Can You Tell AI Text From Human? 11 Dead Giveaways

I used to think I was pretty good at spotting AI writing.

Like, I’d read a paragraph and instantly go, yep. That’s a bot. Too smooth. Too… polite.

Then it got harder. A lot harder.

Now I’ll read something that feels human. A tiny bit messy. Even funny. And still, there’s this weird sense that nobody actually lived through what they’re describing. It’s like reading a brochure written by a very confident ghost.

So can you tell AI text from human?

Sometimes, yes. Not because AI is “bad” at writing anymore. But because it tends to be bad at being a person on a page. It misses certain little moves humans do without thinking. Or it overdoes them. Or it avoids risk so aggressively that the whole piece becomes… safe. Inoffensive. Weightless.

Here are 11 dead giveaways. Not “gotchas” in a lab setting. More like, real world patterns you start seeing once you’ve edited a lot of AI assisted drafts.

1. It says a lot. But you finish the paragraph and learned nothing.

This is the big one.

AI can generate a paragraph that looks meaningful, especially if you skim. But when you slow down, it’s basically fog.

Example vibes:

• “In today’s fast paced digital landscape, leveraging innovative solutions is essential for sustainable success.”
• “This approach helps businesses streamline workflows and achieve better outcomes.”

Okay. Better outcomes how. Which workflows. What changed. Who is this for.

Humans do write fluff too, sure. But humans usually slip and reveal intent. They’ll accidentally get specific. They’ll mention a detail they didn’t need to mention. A number. A tool. A weird edge case. AI tends to float above the ground unless you force it down.

If you’re editing AI content, your fix is simple but annoying: keep asking “what do you mean” until there’s nowhere left to hide.

2. The intro is perfectly “hooky” but strangely interchangeable

A lot of AI intros feel like they came from the same template.

You know the ones:

• Question hook.
• Bold claim.
• “In this article, we’ll explore…”
• Immediate list preview.

Nothing technically wrong. But if you replace the topic with something else, the intro still works. That’s the giveaway.

A human intro usually has at least one of these:

• A specific moment. “Last Tuesday I…”
• An opinion they’ll have to defend.
• A slightly awkward transition. Because real people don’t outline their thoughts like a PowerPoint.

AI intros read like they were optimized for “good writing” instead of written to communicate something real.

3. It over explains the obvious, then skips the part you actually need

This is one of those patterns I can’t unsee now.

AI will spend 120 words explaining what SEO is. Or what content marketing is. Or what “tone” means.

Then when you get to the part where the reader actually needs help, it goes vague again.

Humans (especially practitioners) usually do the opposite:

• they assume a baseline of knowledge
• they rush past definitions
• they slow down on the part that’s painful in real life

So if you’re reading an “expert” article and it sounds like it’s teaching a beginner, but also never shows the beginner how to do anything, that’s a smell.

4. The transitions are too clean. Like every paragraph is holding hands

Humans don’t transition like a textbook all the time.

AI loves these:

• “Moreover…”
• “Additionally…”
• “Furthermore…”
• “In conclusion…” (halfway through the article)
• “Let’s dive in…”

It’s not just the words. It’s the feeling that every paragraph was generated to be neatly attached to the previous one, even when the idea doesn’t truly follow.

Human writing has friction. Little jumps. Tangents. A paragraph that starts with, “Actually, wait.”

And yes, you can prompt AI to be more conversational. But often it still sounds like a polite tour guide.

5. It uses “industry standard” examples that nobody actually uses

AI loves examples that are technically plausible but emotionally fake.

Like:

• “Imagine you run a bakery and want to improve your online presence.”
• “A fitness brand might use email campaigns to engage customers.”
• “A SaaS company can leverage data driven insights.”

Humans pick examples that betray their life. Or their obsessions. Or their clients. Even if they anonymize things, it still feels like it happened.

If you want AI text to pass as human, the fastest way is adding real examples. Even small ones.

Not “a bakery”. More like:

“We changed one heading on a pricing page, and trial signups didn’t move at all. Then we swapped the CTA language, and it jumped 18 percent in a week. I hate how often it’s the dumbest change that matters.”

AI won’t write that unless you give it that kind of lived detail.

6. It’s allergic to being wrong. Or being controversial. Or being… anything

This one is subtle. But once you feel it, you feel it.

AI writing often avoids clear positions because clear positions can be challenged.

So you get a lot of:

• “It depends.”
• “There are pros and cons.”
• “The best approach is to evaluate your needs.”
• “Different businesses have different goals.”

Which is true. And also useless.

Humans will say:

• “I don’t like this method and here’s why.”
• “Most people should not do X until they’ve done Y.”
• “If you’re a small site, forget Z. It’s a distraction.”

They might be wrong. But they’re someone.

AI’s safety instinct becomes a style tell.

7. The structure is suspiciously balanced

Humans don’t naturally write in perfect blocks.

AI loves symmetry:

• every section is 120 to 160 words
• every bullet list has 5 bullets
• every heading is the same length
• every takeaway has the same cadence

It feels “produced”.

A human article might have:

• one section that’s long because the author cares
• one section that’s short because they got bored
• one section that’s basically a rant

If your listicle reads like it was poured into a mold, it might’ve been.

8. Repetition that doesn’t look like repetition at first

AI repeats itself in disguise.

Not word for word. More like the same concept restated with new synonyms.

You’ll see:

• “streamline”
• “optimize”
• “enhance”
• “improve efficiency”
• “boost performance”

And you realize all five phrases are doing the job of one clear sentence.

