AI Knows the Language, Experts Know the Science: Balancing AI with Human Insight in Research Publishing
The scientific community has normalized AI use to an extent. A 2025 study by Wiley [1] reports that, of the 2,400 survey participants, 85% agree AI has improved their efficiency. Moreover, the usage of AI tools for specific research-related tasks like manuscript preparation, publication planning, journal submission, or even research promotion significantly increased from 45% (2024) to 62% (2025).
Despite this surge in AI adoption, researchers should exercise caution. Knowing the strengths and weaknesses of AI and where human expertise shines allows you to make informed, conscious decisions about using AI tools. This article takes you through what AI does best when it comes to research writing, to what extent you should rely on AI tools, how you can recognize the weaknesses of AI tools, and which aspects of research writing still require human intervention.
Strengths of Expert Human Editors
- Scientific Reasoning
- Contextual Understanding
- Field-specific Terminology
- Reviewer Expectations
- Publication Strategy
Conclusion: Balance AI Use with Human Insight
Strengths of AI
Speed
The purpose of tools has always been efficiency. Instant results to save time. The output of any text you wish to edit, refine, rewrite, paraphrase, or even generate (which is not ideally recommended), is shared with you within minutes.
For example, let’s say you have written your abstract but it exceeds the word count limit suggested by the target journal. Writing tools like Paperpal can help you tighten sentences and reduce word count per your requirements without altering your intended meaning and provide you with the output instantly. The same task with expert editing services would take at least 4 to 8 hours even when faster turnaround time is requested.
Grammar Fixes
Large language models (LLMs) are typically trained to identify and fix grammar errors. Non-native authors especially struggle with English grammar, as the correct choice of articles, adverbs, conjunctions, and other parts of speech of the English language may not be as straightforward to them as it is to native English authors.
AI writing tools, or even other in-built features in MS Word, helps you find these mistakes and recommends the correct alternatives. Take these hypothetical examples:
| Author-written sentence | AI-corrected sentence | What was fixed |
| The results shows that the two groups displays better performance than… | The results show that the two groups display better performance than… | The plural subject “results” requires the plural verb “show,” “groups” requires “display,” and the singular subject “study” should be followed by the singular verb “aims” |
| The study aim to investigate… | The study aims to investigate… |
But there’s more to the above examples! Keep reading to find out why the corrected sentences are still not correct.
Language Enhancement & Sentence Drafting
Writing academic papers is not only about reporting findings. The language must be accurate too. Several researchers, especially non-native speakers, struggle to express their opinions in a formal, academic writing style. “What if the words used make me sound like an ESL author? How can I improve my language to sound more like a native English speaker?” This is a common concern that’s addressed by AI tools.
LLMs that are well trained on differentiating the various writing styles can help refine, polish, enhance, and rewrite your opinions in a way that meets academic standards. For example, features like paraphrasing and rewriting in Paperpal, a tool that’s designed specifically to assist academic writing, can enhance the writing in your research papers without altering your original intended meaning.
But these strengths DO NOT imply that AI alone is enough for academic writing! In fact, general use AI tools could be more troublesome than you think.
Weaknesses of AI Tools
A few common drawbacks of AI tools are
- lack of contextual understanding,
- surface-level corrections without in-depth explanations,
- hallucinations and fabrication of citations,
- the absence of scientific reasoning,
- failure to recognize reviewer expectations when handling responses to peer reviewers,
- mechanical writing patterns that impact author’s voice,
and the list could go on. But it’s no longer just about these obvious drawbacks. Although many top journals outline clear guidelines for AI use, a key concern for authors is: “What if my writing is flagged as AI?”
And with tools like Claude watermarking AI-generated content [2] to comply with the EU AI Act, more AI tools are likely to follow suit. What could these mean for authors?
Let’s say you write your research paper without using AI. But only wish to run it by an AI tool to tighten the text or check for grammatical errors. Or take the case of requiring a table. You input the data to the tool and prompt it to convert the provided details into a well-formatted table. The output shared by the tool will be tagged as AI-generated with an invisible watermark even though the ideas were originally yours! And if the journal checks your submission for AI detection using their in-house developed tool or an external detector, your content is highly likely to be flagged as AI generated because of the attached watermark.
If more stringent rules are set forth by the EU AI Act [3], tools would continue to amend how they operate to ensure compliance. Of course, journals and publishers too would consider evolving their guidelines regarding AI use. But the key takeaway remains that human oversight and intervention are crucial.
Strengths of Expert Human Editors
You, as an author, should oversee the extent to which AI tools contribute to your research paper writing. That’s the oversight aspect. However, expert editors have unique strengths that drive the preparation of research papers.
Scientific Reasoning
One of the key weaknesses of AI tools is its lack of ability to apply scientific reasoning when making corrections. Language editors, who are also subject matter experts, provide reliable guidance to authors, either through comments or direct corrections, with convincing rationale.
