AI in Academic Writing: How to Disclose Assistance Without Risk in 2025

AI in Academic Writing: How to Disclose Assistance Without Risk in 2025

Within a few short years, AI tools have moved from the margins of academic life to the centre of everyday research practice. Many scholars now experiment with AI to improve grammar, summarise literature, propose outlines or even draft small fragments of text. At the same time, publishers, universities and funders have responded with new policies: AI cannot be listed as an author; AI-generated text and images must not be passed off as purely human; and substantial AI involvement must be disclosed. A growing number of policies go even further and make it clear that using AI to “rewrite”, “rephrase” or “polish” text is not a trivial, mechanical operation but a form of content creation that risks blurring the boundary between human authorship and machine output.

For authors, this creates a delicate balance. Hiding AI use is increasingly risky, but overemphasising it may raise doubts about originality and authorship. The challenge is to document AI assistance honestly, in a way that complies with 2025-style policies, while also assuring editors and reviewers that the intellectual work remains firmly under human control and that the manuscript is not simply a disguised AI product. The safest path is to treat AI as a tentative tool for idea support, not as a ghost-writer, and to reserve substantive language editing and rephrasing for human specialists rather than algorithms.

1. Why AI Disclosure Matters in 2025

At the heart of AI disclosure requirements lies a simple concern: trust. Editors and reviewers must be confident that the research they evaluate is based on genuine data, rigorous reasoning and accountable authorship. AI models do not understand truth or responsibility; they generate plausible text or images based on patterns in training data. They may be helpful in producing grammatically fluent sentences, but they do not know whether those sentences correctly represent the literature, the methods or the results.

If AI-generated or AI-rewritten output is inserted into manuscripts without careful oversight, the integrity of the scholarly record is at risk. An AI system might rephrase a cautious statement into one that overclaims, or might silently drop important limitations because they do not fit its learned patterns of “good writing”. Even seemingly harmless AI “proofreading” can reshape the emphasis and nuance of key arguments. This is why many 2025 policies state explicitly that AI must not be used to create or substantially revise content, including language-level transformations, without full disclosure and human verification.

Policies introduced by publishers and academic societies converge on a few core points. AI systems cannot be authors because they cannot take responsibility or respond to queries. Substantive use of AI in data analysis, text generation, figure production or language rewriting must be acknowledged. Authors are expected to verify every claim, reference and result, regardless of whether AI was involved. In other words, AI can be a tool, but never a substitute for scholarly judgement or for the human act of writing and revising a scientific argument.

2. What Kinds of AI Use Need to Be Disclosed?

Not every incidental interaction with AI requires a full methods paragraph. Asking a system once to suggest a synonym for a single word, then replacing the sentence entirely with your own formulation, does not meaningfully alter the manuscript. However, as soon as AI starts to shape the wording, flow or structure of your paragraphs in ways that are preserved in the paper, the situation changes. Using AI to edit full sections, to generate draft paragraphs, to paraphrase large chunks of text or to “improve” the language of an entire manuscript is essentially asking the system to perform content creation, even if you still recognise the underlying ideas as yours.

Similarly, using AI to create figures, code or summaries of large document collections crosses the line into areas where transparency is expected. If the tool influenced the wording, the logic of the argument, the coding decisions or the visual representation in a way that another researcher would reasonably want to know, then disclosure is advisable. Most 2025-style policies focus on three areas: language rephrasing, content generation and data-related assistance. As the role of the tool moves from trivial spelling suggestions into rewriting or restructuring, the case for explicit documentation becomes stronger.

It is crucial to recognise that to many publishers there is no sharp distinction between “AI drafting” and “AI proofreading” when the tool is allowed to rephrase sentences or entire paragraphs. If an AI system generates new sequences of words that end up in your article, it has participated in content creation. Responsible authors either avoid that kind of use altogether or make a clear, honest statement about it and then actively replace or thoroughly revise that output in later drafts.

3. Typical Themes in 2025 Publisher Policies

Although the exact wording varies by journal and field, current policies tend to emphasise several recurring themes. The first is the non-negotiable point that AI systems cannot fulfil the criteria for authorship. They do not design studies, approve final versions or accept responsibility for the work. They cannot respond to readers’ questions or correct the record if errors are discovered. For that reason, listing an AI tool as a co-author is not allowed, and relying on it to generate substantial parts of the text without oversight is seen as a failure of authorship responsibility.

