12,637 papers · updated 10 Oct 2026livingmeta.ai
← Browse all papers
Research theme

Institutional Policy

The Institutional Policy theme comprises 617 papers in this corpus published between 2006 and 2026. Work here is dominated by Literature Review, Conceptual, Qualitative. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Literature Review102 (17%)
  • Conceptual92 (15%)
  • Qualitative66 (11%)
  • Case Study64 (10%)
  • Policy Analysis56 (9%)
  • Mixed Methods53 (9%)

Research domains

  • AI Governance593 (96%)
  • Scholarly Infrastructure19 (3%)
  • Research Integrity3 (0%)
  • Peer Review2 (0%)

Frequent sub-topics

AI adoption in higher education institutions · 2organizational conditions for scaling AI adoption and overcoming pilot trap · 1educational technology governance and responsible AI implementation in learning environments · 1organizational discourse and generative AI adoption · 1multi-layer governance of generative AI-enabled platforms · 1adoption attitudes toward generative AI by experience level · 1Chief AI Officer role and organizational structure · 1AI curriculum alignment between academia and industry in Taiwan · 1

Open research gaps

  • The authors identify a critical gap: "there is no empirical understanding of how senior leaders actually navigate the organizational, regulatory, and technical complexities of scaling autonomous AI sy
  • The authors identify several gaps and future directions: the need for harmonized and forward-looking regulatory frameworks addressing data privacy, algorithm transparency, accountability, and inequali
  • The paper identifies a gap in understanding how international economic law frameworks address and are reshaped by artificial intelligence development and deployment, positioning this intersection as a
  • Comparative studies across colleges, disciplines, or institutional types to examine whether similar governance regimes appear in STEM, humanities, professional schools, or community colleges
  • Instructor interviews to clarify how faculty design AI policies and understand authorship, assessment, and student responsibility

Representative papers