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HT: AI inside Immersion

PART I — FORESIGHT SNAPSHOT  |  HT: AI Inside Immersion  |  Fixed Time-Stamped Synthesis


2026 HT: AI Inside Immersion

Card Type

Historical Technology Shift

Series

Immersive Futures Guild — Vision 2035

Layer

1 — Atomic Foresight Object

Status

Active

Confidence

Medium

Workshop

Circle of Scholars — January 2026

Facilitator

Circle of Scholars Workshop Team

Tags

AI-in-XR  |  historical  |  adaptive  |  layer1  |  ht

Tally.so Form

https://tally.so/r/ilrn-if-ht-aiimm-2026


The integration of AI capabilities — adaptive engines, natural language interaction, computer vision — directly into XR environments marks a qualitative shift from XR as a presentation medium to XR as an intelligent, responsive environment. Early research on AI-inside-immersion is generating an initial evidence base but the design, governance, and pedagogical implications remain significantly underexplored.

Key Drivers / Contributing Conditions:

  • On-device AI processing enabling real-time environmental response

  • Platform integration of LLM APIs into XR development toolkits

  • Early commercial deployments in training, healthcare, and education sectors

Tensions Carried Forward to Part II:

  • How should design principles for traditional XR learning be updated for AI-responsive immersive environments?

Linked Scenarios / Strands: FT: Agentic AI | STRAND: Human-Centered AI + XR

Ways of Knowing: Tree  ·  Garden  ·  Lantern


PART II — COMMUNITY EVIDENCE & DIALOGUE TRACK  |  HT: AI Inside Immersion  |  H2 2026 — Living


T

COMMUNITY CONTRIBUTION FORM  —  HT: AI Inside Immersion

Submit case examples, methodological challenges, cultural perspectives, and proposed evidence criteria via: https://tally.so/r/ilrn-if-ht-aiimm-2026


Part II — Scope and Instructions

This section collects community responses, case examples, and challenges to the Part I foresight snapshot above.

It opens July 1, 2026 and undergoes synthesis review in September 2026, November 2026, and January 2027.

Contributions are submitted via the Tally.so form above and appear in the registers below after editorial review.

The Part I text is not modified in response to Part II contributions; it is versioned at the Annual Handoff review.

Contribution categories:  Case Example  |  Methodological Challenge  |  Cultural/Community Perspective  |  Proposed Evidence Criterion

Ways of Knowing accepted:  Tree (evidence)  |  Garden (practice)  |  Lantern (futures)


Tensions Open for Community Response:

  • How should design principles for traditional XR learning be updated for AI-responsive immersive environments?


Contributor / Date

Category

Way of Knowing

Contribution Summary

[ Awaiting contributions — form opens July 1, 2026 ]




 

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