Today, many academics and students use AI tools such as ChatGPT, Claude, and Gemini to help improve their writing. These tools are easy to access and can quickly make writing sound clearer, smoother, and more polished. For non-native English users in particular, these tools may appear to offer an immediate solution to long-standing challenges in academic communication, especially in achieving clarity, fluency, and a more native-like style. Yet amid this growing dependence, an important question deserves greater reflection: Are generative AI tools truly designed for language editing?

Generative AI is not the same as language-editing software

Large Language Models (LLMs) are fundamentally generative systems. They are designed to predict and produce text that is statistically probable based on patterns in language data. Their primary function is not to edit language according to established linguistic conventions, disciplinary expectations, or institutional standards.

In contrast, language-editing applications such as Grammarly, QuillBot, and InstaText, as well as similar platforms, are specifically designed for proofreading and refinement. These tools focus on grammatical accuracy, sentence-level clarity, stylistic consistency, spelling conventions, and appropriate collocations while preserving the writer’s intended meaning.

As a proofreader and editor, I would argue that generative AI is not always the most appropriate tool for language checking. While AI-generated text may appear fluent and sophisticated, it often introduces unnecessary paraphrasing, subtle shifts in meaning, and a gradual loss of authorial voice. In academic, administrative, and policy-related writing, where precision and fidelity are essential, such alterations can become problematic.

The growing risk of over-dependence

More concerning, however, is the increasing tendency to rely on AI not only to refine language but also to initiate, structure, and conclude thought processes. While convenient, this level of dependence risks weakening both language development and intellectual ownership. Many users may already be familiar with the frustration of repeatedly refining prompts while still struggling to obtain the intended output. I have experienced this myself. There were moments when I spent considerable time attempting to guide AI towards a response that aligned with my own thinking, only to realise that the process itself had become mentally exhausting.

Ironically, that experience led me to an important realisation that the human mind operates with far greater depth than any generative system. AI may imitate language patterns impressively, but it does not possess lived experience, intuition, judgment, or genuine understanding. It can identify frustration through textual cues, but it cannot truly comprehend what frustration feels like. This distinction, however subtle it may seem, reminds us of the irreplaceable value of human thought and emotion. In many instances, the time spent refining prompts could instead be invested more meaningfully through reading, engaging with scholarly sources, and strengthening one’s own arguments. Although AI may assist the writing process, meaningful intellectual growth still depends on active reading, reflection and engagement with knowledge.

Language development is a gradual process

For many non-native users, the desire to sound more native-like is entirely understandable. Nevertheless, language proficiency cannot be achieved solely through instant rewriting or automated refinement. Vocabulary, stylistic awareness, appropriacy and communicative sensitivity develop gradually through extensive reading, active engagement with texts, attentive listening, observation and consistent practice. When generative AI is used uncritically, writers may eventually produce language that appears fluent but no longer feels authentic. Over time, this may hinder rather than strengthen genuine language development. Language is not merely about sounding correct. It is also about expressing identity, perspective and lived experience.

Choosing the right tools and the right process

This is not a call to reject AI altogether, but rather to use these technologies thoughtfully and responsibly in ways that genuinely support human learning and intellectual growth. Different tools serve different purposes, and understanding these distinctions is crucial. Generative AI can be highly useful for brainstorming, summarising information, organising ideas or exploring alternative expressions. However, when the primary goal is language refinement and proofreading, dedicated editing tools, alongside human editorial expertise, remain far more reliable.

Here, I present several examples illustrating how the same text may differ when revised through generative AI, language-editing software, and human editorial intervention.

The comparisons in Figures 1, 2 and 3 reveal subtle yet significant differences between these editing approaches. Generative AI may produce polished and highly fluent sentences, but in doing so, it can unintentionally alter emphasis, tone, or meaning. Language-editing software typically offers more controlled refinement by improving clarity and grammatical accuracy without extensively reshaping the text. Human editing, however, goes beyond correction alone. It involves contextual judgment, sensitivity to intention, and an understanding of what the writer genuinely seeks to communicate. No matter which tools we choose to use, the final responsibility still lies with us. Suggestions generated by AI, editing software, or even human editors ultimately require human judgment, critical evaluation, and conscious decision-making. The ability to determine what truly reflects our intended meaning remains an intellectual process that cannot be outsourced entirely.

A final reflection

Regardless of the tools we use to improve our writing, language ultimately reflects something deeply personal. These include our thoughts, intentions, values, and ways of understanding the world. In pursuing the desire to sound right, we should be careful not to sacrifice the individuality and intellectual voice that make our writing uniquely ours. Because in the end, going beyond sounding native is not merely about language proficiency. It is also about preserving the human capacity to think critically, express meaningfully and communicate authentically in an increasingly automated world.

This perspective also aligns closely with the aspirations of Universiti Teknologi Malaysia’s UTM ASCEND 2030, which emphasises not only technological advancement and global competitiveness, but also humanity-centred values and meaningful intellectual development. In an increasingly AI-driven world, these values remain essential in ensuring that technology continues to support, rather than diminish, the human capacity to think critically and engage thoughtfully with knowledge.

A scholarly mindset demands more than convenience. It requires curiosity, sustained learning, critical reflection and the discipline to continually refine our knowledge and skills. Through reading, practice, dialogue and thoughtful engagement, we grow not only as writers but also as thinkers. It is through this continuous human process of learning, refining, and sharing knowledge that intellectual growth continues to flourish in the age of AI.

Dr Wan Farah Wani Wan Fakhruddin teaches at the Faculty of Social Sciences and Humanities (FSSH) Kuala Lumpur, Universiti Teknologi Malaysia. Her academic interests include studying the science of human communication through the lens of functional linguistics.