What should students not yet delegate to AI? Toward a theory of cognitive delegation boundaries in higher education

A qualitative critical review across 31 purposively selected sources proposes a theory of cognitive delegation boundaries for generative artificial intelligence in higher education. The analysis challenges conventional governance that focuses strictly on disclosure and permission, highlighting a structural verification circularity problem regarding tasks students are developmentally equipped to evaluate.

This analysis is critical because regulatory and operational frameworks focused solely on disclosure fail to safeguard student skill acquisition. Premature cognitive delegation risks undermining the foundational analytical capacities required for learners to critically assess automated outputs. Institutional leaders must redefine academic guidelines around learning boundaries rather than compliance alone.

Existing guidance in higher education predominantly focuses on whether generative artificial intelligence use is disclosed or permitted, rather than evaluating cognitive developmental risks.

Forward consideration, not a verified fact.