After the Award: The Authorization Gap in Academic Access to Frontier AI
Academic access programs distribute frontier artificial intelligence as research infrastructure, but awards and institutional authorization are distinct stages. We examine the handoff through structured coding of 15 publicly documented access pathways captured on 19 September 2026, of which ten met prespecified inclusion criteria, and a process trace at one US university. Two isolated model-assisted coding passes found explicit eligibility criteria in nine programs and three implied institutional prerequisites across the corpus. Downstream specification was weaker: access duration was unstated in six programs, seven reported no use or outcome metric, and liability assignment was unstated in five to seven. Public terms did not establish an unambiguous institution-independent path from award to intended use in eight to nine programs, a composite that includes possible and unclear cases. In the institutional trace, policy required review even for free tools. A bounded request generated a ticket but no substantive response or decision pathway during the observation window. We define the authorization gap as the distance between an access award and authorized research use. Tracking first use, clearance, time to first use, and persistence would help programs distinguish allocated resources from usable scientific infrastructure.