From Challenge to Studio: A Prototype Frontline AI Innovation Mechanism to Address the AI Embedding Deficit in Healthcare and Educational Institutions.

Authors

Bo Xie

Published in

Learning health systems. Volume 10. Issue 4. Pages e70126. Epub Oct 09, 2026.

Abstract

Health systems are expanding access to artificial intelligence (AI), yet frontline integration into teaching, clinical workflows, and research practice remains uneven. We frame this gap as the "AI embedding deficit," reflecting limited organizational pathways that enable frontline professionals to translate local needs into legitimate, supported, and sustainable AI-enabled tools and workflows. This Experience Report describes a prototype intervention mechanism implemented at an academic nursing school: a rapid-cycle Nursing-AI Challenge followed by a year-round Nursing-AI Studio (NAIS) designed to stabilize and scale embedding.
We implemented the Nursing-AI Challenge as a structured, time-bounded mechanism to solicit real-world challenges from nursing faculty, translate and curate submissions through an interdisciplinary facilitation role, match challenges to AI trainees and mentors, and support rapid proposal development culminating in a public showcase. We then developed NAIS to address continuity and embedding barriers revealed in the Challenge, incorporating continuous intake, environmental scanning, supported co-development, year-round coordination, formalized interdisciplinary partnerships, and a strategic memorandum of understanding with the Chief Information Officer's office to support legitimate integration pathways.
In the inaugural Challenge cycle (Spring 2025), nursing faculty identified 17 challenges spanning education, clinical practice, and research, and students in AI-related fields submitted eight proposals, followed by team formation, co-design of the AI prototypes, and a public showcase event. Implementation reflections identified key sustainability barriers including semester-bounded participation, summer momentum gaps, and intellectual property ambiguity. NAIS was established (Fall 2025 onward) to mitigate these barriers and support ongoing embedding. In early Spring 2026, NAIS launched "Teaching with AI," a clinical faculty innovation initiative piloting an AI-powered teaching tool fully deployed within the university's information technology infrastructure.
A Challenge-to-Studio pathway may function as a practical prototype mechanism for learning health systems seeking to reduce embedding barriers and convert decentralized frontline innovation into durable, governable, and evaluable practice change.

PMID:
42859688
Bibliographic data and abstract were imported from PubMed on 11 Oct 2026.

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