizations are rapidly moving from experimenting with AI assistants to integrating AI into team workflows. However, most systems are still designed around individual users. This session addresses a timely challenge facing the industry: designing AI experiences that scale from personal productivity to collaborative intelligence while maintaining governance, usability, and trust.