Research and classroom experimentation are increasingly focused on how students use AI in writing and how faculty should respond. A study published in Computers & Composition reports that when students used AI for writing, their cognitive work shifted toward higher-order decisions—prompt refinement, evaluation of outputs, and quality control—rather than simply drafting text. The findings land amid broader instructor concerns: a separate poll indicates many professors have attempted to “AI-proof” assignments, and many report catching AI-assisted cheating. In parallel, classroom-focused AI guidance continues to emerge from institutions and education organizations aimed at teaching students how to critique AI outputs and write with accountability. For higher education teaching and assessment, the practical upshot is that AI literacy is moving from a policy debate to a measurable instructional focus—how learning objectives are assessed and how students are trained to justify revisions. Campuses are likely to see increased demand for faculty development around AI-aligned pedagogy, assessment redesign, and academic integrity practices that reflect how students actually use generative tools.