Once you start noticing AI-generated writing, it can feel as though it is everywhere. It appears in school assignments, advertisements, restaurant descriptions, corporate announcements, social media posts and increasingly in journalism. The words may change, but the rhythm often feels familiar: polished introductions, predictable transitions, carefully balanced paragraphs and conclusions that neatly summarise everything that came before.
Artificial intelligence has undoubtedly made writing easier. It can produce a description in seconds, suggest ten headlines before a person has thought of one and transform a messy paragraph into something clearer and more professional. But as more people rely on the same tools to do the writing for them, we risk creating a world in which everything begins to sound the same.
That concern is no longer purely anecdotal. A 2026 study published in Nature Human Behaviour, examining more than 880,000 texts, found that large language models used as writing assistants can make writing styles more uniform. The researchers found that while AI generally preserved the meaning of a text, it reduced linguistic diversity and could weaken some of the individual characteristics normally reflected in a person’s writing.
Researchers have also identified recurring patterns in AI-generated prose. The Reuters Institute has highlighted the increasing appearance of words such as “delve”, “intricate” and “underscore”, alongside formulaic sentence structures. Even punctuation such as the em dash has become jokingly associated with AI online.
The danger is not simply boring writing; writing is supposed to carry personality. Two journalists covering the same event should not necessarily produce identical stories. Two students answering the same essay question should approach it through their own reasoning and vocabulary. A restaurant describing its food should sound like that restaurant, not like every other business that typed “write an elegant menu description” into an AI chatbot.
There is also a more serious problem: AI can be wrong. Large language models generate responses by predicting language rather than independently establishing truth. They can produce incorrect information and even invent convincing-looking facts or sources. Stanford University’s 2025 AI Index noted that even advanced models continued to struggle with inaccuracies.
Bias presents another challenge, AI systems learn from enormous quantities of human-created material, meaning they can reproduce patterns and biases contained in that material. Stanford researchers have found that models designed to reduce explicit bias can still display implicit racial and gender biases. This is why users should understand that an AI response is not a neutral authority. The information it produces can be shaped by training data, model design, safety rules and decisions made by the organisations developing these systems.
Used intelligently, it is a useful tool. It can help brainstorm ideas, locate starting points for research, suggest synonyms, generate headline options, explain difficult concepts and help writers see different ways of structuring an argument. Research has even found that ChatGPT can improve individual performance on some creative brainstorming tasks, although reliance on it can also make people's ideas more similar to one another.
Journalism provides a useful example of where that distinction matters. A Reuters Institute survey found that 56 per cent of UK journalists were using AI professionally at least weekly. Common uses included transcription, translation and copy-editing, while only 10 per cent reported using it at least monthly to generate first drafts of articles.
AI is not going away; therefore, the goal should be to learn how to use it without allowing it to replace our own voices.
A good AI tool should help someone become a better writer, not become the writer. Technology can suggest the words, but humans still need to decide what is true, what matters and, most importantly, what they actually want to say.
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