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Artificial Intelligence (AI) in Academic Writing

Original Editor - Angeliki Chorti

Top Contributors - Angeliki Chorti  


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Introduction

Academic writing is progressively transforming. The increasing accessibility of Artificial Intelligence (AI) tools has led numerous journals to the application of guidelines on AI use and disclosure for editors, reviewers and authors. [1] [2] [3] The use of AI tools in areas such paraphrasing, proof reading, citation management, plagiarism detection, managing complex and extensive information and reducing it to a summary / abstract has been reported to result in less academic time and errors, more work productivity and this has encouraged academics, students and researchers to its increasing use. [4]

Despite this progress and gradual transformation, considerations on the safe, ethical, credible, accountable and transparent academic writing can not be overlooked. Although AI may provide valuable benefits to the people using AI, risks may still need to be considered; unintentional plagiarism, inaccurate citations and overreliance on AI to generate content are some examples. Guidelines on the ethical and best AI use in academic writing are required to ensure research credibility and promotion, not replacement of human expertise. [5]

Areas of Impact

A systematic review of 24 studies since 2019 on AI impact in academic writing has detected six major areas of benefit:

  1. Idea generation and research design facilitation
  2. Content and structure enhancement
  3. Literature synthesis support
  4. Data management and analysis support
  5. Editing, review and publishing
  6. Ethical compliance

[6]

Key Principles of AI Use in Manuscript Preparation

Key principles on AI tools use in academic research vary according to institution, journal and framework. As the integration of these tools becomes more widespread, various initiatives are put forward to highlight the need for uniform requirements in academic writing . You can find some examples in the resources section of this article. The need for uniform standards of AI use need was further supported by recent estimates reporting that AI-generated text may have already increased dramatically in recently published manuscripts but not disclosed by authors. [7]

Yousaf describes practical and ethical considerations in his editorial:[8]

Permission in Certain Stages / Processes

The use of AI is allowed during the pre-writing phase of writing, with the aim to improve readability and language during this process.

Transparency

Authors are required to disclose if they have used AI and which tools they have used.

Ethical Use

Ethical use of AI in academic writing involves the responsible of these tools while maintaining academic originality and integrity.

Authorship and Accountability of Authors

Authors remain ultimately responsible for the article they have created. AI cannot take responsibility for the scientific work created because authorship is linked to a set of ethical and intellectual responsibilities that only human researchers can fulfill. These prerequisites are in alignment with broader academic policies, such as the International Committee of Medical Journal Editors criteria for authorship, which require authors to have made significant intellectual contributions to the research and to be accountable for the final work.

Intellectual Property of AI-Generated Content / Plagiarism

Intellectual Property (IP) is a legal term used to protect ideas, their expression through writing or products and their exploitation by others. [9] Scientific manuscripts may include copyrighted material that could lead to violations or IP disputes. Therefore, authors must be careful in ensuring that the AI-generated text does not unintentionally lead to plagiarism and examine the terms of service of the AI platform being used to adhere to proper citation practices.

Resources

COPE Guidance on Authorship and AI tools

Equator Network on AI and Machine Learning Use in Health Research

References

  1. ↑ Elsevier. Generative AI policies for journals. Available from: https://www.elsevier.com/about/policies-and-standards/generative-ai-policies-for-journals [accessed 19/10/2025]
  2. ↑ American Psychological Association. APA Journals policy on generative AI. Available from: https://www.apa.org/pubs/journals/resources/publishing-tips/policy-generative-ai [accessed 19/10/2025]
  3. ↑ Laher S. Using AI in academic writing: what’s allowed and what’s not. S. Afr. J Psychol. 2025;55(2):155-8.
  4. ↑ Kwong J, Wang S, Nickel G, Cacciamani G, Kvedar J. The long but necessary road to responsible use of large language models in healthcare research. npj Digit. Med. 2024; 7: 177.
  5. ↑ Fauziah RR, Puspita AMI, Yuliana I, Ummah FS, Mufarochah S, Ramadhani E. Artificial intelligence in academic writing: Enhancing or replacing human expertise? J Clin Neurosci. 2025 May;135:111193.
  6. ↑ Khalifa M, Albadawy M. Using artificial intelligence in academic writing and research: An essential productivity tool. Comp Meth Progr Biomed Update. 2024; 5: 100145.
  7. ↑ Naddaf M. AI tool detects LLM-generated text in research papers and peer reviews. Available from: https://www.nature.com/articles/d41586-025-02936-6 [accessed 19/10/2025]
  8. ↑ Yousaf MN. Practical Considerations and Ethical Implications of Using Artificial Intelligence in Writing Scientific Manuscripts. ACG Case Rep J. 2025 Feb 19;12(2):e01629.
  9. ↑ Brown WM. Intellectual property. Methods Mol Med. 2000;40:227-41.
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