How AI writing tricks readers (and how to tell).

How to spot AI writing instantly

In 2025, distinguishing between human and AI-generated writing has become a vital skill. With large language models (LLMs) like ChatGPT, Gemini, and Claude rapidly improving and being adopted across nearly every digital platform, the line between human expression and algorithmic text is blurring.

AI can now produce essays, tweets, emails, blog comments, and even heartfelt-sounding messages that seem indistinguishable from those written by real people. However, there are still reliable indicators that can help you spot AI writing instantly once you know what to look for.

This is a comprehensive guide to identifying machine-generated content. Where we examine the common patterns, red flags, and subtle inconsistencies that give AI writing away. Whether you’re a reader, writer, educator, or content moderator, this guide will help you pass the ultimate AI vibe check.

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The overuse of the m-dash

One of the most conspicuous tell-tale signs of AI-generated writing is the overuse of the m-dash (—). This punctuation mark, while elegant when used sparingly, is rarely used as frequently by actual human writers. LLMs, however, seem to have an inexplicable love affair with the m-dash. No matter how many times you ask ChatGPT or similar models to avoid them, they keep showing up. This is partly because AI has learned from sources where the m-dash is often used to create dramatic pauses or break up thoughts, but most people don’t even know the keyboard shortcut for it.

If you see an unusual number of m-dashes in a social media post, email or comment, especially from someone who doesn’t normally write that way, it could be your first red flag.

Parallel sentence structures

Another major giveaway is the use of repetitive rhetorical structures. A classic AI construction is the “It’s not just X – it’s Y” sentence. For example: “Eating local food isn’t just about taste – it’s about experiencing a culture through its ingredients.” It reads clean and sounds persuasive because it’s a template learned from thousands of similar examples.

This sort of sentence appears everywhere in AI-generated writing, from LinkedIn posts to marketing copy. While it can sound polished and professional, overuse of this parallelism tends to lack the natural variation of human language.

The rule of three

Humans naturally appreciate information presented in groups of three. “Tell a story, convey emotion, and leave a lasting impression” feels pleasing and memorable. LLMs, however, overdo it. AI-generated content often contains neatly packaged lists of three (or five) points in paragraph after paragraph. While not a red flag on its own, when combined with other patterns like the m-dash or parallel phrasing, it increases the likelihood that you’re reading AI writing.

The uncanny valley of language

AI-generated text often occupies what some call the “uncanny valley” of language. Everything looks correct on the surface: spelling, grammar, structure, even tone. But something still feels off. You might read a phrase like “Harnessing the full potential of daily synergy” and pause, not because it’s wrong, but because it doesn’t quite feel human. The language is almost too polished, too idealised, or subtly awkward in ways that a native speaker wouldn’t naturally phrase.

Overuse of vague positivity

AI tends to lean heavily on vague, overly optimistic language. Words like “innovative”, “impactful”, “empowering”, or “exciting new chapter” often pepper its writing. These adjectives and adverbs sound pleasant but say very little. If a comment or article reads like it’s trying to say something nice without any actual substance, chances are high that it was generated by AI.

AI often tries to sound kind and enthusiastic sometimes overly so. Emails generated by LLMs might say things like “Your travel vlogs are genuinely captivating — I love how you bring every new place to life with such honest and vivid storytelling.” It sounds flattering, but flat. That lack of true individuality or sincerity is another strong indicator.

Unusual analogies and metaphors

AI is increasingly taught to use creative language, but it tends to go too far. This often results in strange or forced analogies that fall flat. For example: “Being able to spot AI writing is like being a lighthouse in the middle of a dense fog.” It tries to sound poetic or profound, but feels hollow or overengineered.

Similarly, similes such as “like a Band-Aid made of sandpaper” are meant to be clever, but often just confuse readers. If a sentence makes you stop and think “wait, what?”, you might be looking at the mechanical fingerprints of a large language model.

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Redundant clarification and filler

AI writing is notorious for reiterating points unnecessarily. It tends to restate its arguments in different ways, sometimes in back-to-back sentences, and provides over explanatory context. For instance: “Social media has changed communication. It’s a new way for people to talk to each other online.” This kind of repetition is not only dull but a clear signal that an algorithm is padding for length.

Similarly, AI often introduces paragraphs with filler that adds no real value: “In today’s fast-paced world…” or “As we continue to innovate…”. Human writers do this too, but AI does it with numbing frequency.

Generic stories and lack of personal touch

Human writing usually contains identifiable voice, perspective, or specific lived experience. Real people share first-person anecdotes or weave in small details, where they live, how they feel, or something that happened to them. AI struggles to do this convincingly unless it is specifically prompted to fabricate stories.

Look for personal pronouns, references to specific events, and unique phrasing. These details anchor a piece of writing in reality and suggest human authorship. Conversely, if everything reads as though it could apply to anyone, anywhere, at any time, it’s probably AI-generated.

Tangents and curiosity

One of the best ways to tell if a piece of writing is human is the presence of tangents, those little asides or off-topic nuggets that show personality and curiosity.

AI tends to stay rigidly on topic, unless specifically prompted to deviate. These detours in human writing, while sometimes meandering, reveal authentic thought processes. AI struggles with this spontaneity and creative looseness.

The vibe check: Trusting your instinct

Perhaps the most important skill in spotting AI writing is learning to trust your gut. If something feels sterile, strangely enthusiastic, or generically polished, it might be written by AI. The vibe check is not about hard logic, it’s about intuition built from consuming human-created content over time. The problem is, as AI becomes more embedded in our daily information diet, that intuition is being eroded.

What makes AI writing particularly challenging to detect now is its increasing sophistication and frequency of use. Even politically significant statements and viral posts may be AI-assisted. While these tools can be helpful, they’re also flooding public spaces with synthetic voices, which makes human discernment even more critical.

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Final thoughts: Stay aware and share

As large language models continue to advance, learning how to spot AI writing is essential. From overused punctuation like the m-dash to eerie tonal consistency and lack of personality, AI writing has patterns that are visible to trained eyes. However, it’s also getting better at masking those patterns, especially when guided by skilled users.

That’s why spreading awareness is key. Teach others how to spot the signs, and remain conscious of how often AI is involved in the content we consume. The next phase won’t just involve spotting machine-generated text, it’ll be about understanding how much of our digital world is shaped by algorithms and what that means for genuine human communication.

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