AAC&U survey finds that 95% of faculty fear students will overuse generative AI as it grows, and about two-thirds believe graduates are not well prepared to use AI in the workplace.

Additional findings project an 83% drop in attention spans due to GenAI, with 86% saying the teaching workforce will be impacted and 79% expecting at least some disruption to typical department teaching models.

The report notes the findings come from a non-scientific survey and are not generalizable to all college faculty, with full methodology detailed in the accompanying report.

Respondents come from diverse disciplines and institution sizes; 39% were full professors and 26% were non-tenured instructors, suggesting results may not be fully generalizable.

Faculty views on GenAI are mixed, ranging from innovation to resistance, and many are grappling with how to proceed, underscoring a need for clear values, shared norms, and AI literacy to safeguard deep learning.

Despite divisions on GenAI itself, there is broad agreement on the need for clear values, shared norms, and investment in AI literacy to preserve human judgment and learning in higher education.

Leadership calls for rethinking teaching models, assessment practices, and academic integrity so AI should support, not undermine, the value of a college degree.

Opinions on AI literacy for students are mixed, with about half considering it very important and others rating it less important or irrelevant.

Most faculty (about 78%) believe AI-driven cheating is rising, though there is sharp disagreement on what counts as cheating, such as AI-generated outlines or edits.

There is substantial disagreement on legitimate AI use; roughly half view following detailed AI-generated outlines as cheating, while the rest are undecided or see it as acceptable.

Cited institutions like AAC&U and Elon University centers emphasize democratic purposes of higher education, equity, and liberal education as AI literacy becomes essential.

Specific concerns include diminished critical thinking (about 90%), shorter attention spans (83%), altered teaching dynamics (86%), disruption of department teaching models (79%), increased cheating (78%), and devaluation of degrees (74%).