The AI-Powered Revolution in Academic Publishing: A Holistic Toolchain for Enhanced Efficiency and Quality
DOI:
https://doi.org/10.69974/glskalp.05.03.04Keywords:
Artificial Intelligence (AI), Machine Learning, Deep Learning, Academic Publishing, Scholarly Communication, Manuscript Preparation, Peer Review, Editorial Workflow, Publication Process, Automation, Natural Language Processing (NLP), Generative AI, Custom AI Models.Abstract
The integration of artificial intelligence and associated digital technologies is causing a significant shift in the academic publication landscape. This paper addresses the changing issues faced by authors, editors, reviewers, and publishers by giving a thorough summary of the AI-powered toolchain spanning the whole scholarly publishing lifecycle. We investigate a broad range of current and emerging artificial intelligence tools, including deep learning and machine learning models, along with their specific advantages for each type of stakeholder. These tools enhance manuscript quality for writers by providing writing support, grammar and style checking, citation management, and plagiarism detection. AI-driven solutions for layout analysis, quality control, reviewer recommendations, and manuscript screening help editors and reviewers. AI enables publishers to automate processes, ensure ethical compliance, and enhance the distribution of their content. We also explore the possibilities and approaches for creating customised artificial intelligence models tailored to specific publishing requirements, highlighting how these individualised solutions can maximise quality and efficiency in scholarly communication. Synthesised from a broad spectrum of research, this comprehensive view emphasises the transformative power of artificial intelligence in shaping a more transparent, efficient, and high-quality future for academic publishing.
References
Mike Thelwall, Pardeep Sud; Scopus 1900–2020: Growth in articles, abstracts, countries, fields, and journals. Quantitative Science Studies 2022; 3 (1): 37–50. doi: https://doi.org/10.1162/qss_a_00177
el-Guebaly N, Foster J, Bahji A, Hellman M. The critical role of peer reviewers: Challenges and future steps. Nordic Studies on Alcohol and Drugs. 2022;40(1):14-21. doi:10.1177/14550725221092862
Teixeira da Silva, J. A., & Nazarovets, M. (2024). Rejected papers in academic publishing: Turning negatives into positives to maximize paper acceptance. Learned Publishing, 38(1). https://doi.org/10.1002/leap.1649
L. Fiorillo and V. Mehta, “Accelerating editorial processes in scientific journals: Leveraging AI for rapid manuscript review,” Oral Oncology Reports, vol. 10. Elsevier BV, p. 100511, Jun. 2024. doi: 10.1016/j.oor.2024.100511.
M. Murtaza, Y. Ahmed, J. A. Shamsi, F. Sherwani, and M. Usman, “AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions,” IEEE Access, vol. 10. Institute of Electrical and Electronics Engineers (IEEE), pp. 81323–81342, 2022. doi: 10.1109/access.2022.3193938.
Menon V, Varadharajan N, Praharaj SK, Ameen S. Why Do Manuscripts Get Rejected? A Content Analysis of Rejection Reports from the Indian Journal of Psychological Medicine. Indian Journal of Psychological Medicine. 2020;44(1):59-65. doi:10.1177/0253717620965845
Kadam, Sujata D.. Challenges in scientific writing: Editor's perspective. Journal of Ayurveda Case Reports 8(1):p 1-4, Jan–Mar 2025. | DOI: 10.4103/jacr.jacr_47_25
Severin, A. and Chataway, J. (2021), Overburdening of peer reviewers: A multi-stakeholder perspective on causes and effects. Learned Publishing, 34: 537-546. https://doi.org/10.1002/leap.1392
Richtig G, Berger M, Lange-Asschenfeldt B, Aberer W, Richtig E. Problems and challenges of predatory journals. J Eur Acad Dermatol Venereol. 2018 Sep;32(9):1441-1449. doi: 10.1111/jdv.15039. Epub 2018 May 29. PMID: 29729106; PMCID: PMC6174996.
