Imagine submitting your hard-earned research to a prestigious journal, only to receive a review that's more bot than human. This isn't science fiction; it's the strange reality researchers face today. In a recent incident involving a computational linguistics journal, a suspiciously formulaic review exposed the potential for misuse of large language models (LLMs) in the peer review process. The review, filled with generic language and superficial suggestions, raised immediate red flags, prompting the authors to contact the editor-in-chief. Ironically, their paper focused on deception detection. While some improvements were suggested, the core issue—the blatant use of an LLM for review—remained unaddressed. The incident raises serious questions about the integrity of peer review in the age of AI. What are the ethical implications of using LLMs for such a critical task? How can we ensure human oversight and prevent the erosion of trust in academic publishing? The authors' experience highlights the urgent need for clear guidelines and policies regarding the ethical use of AI. The incident also reveals the limitations of current LLMs, which lack the critical thinking and nuanced understanding required for meaningful peer review. As AI tools become increasingly sophisticated, safeguarding the integrity of academic publishing becomes paramount.