The release of the DeepSeek-R1 model in early 2025 has significantly garnered public attention and interest regarding artificial intelligence (AI) applications. The emergence of artificial intelligence generative content (AIGC) has led to a flourishing trend in academic publishing, driven by technological advancements, and has sparked a synergy between academic research and publishing practices. AIGC demonstrates extensive applications across various fields, including text creation, speech synthesis, and image editing, which will introduce three main changes to academic publishing: First, the enhancement of production intelligence, which signifies a shift from traditional methods to AI-driven ones. Second, a transition to multimodal presentation, which evolves from solely visual and auditory experiences to more comprehensive multisensory experiences. Third, the development of a complete ecosystem, which advancing from mere technological reshaping to model reshaping. The innovation and application of this technology will greatly improve the quality and efficiency of academic publishing. However, while technological advancement presents opportunities, it also poses challenges, and the quality of risk control and solutions directly affects the integration effect of academic publishing and emerging technologies. Analysis indicates that the AIGC integration in academic publishing presents four primary problems and challenges. First, insufficient accuracy and reliability may undermine trust in academic research. Second, a lack of understanding and critical thinking can hinder innovation in academic research. Third, inadequate interpretability and redundancy can diminish the value of academic research. Finally, insufficient creativity and autonomy will weaken the essence of academic research. To address these challenges, the following countermeasures and suggestions are proposed: First, it should strengthen the digital skills of academic creators and publishers, enhancing their ability and literacy in the scientific use of AIGC technology. Second, it is essential to balance the "changes" and "constants" in academic publishing, ensuring the quality, innovation, and authority of academic content generation. Third, it needs to establish a comprehensive inspection and verification system for academic publishing achievements, enabling full tracking of the academic content production process. Fourth, it must effectively integrate human expertise with AI generation, ensuring users can effectively understand, comprehend, utilize, question, and evaluate AI technology. These measures promote appropriate AIGC technology implementation while avoiding falling into technical misunderstandings and efficiently producing and disseminating academic achievements. In conclusion, while acknowledging the vast opportunities that AIGC brings to academic publishing, it is essential not tounderestimate the disruptive impact that the AI application will have on knowledge production. The process of technology triggering the reconstruction of content production order and human-machine relationship is also a process of publishers constantly updating their understanding of technology and exploring the value of human beings.