The second theme is the requirement that authors must ensure AI output is carefully reviewed for accuracy, bias and originality. Journals have seen cases where AI-generated passages contain factually wrong statements, invented references or mixtures of ideas that no responsible human scholar would endorse. Even when authors ask AI to “only edit language”, the system may introduce subtle content changes—altering claims, removing qualifiers or remixing sentences from its training data. This is precisely why many publisher policies now stress that AI should not be used for transformations that extend beyond basic spelling checks, and that any such use must be disclosed and tightly controlled.

The third theme is a growing concern about fabricated references, altered figures and synthetic data. Editors know that AI can fabricate citations that look realistic, can clean and enhance images in ways that remove important imperfections and can generate entirely synthetic datasets. Disclosing AI use is partly a way of signalling that you understand these risks and have taken steps to guard against them. It is also a way of assuring the journal that where AI was involved, it was not performing tasks that are prohibited, such as generating text in place of the author’s own writing or “proofreading” sections in a way that effectively rewrites them.

4. Where to Document AI Assistance in Your Manuscript

Once you decide that disclosure is appropriate, the next question is where to place it. In most cases, a short statement in one or more of the following locations works well: the methods section, the acknowledgements, the declarations section (if the journal has one) and, occasionally, the cover letter. The choice of location depends on the role AI played.

If AI was used in data processing, coding, text mining or figure generation, the methods section is usually the appropriate place to describe it. Treat the AI system like any other software or analytical technique: name it, briefly describe what it did and explain how you verified its outputs. If AI was used for language suggestions, many publishers prefer this to be noted in the acknowledgements rather than the methods, because it does not change the underlying scientific method. However, you should be careful not to understate the extent of AI involvement. If AI did more than flag spelling errors—if it rewrote whole sentences or paragraphs—that is likely to go beyond what policies consider acceptable “language correction” and should be described frankly as content-level assistance or, preferably, removed and replaced with your own writing.

Some journals now provide specific fields in their submission systems where you can answer questions about AI use. These should be completed honestly and consistently. If the system asks whether any part of the text was generated by AI, and you have previously used AI to paraphrase sections, the safe and ethically sound answer is not “no”. Instead, you should explain that AI was used at an earlier stage, that you have now rewritten affected passages and that the present version is fully human-authored and verified.

5. Sample Wording That Does Not Harm Acceptance Chances

Many authors worry that mentioning AI will trigger rejection. In practice, editors are far more concerned about undisclosed use than about limited, transparently described assistance. The key is to frame AI as a tool that you directed and corrected, not as an engine that wrote your paper. It is also wise to avoid normalising AI rewriting as if it were the same as working with a human language editor. The two situations are ethically distinct in most policies, because a human editor is accountable in ways that an AI system is not.

In the acknowledgements, a responsible, low-risk statement might say that during manuscript preparation you used AI-assisted tools to highlight potential grammar issues or to suggest alternative phrasing, but that all wording present in the final version was written, reviewed and revised by the authors. Importantly, you should not claim that AI merely “polished” your text if, in reality, large portions were generated or rephrased by the system and then accepted with only minor edits. In such cases, the correct solution is to rewrite those sections yourself so that the remaining text can honestly be presented as your own.

When AI supported data processing or coding, you might describe it in the methods as providing preliminary clustering of texts or initial suggestions for parameter settings, followed by manual review and confirmation using accepted non-AI tools. The focus should always be on the human decisions that shaped the analysis. If AI produced code that you adopted, you should note that you inspected, tested and, if necessary, modified that code before using it for any reported results.

In a cover letter, if disclosure fields are limited, a single clear sentence can suffice. You might confirm that no part of the manuscript was left in a state generated autonomously by AI systems, that you have avoided using AI for wholesale rewriting or proofreading of sections and that any limited AI assistance in early drafts was either removed or thoroughly replaced by human-authored text before submission.

6. Documenting Different Types of AI Assistance

Because not all AI involvement is the same, it helps to describe briefly what kind of assistance was provided. Language-level support provided by a human editor, such as corrections of grammar or improvements to sentence structure, is normally regarded as acceptable, provided it is acknowledged and does not alter the substance of the arguments. By contrast, language-level transformations carried out by AI—rewriting sentences, changing style, paraphrasing whole sections—are increasingly treated as content creation by publishers, because a machine, rather than an accountable human, is generating the actual strings of words that appear in the document.

