Impact of Artificial Intelligence (AI) on the Quality, Efficiency, and Transparency of the Scholarly Publishing Process

Artificial Intelligence (AI) has become an integral part of the scholarly publishing process, offering innovative solutions to enhance quality, efficiency, and transparency. With the rise of automated tools for plagiarism detection, peer review assistance, and workflow optimization, the publishing industry has witnessed a significant transformation. However, the ethical challenges and potential biases in AI adoption raise critical questions about fairness and accountability. This review synthesizes insights from recent studies and literature on AI applications in scholarly publishing, focusing on how AI tools impact various stages of the publishing process. It evaluates AI’s role in enhancing manuscript quality, expediting editorial workflows, and improving the transparency of peer review and data integrity. Examples of AI tools and their use cases, such as plagiarism detection software, reviewer-matching algorithms, and image fraud detection systems, are examined to illustrate their practical applications. The AI has demonstrated measurable benefits in improving publication quality through automated error detection, language enhancement, and statistical validation tools. It has significantly increased efficiency by automating time-consuming processes like reviewer selection, manuscript formatting, and compliance checks. Furthermore, AI-driven systems have enhanced transparency by detecting data manipulation, ensuring accountability in peer review, and facilitating open dissemination of research. Despite these advancements, challenges persist, including biases in algorithms, ethical concerns, and the lack of transparency in proprietary AI systems. The AI is reshaping the scholarly publishing landscape by addressing critical challenges related to quality, efficiency, and transparency. However, ethical implementation and ongoing oversight are necessary to mitigate potential biases and ensure that AI-driven solutions remain fair, accountable, and equitable. The responsible integration of AI can revolutionize scholarly publishing, making it more robust and trustworthy.