A new survey finds students are using AI for learning support while simultaneously fearing they will be wrongly accused of misconduct. The results point to a growing compliance and risk-management pressure on universities that rely on AI-use policies, proctoring, and detection workflows. The reporting frames the issue as more than etiquette: students’ trust in AI-enabled learning tools may hinge on whether institutions can distinguish legitimate assistance from prohibited work. That, in turn, affects both classroom adoption and student willingness to ask for help using AI-backed study supports. For higher education leaders, the immediate operational takeaway is that AI governance needs to account for student experience. Policies that are unclear—or enforcement mechanisms that generate false positives—can push learning support tools into the shadows rather than normalize them within authorized boundaries. The combination of proactive student adoption and anxiety about accusations is likely to intensify demands for clearer academic integrity guidance, appeal pathways, and better alignment between instructors, student services, and institutional enforcement systems.