How can AI be used to ensure that the format of articles meets the requirements of journals?

Artificial Intelligence enables automated journal format compliance by processing manuscript text and metadata against journal-specific style rules. This is achieved through specialized algorithms trained on journal guidelines that verify and reformat manuscripts with minimal human intervention. AI systems analyze documents to match structural requirements such as heading hierarchies, reference citation formats (e.g., APA, Vancouver), table/figure presentation, and section ordering. They detect inconsistencies in punctuation, terminology, numbering, and word counts specified by the target journal. Crucially, these tools rely on predefined style templates often using XML schemas or proprietary rule sets, requiring precise input data and initial setup to align with specific publisher standards. Validation checks cover essential aspects like font usage, spacing, margin specifications, and abstract structure before submission. Implementation involves uploading the manuscript draft to an AI formatting platform that scans the document and flags deviations. The tool then automatically suggests corrections or directly applies necessary adjustments. This application significantly reduces authors' manual editing time, minimizes formatting errors leading to desk rejection, and ensures adherence to complex journal formatting instructions prior to peer review.