Agentic AI in Education
Showcasing real-world deployments across education, creativity, and knowledge work — from AI-native learning environments to tools that amplify human capability.
Key Topics
AI-native learning environments and embodied AI
From coding to specification: what do we teach when AI writes the code?
Multimodal knowledge systems and personalized instruction
Structural shift: from writing code → defining specs → expressing intent
Personalized learning pathways powered by AI agents
Creative pedagogy in the age of agentic AI
AI literacy for educators and students
Measuring learning outcomes with AI analytics
Panel 2 · At a glance
Visual summary of Agentic AI in Education: Learning & Creativity.
What the discussion produced
~95% of enterprise AI pilots fail. Cognitive design is the missing layer. The calculator effect. 2–3M RMB (~€150K) vs no role for new graduates. How to keep AI from widening the top/median gap.
Recommendations
Concrete actions surfaced by the panel — distributable as a standalone card.
Why This Matters
The structural shift from writing code to defining specs to expressing intent is transforming education at every level. This track explores how AI-native learning environments and embodied AI are creating new paradigms for teaching and knowledge work in a post-code world.
Focus Areas
- AI-native learning environments and real-world deployments
- From coding to specification: curriculum transformation
- Multimodal knowledge systems for personalized instruction
- The intent economy: expressing goals instead of writing code
Related Resources
Read the full forum report
Five high-conviction claims, seven headline findings, and the Paris Initiative — alongside every panel writeup.
Open the report