Razack, H. I. A., Mathew, S. T., Saad, F. F. A., & Alqahtani, S. A. (2021). Artificial intelligence-assisted tools for redefining the communication landscape of the scholarly world. Science Editing, 8(2), 134–144. https://doi.org/10.6087/kcse.244
Kousha, K. and Thelwall, M. (2024), Artificial intelligence to support publishing and peer review: A summary and review. Learned Publishing, 37: 4-12. https://doi.org/10.1002/leap.1570
Khalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. In Computer Methods and Programs in Biomedicine Update (Vol. 5, p. 100145). Elsevier BV. https://doi.org/10.1016/j.cmpbup.2024.100145
Buriak, J. M., Akinwande, D., Artzi, N., Brinker, C. J., Burrows, C., Chan, W. C. W., Chen, C., Chen, X., Chhowalla, M., Chi, L., Chueh, W., Crudden, C. M., Di Carlo, D., Glotzer, S. C., Hersam, M. C., Ho, D., Hu, T. Y., Huang, J., Javey, A., … Ye, J. (2023). Best Practices for Using AI When Writing Scientific Manuscripts. In ACS Nano (Vol. 17, Issue 5, pp. 4091–4093). American Chemical Society (ACS). https://doi.org/10.1021/acsnano.3c01544
WEI, Y., & LIU, X. (2022). ERROR ANALYSIS ON THE INTRODUCTION OF ENGLISH ACADEMIC WRITING BY CHINESE NON-ENGLISH MAJOR POSTGRADUATES AND WAYS TO IMPROVE THEIR WRITING ABILITIES. In Journal of Global Research in Education and Social Science (pp. 38–46). IK Press. https://doi.org/10.56557/jogress/2022/v16i27764
Lamptey, R., & Atta-Obeng, H. (2013). Challenges with Reference Citations among Postgraduate Students at the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. In Journal of Science and Technology (Ghana) (Vol. 32, Issue 3). African Journals Online (AJOL). https://doi.org/10.4314/just.v32i3.8
Ivey, C., & Crum, J. (2018). Choosing the right citation management tool: EndNote, Mendeley, RefWorks, or Zotero. In Journal of the Medical Library Association (Vol. 106, Issue 3). University Library System, University of Pittsburgh. https://doi.org/10.5195/jmla.2018.468
Nicholson, J. M., Mordaunt, M., Lopez, P., Uppala, A., Rosati, D., Rodrigues, N. P., Grabitz, P., & Rife, S. C. (2021). scite: A smart citation index that displays the context of citations and classifies their intent using deep learning. In Quantitative Science Studies (Vol. 2, Issue 3, pp. 882–898). MIT Press. https://doi.org/10.1162/qss_a_00146
Elali, F. R., & Rachid, L. N. (2023). AI-generated research paper fabrication and plagiarism in the scientific community. In Patterns (Vol. 4, Issue 3, p. 100706). Elsevier BV. https://doi.org/10.1016/j.patter.2023.100706
Rupp, D. E. (2011). Ethical Issues Faced by Editors and Reviewers. In Management and Organization Review (Vol. 7, Issue 3, pp. 481–493). Cambridge University Press (CUP). https://doi.org/10.1111/j.1740-8784.2011.00227.x
Zhong, X., Tang, J., & Yepes, A. J. (2019). PubLayNet: largest dataset ever for document layout analysis (Version 1). arXiv. https://doi.org/10.48550/ARXIV.1908.07836
Xu, Y., Xu, Y., Lv, T., Cui, L., Wei, F., Wang, G., Lu, Y., Florencio, D., Zhang, C., Che, W., Zhang, M., & Zhou, L. (2020). LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding (Version 4). arXiv. https://doi.org/10.48550/ARXIV.2012.14740
Kim, G., Hong, T., Yim, M., Nam, J., Park, J., Yim, J., Hwang, W., Yun, S., Han, D., & Park, S. (2021). OCR-free Document Understanding Transformer (Version 5). arXiv. https://doi.org/10.48550/ARXIV.2111.15664
Xu, Y., Lv, T., Cui, L., Wang, G., Lu, Y., Florencio, D., Zhang, C., & Wei, F. (2021). LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding (Version 3). arXiv. https://doi.org/10.48550/ARXIV.2104.08836
