This paper is dedicated to an in-depth exploration of the human-machine collaborative translation, which specifically refers to the synergy between human translators and artificial intelligence tools. The paper systematically reports the merits and drawbacks emerging in the pre-translation, in-translation, and post-translation phases. To illustrate this, a real translation project is taken as an example to depict the detailed collaboration process. In the current translation field, the human-machine collaborative model has become a key research focus. Through this case study, several factors that influence the collaboration are identified. For instance, the accuracy and adaptability of artificial intelligence tools, as well as the human translator’s ability to leverage and correct these tools. Moreover, strategies and methods to enhance collaboration and generate high-quality translations are discovered. These include proper utilization of AI features like automatic Translation Memories and Terminology Recognition, combined with human critical thinking and cultural understanding. By examining the cooperation mechanism and exploiting diverse translation tools, the aim is to strengthen the bond between humans and machines. This not only improves translation quality and accelerates the process but also lays a solid theoretical foundation for future research. The practical significance of this research topic is thus well-established, striving to optimize translation workflows and pioneer new paths for more proficient and accurate translations in the age of technological advancement.