For example, one of our editors at Editage noticed that including specific additional input could bridge certain logical gaps in a paper. Here’s a comment left by the editor to the author: “Please explain the case history effectively by describing any prior therapeutic or surgical interventions. Also, explain the characteristics of the tumor mass. You may even provide details of the surgical procedures and any post-operative complications to complete the section appropriately with thorough details of the analysis.”
Contextual Understanding
Remember our aforementioned examples where AI tool corrected grammar mistakes but those fixes were still inaccurate? Here’s why.
The sentences were written in the Conclusion section of the paper, which means the information appeared at the end and was referring to “completed study” rather than “what was going to be studied.” So, not only did the verbs need fixing but the tenses also had to be revised.
| Author-written sentence | AI-corrected sentence | What was fixed | Human-edited sentence | What was fixed |
| The results shows that the two groups displays better performance than… | The results show that the two groups display better performance than… | The plural subject “results” requires the plural verb “show,” “groups” requires “display,” and the singular subject “study” should be followed by the singular verb “aims” | The results showed that the two groups performed better than… | The editor noticed that these sentences are part of the Conclusion section and hence used past tenses of the verbs. |
| The study aim to investigate… | The study aims to investigate… | This study investigated… |
This contextual understanding is only one example of the value human editors add to polished papers. In academic writing, knowledge of the discipline, expertise in subject area, familiarity with field-specific terminology—everything plays into the context of a research. Which is why human editing remains critical.
Field-specific Terminology
AI tools trained on non-scientific and non-academic datasets tend to provide generic suggestions for improving writing. For instance, AI often overlooks non-native usages. If the text is grammatically correct, AI retains conversational language and lexical terminology in academic texts.
But a manuscript carefully edited by expert editors adheres to academic writing conventions and discipline-appropriate usage throughout the document. Take the following text, for example. You’ll see how the editor has used field-specific terminology while eliminating non-native tone and conversational usage yet ensured that the author’s voice is retained when tightening the sentences.
Original text: And, spectral data can be used to form databases that, in the future, will allow the development of computational platforms for multi diagnosis, starting from a single biological sample. In other words, by obtaining a spectrum and comparing it with spectra stored in databases, it will be possible to identify the infections in an individual, without the need for specific tests for each pathogen.
Expert-edited text: Furthermore, spectral data can be utilized to create databases that may facilitate the future development of computational platforms for multi-diagnostic assessments based on a single biological sample. This approach enables the identification of infections in individuals by comparing obtained spectra with pre-existing spectra stored in databases, thus eliminating the need for specific tests for each pathogen.
Reviewer Expectations
Most academic editors are themselves researchers or have frequently interacted with personnel in the publishing industry. They know what reviewers expect to see in a manuscript:
- Appropriate section headings because it makes initial perusal and navigating the paper easy for reviewers
- Proper citations of works referenced for reviewers to verify the authenticity of the author’s claims
- Accurate callouts to figures, tables, graphs, maps, and other display items to expedite peer evaluation
- Sufficient details of the methodology to ensure clarity and completeness of how the study was executed
Editors look for gaps in these aspects when reviewing a manuscript. Perhaps they would even have peer reviewed for certain journals in the past, making them excellent sources of external input for validating and verifying the readiness of your submission.
Publication Strategy
Some editing services go beyond basic editing. They help plan your entire publication strategy with proper support systems in place. From journal recommendation and artwork formatting to resubmission support, a solid publication strategy can maximize your chances of acceptance. You will get advice on
- which journals are most likely to accept your manuscript based on an expert analysis of previously published research papers in those journals,
- how best to present your cover letter to journal editors to create the correct first impression,
- finalizing your entire submission package such that it is tailored to a specific journal rather than a generic one, and
- a professional mock peer review before the actual submission so you can identify and fix errors that are likely to be cited as reasons for rejection.
Such dedicated support systems for publication can do more than what an AI tool can do by fixing your grammar and language errors!
Conclusion: Balance AI Use with Human Insight
Most journals don’t penalize authors for using AI tools. But not disclosing AI usage and unethical use of AI tools are definitely considered malpractice. So, find the right balance between the two: AI use and human insight. Know what tasks can be successfully executed by AI and which aspects of manuscript editing needs human expertise. Making the correct choices ensures research integrity, retains author voice, and assures compliance with ethical AI use.
References
1. AI Adoption Jumps to 84% Among Researchers as Expectations Undergo Significant ‘Reality Check’ https://newsroom.wiley.com/press-releases/press-release-details/2025/AI-Adoption-Jumps-to-84-Among-Researchers-as-Expectations-Undergo-Significant-Reality-Check/default.aspx
2. How Claude marks AI-generated content https://support.claude.com/en/articles/16266773-how-claude-marks-ai-generated-content
3. EU artificial intelligence act https://artificialintelligenceact.eu/
