This study examines error patterns in the use of the dynamic aspect markers le, zhe, and guo in the interlanguage of Korean learners of Chinese, and compares the corrective strategies and effects of human teachers with those of artificial intelligence systems represented by ChatGPT-5 and DeepSeek in grammatical error correction. The findings indicate that AI demonstrates high efficiency in correcting frequent and rule-based overt errors, producing revisions that are largely comparable to those of teachers in terms of formal grammatical accuracy. However, when errors involve semantic distinctions, aspectual function differentiation, or discourse-level coherence, AI corrections tend to remain at a surface level, lacking systematic explanation and pedagogical orientation. In contrast, human teachers integrate contextual information and aspectual semantics to provide targeted analysis and feedback, which better supports learners’ construction of aspectual understanding. Based on these findings, this study argues that AI is currently more suitable as a supplementary tool for grammatical error correction, and proposes promoting the development of AI correction systems toward greater interpretability and pedagogical integration in order to achieve a human-AI collaborative model of Chinese language teaching.