Abstract: To strengthen the collective awareness of standardized, transparent, and responsible artificial intelligence (AI) usage in the entire process of sports knowledge production and to safeguard the foundation of authenticity, originality and academic integrity in sports academic innovation, five scholars were invited by the Journal to conduct a thematic discussion on the value reshaping and boundary challenges faced by sports knowledge production in the AI era. Ye Chao from Fudan University argued that the core issue of AI's role and boundaries lies in achieving human-machine collaboration and dynamic coexistence. When addressing the dual contexts of AI's involvement in sports knowledge production—professional and daily-life scenarios—differential ethical frameworks and practical guidelines should be established, while seeking the balance between technological empowerment and the adherence to humanistic values. Guo Qing from Hangzhou City University noted that AI brings instrumental convenience to sports academic research but also raises challenges in academic originality, argument depth and academic integrity. Academic journals should establish transparent and responsible new norms, while researchers must transition from being "tool users" to "the master of wisdom". Fu Weijie from Shanghai University of Sport observed that AI reshapes the production methods of sports knowledge, requiring sports academic research to focus on AI's blind spots and the core attributes of the sports discipline to maintain uniqueness. Sports researchers should prioritize the cognitive principle of "empowerment rather than replacement", adhering to ethical boundaries when using AI-assisted writing. Tan Guangxin from South China Normal University emphasized that in sports academic research, AI should not become a profit-driven tool. Its application must always uphold academic impartiality, clearly define its scope and ethical boundaries, particularly for journal editors who act as "gatekeepers" of academic publishing. Xu Zhengxu from Changzhou University pointed out that AI's involvement in sports knowledge production has both advantages and disadvantages. To address the ethical risks it generates in originality, scientific rigor and accountability, technological innovation should be promoted to resolve universal ethical risks, while institutional norms should be strengthened to tackle specific ethical risks. Additionally, digital literacy education should be implemented to enhance the ability to identify ethical risks.