If you have used AI to help with language only in the very early stages, a safe strategy is to treat that early draft as scaffolding and then rewrite all key sections yourself, with the AI-assisted wording serving only as a temporary aid to clarify your own thoughts. In that scenario, once you have fully re-authored the text, the AI’s contribution has been effectively erased, and there may be little left to disclose. If, however, you plan to keep AI-rephrased sentences in the final manuscript, you should assume that this will be considered substantive AI involvement, which must be described and may conflict with some journals’ prohibition of AI language editing.

Content-level support, such as summarising a large body of literature, suggesting outlines or generating example paragraphs, always carries more risk. Even if you subsequently revise those outputs, it can be difficult to ensure that no fabricated references or distorted summaries remain. For this reason, many authors now restrict AI’s role to brainstorming at a distance—perhaps asking general questions about possible research designs or about typical structures for particular article types—rather than feeding their own text into a system for rewriting.

7. Balancing Transparency and Perception

Authors sometimes hesitate to mention AI because they fear reviewers will assume the manuscript is less original or less carefully written. At the same time, many reviewers and editors are deeply concerned that authors may be using AI extensively without acknowledgement. Clear, concise disclosure can actually strengthen credibility because it demonstrates that you take the issue seriously, that you understand the limits of AI tools and that you are prepared to stand behind your own writing.

The most reassuring disclosures emphasise that the AI’s role was limited and clearly defined, that all scientific and interpretive decisions were made by the authors and that every sentence has been reviewed critically by a human who is responsible for its content. It is not usually necessary to state which version of which model you used unless the tool played a central analytical role. However, if the journal asks specific questions about the tool, or if the AI’s role went beyond trivial assistance, you should respond accurately rather than minimise.

It is also important to recognise that some uses of AI will be unacceptable to certain journals, regardless of how honestly you describe them. Many publishers now state explicitly that using AI to “polish” or “proofread” manuscripts is not allowed, because that involves the model generating alternative sentences in place of the ones you wrote. In that sense, even AI language editing is not simply a neutral service but an act of content creation. If you want the security of avoiding such conflicts, the safest approach is to rely on human language editors and proofreaders, who can be named and who are bound by professional ethics.

8. Good Record-Keeping and Internal Documentation

Even if a journal only requires a short disclosure, it is wise to maintain more detailed internal records. Keeping a simple log of how and when AI tools were used can protect you if questions arise later. You might make a note immediately after a writing session that you tried an AI assistant on a particular paragraph but later discarded that version, or that you generated a short summary with AI but decided not to incorporate it in the manuscript. If you do accept any AI-suggested wording, you should record where it appears and how you have checked it.

These records do not need to be elaborate or formal. They can take the form of brief annotations in a lab notebook, a text file attached to your project folder or short comments in your shared documents with co-authors. The aim is to create a trace of your decision-making so that, if an editor, reviewer or institutional committee later asks how AI was involved, you can answer from written evidence rather than from memory alone. Documentation is also a mirror for your own practice. If you find yourself reluctant to write down the extent of AI editing because it would look excessive, that is a signal that the model is doing too much of the writing and that your reliance on it may no longer be consistent with emerging norms.

9. Practices That Increase Risk and Should Be Avoided

Alongside guidance on what to do, it is helpful to be explicit about what to avoid. Passing off large blocks of AI-generated text as your own, without verification or revision, is dangerous for both ethical and practical reasons. Such text may contain factual errors, invented references, inconsistent terminology or unacknowledged copying from training data. Even when it appears polished, it is not a reliable substitute for genuine scholarship. Journals are introducing detection tools precisely because they have seen such problems in submitted manuscripts.

Using AI to rewrite or paraphrase your entire literature review is another high-risk practice. Even if the ideas remain broadly accurate, the resulting text is not your writing in any meaningful sense. According to many policies, it becomes AI-created content that cannot simply be “approved” by the author after the fact. Similarly, generating survey responses, interview transcripts or numerical data through AI without a clear methodological framework and without full disclosure conflicts with basic principles of research integrity. These practices undermine trust in the findings and can have serious consequences for authors if discovered.

A particularly subtle risk arises when authors treat AI language editing as equivalent to a human proofreader. Although the words “editing” and “proofreading” may be familiar, when they are performed by an AI system, they are no longer minor surface corrections but acts of text generation. A human proofreader works on the basis of your existing sentences, suggests changes and remains accountable for their actions. An AI proofreader, by contrast, generates new sentences from statistical patterns, with no understanding, no accountability and no guarantee that the output is free from hidden biases or copied fragments. For this reason, many journal policies now group AI “editing” and “rephrasing” under prohibited forms of content creation. Authors who want safe language improvement should therefore prefer human editing and proofreading over algorithmic rewriting.

