Professors and campus policy-makers are seeing an unexpected consequence of AI‑detection tools: students are turning to generative models to evade detectors. Faculty report students altered writing style to avoid false positives and began using AI to 'normalize' voice; other students say detectors’ reputational risk pushed them to adopt AI preemptively. Researchers at CUNY and Stanford have flagged bias in detectors against nonnative English writers, and lawsuits over false flags are rising. The dynamic is reshaping classroom practices and institutional policy on academic integrity, forcing colleges to reconsider detection reliance and to clarify AI-use guidance.