Abstract:

Artificial intelligence is driving academic publishing into a new phase of transformation, fundamentally reshaping traditional journal publishing models and editorial workflows. Academic journals in the daily chemical sector serve as core platforms for disseminating research findings, driving innovation, and fostering academic exchange. However, these journals currently struggle with widespread problems including content homogenization, low efficiency, delayed digital transformation, and limited international influence. Consequently, traditional manual editing can no longer meet the industry’s demands for high-quality development. This paper begins with the current development and transformation needs of daily chemical journals to explore pathways for editorial role transformation and the logic behind restructuring publishing workflows under AI. It clarifies that editors are shifting from traditional text editing and workflow management toward academic curation, data operations, and industry community building. It examines the value of AI across the entire process, from topic planning and intelligent prereview to precise peer review, as well as in academic integrity management and knowledgeenhancement services. The paper also analyzes practical challenges such as algorithmic bias, editorial capability gaps, emerging academic misconduct, and intellectual property disputes. The study concludes that humanmachine collaboration is inevitable for intelligent development, and that editors’ professional judgment and resourceintegration abilities remain core values irreplaceable by AI. By leveraging technology for process innovation and talent empowerment, daily chemical journals can transition from traditional content publishing to intelligent knowledge services, thereby supporting academic innovation and industrial upgrading in the industry.

Key words: daily chemical, artificial intelligence, journal editing, academic publishing, role transformation, process optimization, academic ethics