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FT: Agentic AI

PART I — FORESIGHT SNAPSHOT  |  FT: Agentic AI  |  Fixed Time-Stamped Synthesis


2026 FT: Agentic AI

Card Type

Future Technology Possibility

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

agentic-AI  |  autonomy  |  pedagogy  |  layer1  |  ft

Tally.so Form

https://tally.so/r/ilrn-if-ft-agentai-2026


Agentic AI systems capable of planning multi-step actions, pursuing goals across time, and operating with minimal human oversight are moving from laboratory research into deployed applications. In immersive learning, agentic AI raises questions about who controls the trajectory of a learning experience, how agency is shared between learner, educator, and system, and what happens when learning agents pursue optimization targets that do not align with human educational values.

Key Drivers / Contributing Conditions:

  • AI capability scaling enabling multi-step goal pursuit

  • Commercial deployment of agentic systems in consumer and enterprise contexts

  • Research on AI-assisted learning path generation and adaptive scaffolding

Tensions Carried Forward to Part II:

  • Who is accountable when an agentic AI system makes a pedagogically harmful decision?

  • Can learner agency be preserved in an environment where AI agents are continuously optimizing?

Linked Scenarios / Strands: SC: Responsible AI | SCENARIO: Open Human Agency | STRAND: Human-Centered AI + XR

Ways of Knowing: Tree  ·  Garden  ·  Lantern


PART II — COMMUNITY EVIDENCE & DIALOGUE TRACK  |  FT: Agentic AI  |  H2 2026 — Living


T

COMMUNITY CONTRIBUTION FORM  —  FT: Agentic AI

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

  • Who is accountable when an agentic AI system makes a pedagogically harmful decision?

  • Can learner agency be preserved in an environment where AI agents are continuously optimizing?


Contributor / Date

Category

Way of Knowing

Contribution Summary

[ Awaiting contributions — form opens July 1, 2026 ]




 

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