10. How AI Disclosure Fits into Research Integrity More Broadly

The debate about documenting AI assistance is ultimately part of a larger conversation about research integrity. Just as we expect clear reporting of methods, transparent data handling and honest acknowledgement of limitations, we now need to be transparent about our tools. The goal is not to criminalise every use of automation, but to ensure that the scientific record accurately reflects how knowledge was produced.

AI is not inherently unethical. It becomes problematic when it obscures who did what, when it is used to shortcut reading, thinking or analysis, or when it replaces the act of writing with the act of prompting. If authors begin to rely on AI to generate or “clean up” large portions of their manuscripts, the boundary between genuine scholarship and stylistic simulation becomes blurred. Disclosure is one way to protect that boundary. Another is to choose deliberately to keep AI at a distance from core tasks such as drafting and revising, and to bring in human support instead when needed.

Viewed in this way, AI disclosure is less about confessing to a questionable practice and more about participating in a culture of openness. Just as we disclose funding sources and conflicts of interest, we now disclose technological assistance that could otherwise be invisible. Done calmly and clearly, such disclosure should become a routine, unremarkable part of academic writing rather than a stigma. Over time, the community will develop a more nuanced sense of when AI use is harmless, when it is helpful and when it crosses lines that compromise integrity.

Conclusion: Using AI Transparently Without Undermining Your Work

As 2025 publisher policies continue to evolve, responsible authors need a practical way to integrate AI tools into their writing without damaging trust. The solution is not to banish AI from the process entirely, nor to surrender authorship to algorithms, but to treat AI as a cautiously used assistant whose contributions are openly acknowledged and carefully verified. That means resisting the temptation to let AI “fix” your prose by rewriting it, recognising that such rewriting is content creation in the eyes of many journals, and instead turning to human editors when your language needs substantial improvement.

By describing AI involvement briefly in the methods or acknowledgements when it is genuinely limited, keeping internal records of how tools were used and emphasising human responsibility for all substantive content, you can comply with current expectations without weakening your chances of acceptance. Editors and reviewers are ultimately looking for rigour, clarity and honesty. Transparent AI disclosure is increasingly part of demonstrating those qualities, while avoiding AI rewriting or AI proofreading in the final text protects both your authorship and the integrity of the scholarly record.

For researchers who want to ensure that their manuscripts meet high standards of clarity and integrity, while avoiding the risks associated with AI-generated or AI-rephrased text, our human re-writing services, journal article editing and academic proofreading services provide human expertise that complements, rather than replaces, responsible use of digital tools. Human editors can improve grammar, style and structure while preserving your voice and ensuring that what appears under your name is, in a meaningful sense, written by you.

Sample 1 – Acknowledgements: Early, Limited AI Use Fully Replaced

During the very early stages of drafting this manuscript, the authors experimented briefly with an AI-based language tool to highlight potential grammar issues in a small number of sentences. All text that appeared in those early AI-assisted versions was subsequently discarded or completely rewritten by the authors, and no AI-generated or AI-rewritten phrasing remains in the current manuscript. All wording, interpretations and conclusions in this version have been written, reviewed and approved solely by the human authors.

Sample 2 – Methods/Declarations: AI Assistance for Preliminary Data Exploration

An AI-based tool was used only for preliminary exploration of the textual dataset (for example, to obtain an initial, unsupervised clustering of documents). These exploratory outputs were treated as informal diagnostics and were not used directly for any results reported in this article. All analyses that underpin the findings were specified, executed and checked by the authors using established, non-generative software, and all statistical procedures and qualitative interpretations were conducted and verified by the human authors. No AI system was used to generate, rewrite or “proofread” any part of the manuscript text.

Sample 3 – Cover Letter or Declarations: General AI Disclosure and Explicit Limits

In line with the journal’s policy on artificial intelligence, we confirm that no section of this manuscript has been drafted, rewritten or “proofread” by generative AI tools. The authors did not use AI systems to create or rephrase the text, and no AI-generated wording has been incorporated into the submitted version. Any minor automated checks were limited to standard, non-generative spelling and grammar functions integrated into our word-processing software. All intellectual content, all phrasing and all revisions reflect the work of the human authors, who take full responsibility for the accuracy, originality and integrity of the manuscript.