Appalaraju, S., Jasani, B., Kota, B. U., Xie, Y., & Manmatha, R. (2021). DocFormer: End-to-End Transformer for Document Understanding (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2106.11539
Shen, Z., Zhang, R., Dell, M., Lee, B. C. G., Carlson, J., & Li, W. (2021). LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2103.15348
Liao, H., RoyChowdhury, A., Li, W., Bansal, A., Zhang, Y., Tu, Z., Satzoda, R. K., Manmatha, R., & Mahadevan, V. (2023). DocTr: Document Transformer for Structured Information Extraction in Documents (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2307.07929
Li, M., Cui, L., Huang, S., Wei, F., Zhou, M., & Li, Z. (2019). TableBank: A Benchmark Dataset for Table Detection and Recognition (Version 2). arXiv. https://doi.org/10.48550/ARXIV.1903.01949
Pfitzmann, B., Auer, C., Dolfi, M., Nassar, A. S., & Staar, P. (2022). DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3743–3751). KDD ’22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM. https://doi.org/10.1145/3534678.3539043
Bougueffa, H., Keita, M., Hamidouche, W., Taleb-Ahmed, A., Liz-López, H., Martín, A., Camacho, D., & Hadid, A. (2024). Advances in AI-Generated Images and Videos. In International Journal of Interactive Multimedia and Artificial Intelligence: Vol. In Press (Issue In Press, pp. 1–36). Universidad Internacional de La Rioja. https://doi.org/10.9781/ijimai.2024.11.003
Kondal, M. & Dr. Virender Singh. (2022). Comparative Analysis of Tineye and Google Reverse Image Search Engines. Zenodo. https://doi.org/10.5281/ZENODO.6378256
Sarto, S., Cornia, M., & Cucchiara, R. (2025). Image Captioning Evaluation in the Age of Multimodal LLMs: Challenges and Future Perspectives (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2503.14604
Lu, W., Zhang, J., Fan, J., Fu, Z., Chen, Y., & Du, X. (2024). Large Language Model for Table Processing: A Survey. arXiv. https://doi.org/10.48550/ARXIV.2402.05121
Crossley, S. A. (2024). Developing Linguistic Constructs of Text Readability Using Natural Language Processing. In Scientific Studies of Reading (Vol. 29, Issue 2, pp. 138–160). Informa UK Limited. https://doi.org/10.1080/10888438.2024.2422365
Nuijten, M. B., & Polanin, J. R. (2020). “statcheck”: Automatically detect statistical reporting inconsistencies to increase reproducibility of meta‐analyses. In Research Synthesis Methods (Vol. 11, Issue 5, pp. 574–579). Wiley. https://doi.org/10.1002/jrsm.1408
Marshall, I., Kuiper, J., Banner, E., & Wallace, B. C. (2017). Automating Biomedical Evidence Synthesis: RobotReviewer. In Proceedings of ACL 2017, System Demonstrations. Proceedings of ACL 2017, System Demonstrations. Association for Computational Linguistics. https://doi.org/10.18653/v1/p17-4002
Roelandse, M., Ozyurt, I. B., Evanko, D., & Bandrowski, A. (2023). Assessing the Effectiveness of SciScore in Supporting the Reproducibility of Scientific Research. In Science Editor. Council of Science Editors. https://doi.org/10.36591/se-d-4602-15
Lazarus, E. (2021). Artificial Intelligence-Assisted Editorial Tools: Case Studies. In Science Editor (pp. e7–e9). Council of Science Editors. https://doi.org/10.36591/se-d-4404-e7
Choi, D.-H., Hyun, J. W., & Kim, Y. R. (2023). An Algorithm for Peer Reviewer Recommendation Based on Scholarly Activity Assessment. In IEEE Access (Vol. 11, pp. 39609–39620). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/access.2023.3263857
