In the domain of English-Chinese translation, “translationese” denotes linguistic phenomena where translated texts manifest foreign syntactical structures or deviate from indigenous Chinese communicative norms. This linguistic phenomenon is fundamentally characterized by several critical attributes: linguistic unnaturalness, compromised textual fluency, syntactical rigidity, and potential comprehension challenges. Throughout the evolutionary trajectory of machine translation, these systems have historically been notorious for generating mechanistic translations that uncannily mirror the structural limitations of human-produced translationese. The recent technological advances in artificial intelligence have precipitated a paradigmatic shift. Contemporary AI-driven translation tools now incorporate sophisticated refinement mechanisms, enabling users to strategically enhance translated texts through carefully calibrated linguistic prompts. This development represents a significant methodological evolution in addressing the longstanding challenges of translational artificiality. This research critically examines a pivotal question: Can advanced artificial intelligence effectively eliminate translationese through its refinement mechanisms? Utilizing an authentic proofreading scenario from a professional publishing house, I analyzed translation materials to evaluate AI’s linguistic intervention capabilities. The findings reveal a nuanced landscape: Advanced AI systems significantly enhance amateur translations, demonstrating remarkable potential in detecting and mitigating translationese instances. However, critical limitations persist. Compared to professional translators, AI lacks the sophisticated linguistic intuition necessary for navigating complex nuances. Crucially, AI cannot autonomously initiate contextually sensitive linguistic adaptations. Therefore, I propose a human-AI symbiotic model—specifically, a triangulated editing approach—as the optimal translation production paradigm for the foreseeable future. Beyond its professional application, this triangulated framework holds significant pedagogical value. It establishes a curriculum structure for moving translation training beyond simple tool operation toward the cultivation of critical thinking and sophisticated human-AI collaboration.