Matt Donovan

Personalization at scale is an architecture problem, not a content problem. As AI-enabled coaches and learning agents become part of how people learn, the unit of value is shifting: from the course to the atom of knowledge, a reusable component built so people, not systems, stay in control of how they learn.

This session shows learning organizations how to break instruction into atoms of knowledge that assemble dynamically into molecules of relevance: tailored combinations built for different learners, roles, and moments of need. It also covers the operating model shifts personalization demands: governance, workflows, technology, data structures, and team capabilities.

Participants leave with a practical roadmap: what tomorrow's learning outputs look like, how instructional design must evolve, and the roles and skills teams need to move from static learning products to ecosystems that adapt to the people using them.

Key Takeaways:

• Principles of atomic instructional design
• Content architecture for AI-driven personalization: atoms, molecules, and the AI orchestration that connects them
• New processes, roles, and skills for learning teams becoming ecosystem architects
• A roadmap from course-centric design to dynamic learning ecosystems
• How AI can support personalization while preserving quality, governance, and learner agency