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? In International Journal of Educational Technology in Higher Education (Vol. 16, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s41239-019-0171-0
Ashwin Parwani. (2024). The Relationships between Foreign Direct Investment, State-Owned Investment, Private Investment, Import, Export, and Economic Growth in India. AEIDA: Journal of Multidisciplinary Studies , 1(1), 11–24. https://aeidajournal.org/index.php/AEIDA/article/view/3
The advent of human-assisted peer review by AI. (2024). In Nature Biomedical Engineering (Vol. 8, Issue 6, pp. 665–666). Springer Science and Business Media LLC. https://doi.org/10.1038/s41551-024-01228-0
Resnik, D. B., & Hosseini, M. (2024). The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool. In AI and Ethics. Springer Science and Business Media LLC. https://doi.org/10.1007/s43681-024-00493-8
Checco, A., Bracciale, L., Loreti, P., Pinfield, S., & Bianchi, G. (2021). AI-assisted peer review. In Humanities and Social Sciences Communications (Vol. 8, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1057/s41599-020-00703-8
Lu, C., Lu, C., Lange, R. T., Foerster, J., Clune, J., & Ha, D. (2024). The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery (Version 3). arXiv. https://doi.org/10.48550/ARXIV.2408.06292
Jertec Musap, L. (2023). Enhancing scientific publishing: automatic conversion to JATS XML. In European Science Editing (Vol. 49). Pensoft Publishers. https://doi.org/10.3897/ese.2023.e114977
Struthers, C., Harwood, J., de Beyer, J. A., Dhiman, P., Logullo, P., & Schlüssel, M. (2021). GoodReports: developing a website to help health researchers find and use reporting guidelines. In BMC Medical Research Methodology (Vol. 21, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12874-021-01402-x
ODIN Consortium, Aryani, A., Barton, A. J., Brase, J., Brown, J., Demeranville, T., Herterich, P., McAvoy, L., Paglione, L., Ruiz, S., Thorisson, G., Vision, T., & Ziedorn, F. (2015). D4.2: Workflow for interoperability. Figshare. https://doi.org/10.6084/M9.FIGSHARE.1373669.V1
Jiao, C., Li, K., & Fang, Z. (2023). How are exclusively data journals indexed in major scholarly databases? An examination of four databases. In Scientific Data (Vol. 10, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41597-023-02625-x
Fenton, E. G. (2006). An Overview of Portico: An Electronic Archiving Service. In Serials Review (Vol. 32, Issue 2, pp. 81–86). Informa UK Limited. https://doi.org/10.1080/00987913.2006.10765036
Salem, R. M., Culbertson, N. M., & O’Connell, A. (2016). Process for selecting and implementing a manuscript management system: Experiences of a new peer‐reviewed journal. In Learned Publishing (Vol. 29, Issue 1, pp. 55–59). Wiley. https://doi.org/10.1002/leap.1011
Ndungu, M. W. (2021). Scholarly journal publishing standards, policies and guidelines. In Learned Publishing (Vol. 34, Issue 4, pp. 612–621). Wiley. https://doi.org/10.1002/leap.1410
Teixeira da Silva, J. A., & Moussa, S. (2024). The COPE / DOAJ / OASPA / WAME Principles of Transparency and Best Practice in Scholarly Publishing: A Critical Analysis. In ETHICS IN PROGRESS (Vol. 15, Issue 1, pp. 130–154). Adam Mickiewicz University Poznan. https://doi.org/10.14746/eip.2024.1.7
Majhi, S., Sahu, L., & Behera, K. (2023). Practices for enhancing research visibility, citations and impact: review of literature. In Aslib Journal of Information Management (Vol. 75, Issue 6, pp. 1280–1305). Emerald. https://doi.org/10.1108/ajim-11-2023-532