Humans repeat too, but usually with intention. AI repeats because it’s filling space, or because it’s circling around an idea it can’t sharpen.

Editing trick: highlight every sentence that doesn’t add new information. Delete ruthlessly. The piece will often shrink by 25 percent and get better.

9. The “voice” tries a little too hard

This one shows up a lot in “humanized AI” attempts.

You’ll see:

• forced contractions everywhere
• random “honestly” and “to be fair”
• quirky one liners that don’t match the topic
• fake vulnerability: “I’m not perfect, but…”

It reads like a persona.

Humans have voice because they have constraints. Mood. History. Bias. Fatigue. AI voice is often a costume unless it’s guided with real source material and heavy editing.

And even then, it’s easy to overdo it.

If you’re trying to write more naturally, you don’t need more “quirk”. You need more specificity. More real decisions. More actual opinion.

10. It cites nothing. Or it vaguely gestures at “studies” and “data”

AI will say things like:

• “Studies show that long form content performs better.”
• “Data indicates that internal linking improves crawlability.”
• “According to research…”

Which research. Which study. Where.

Humans who know their stuff either link sources or they talk from experience. They’ll say, “I ran this test” or “Here’s what I’ve seen across 30 posts.”

When AI does include stats, they’re often untraceable unless it was forced to use sources. This is one reason AI detection by “feel” still works. The writing sounds confident, but the foundation is missing.

If you’re publishing for SEO and credibility, you want your content to be grounded. Even basic citations, or screenshots, or internal data. Something.

11. It nails grammar, but misses human intent

This is the weirdest giveaway, and maybe the most reliable.

AI can produce near perfect grammar. Clean punctuation. Clear sentences.

But it often misses the invisible stuff:

• what the reader is actually worried about
• what they will misunderstand
• what they will do next, in the real world
• what objections they’ll have

A human writer anticipates a reader’s skepticism almost automatically.

AI tends to explain the topic. Humans tend to solve the moment.

That’s why some AI content ranks for a bit, then drops. People bounce. They don’t feel helped.

A quick reality check: AI detection is messy now

Let’s be honest. Tools that claim they can “detect AI” with certainty are… shaky.

Some will flag a well edited human piece as AI. Some will miss obvious AI. And as models improve, surface tells disappear.

So if your goal is “passing detection”, that’s a bad target. It’s a cat and mouse game.

A better target is: does the content feel like it came from a real operator. Does it answer the query. Does it earn trust.

That’s the standard that actually matters. For readers, and for Google, and for you.

What to do if you’re using AI for content (without publishing soulless pages)

If you’re writing everything manually, cool. Skip this.

But if you’re using AI to scale content, which is… most teams now, you need a process that forces the human parts back in. Otherwise you end up publishing 100 articles that all kind of sound like each other. And you wonder why nothing sticks.

Here’s a simple workflow that works.

1. Start with strategy, not prompts

AI can write. It’s bad at deciding what’s worth writing, in what order, for what intent.

That’s why “hands off” only works if the system is actually doing the scanning, planning, and clustering properly.

This is basically the pitch behind platforms like SEO software. It scans your site, generates a topic and keyword strategy, writes the articles, then schedules and publishes them. With internal linking and images and all the boring parts that usually stall content teams.

If you want to see what that looks like in practice, their AI SEO editor is a good place to start. It’s the part where you can actually shape the output instead of praying the model “gets it”.

2. Put a human editor in the loop, even if it’s you for 20 minutes

You don’t need a full rewrite. You need targeted edits:

• delete fluff intros
• add one real example
• add one opinion
• add one constraint. “This won’t work if…”
• fix the CTA so it matches the content

That alone removes half the “AI vibe”.

3. Build a repeatable checklist, not a vibe check

Here’s a quick checklist you can literally paste into your process:

• Did we answer the search intent in the first 15 seconds?
• Did we include at least one specific example or mini story?
• Are there any paragraphs that say nothing when you reread them slowly?
• Did we make at least one clear recommendation?
• Are we repeating ideas with synonyms?
• Are there citations or proof where we made claims?
• Does the conclusion tell the reader what to do next?

If you do this, your content starts sounding human because it starts behaving human. It becomes useful.

4. Don’t rely on one model. Or one tool. Or one prompt

A lot of the criticism around “AI content is bad” is really about it being “unedited first draft content”.

If you're looking for a solid overview of different approaches, this roundup of AI writing tools is worth skimming. Even if you don’t switch tools, it helps you think in terms of workflows, not just text generation.

And if your focus is SEO specifically, you want a system that handles internal links, publishing, and updating older posts too. That’s where pure writing assistants fall short.

A small test you can run right now

If you want to practice spotting AI vs human, do this:

1. Open any article you suspect is AI.
2. Highlight every sentence that could belong in any article on the same topic.
3. If you can highlight more than half the piece, it’s probably AI, or heavily AI shaped.

Because the opposite of “AI sounding” is not “more slang”.

It’s specificity. Stakes. Proof. Opinion. A little mess.

The stuff that comes from being a person who had to actually decide what they believe.

Wrap up

So, can you tell AI text from human?

Not with perfect accuracy. Not forever. But right now, yes, pretty often.

Look for the fog. The symmetry. The safe transitions. The examples that feel like stock photos. The confidence without proof. The lack of real decisions.

And if you’re the one publishing content, the goal isn’t to trick an AI detector anyway. It’s to publish pages that don’t feel interchangeable.

If you want the “hands off” route without the usual robotic output problem, take a look at SEO software. It’s built for automated content marketing, strategy to publishing, with editing and rewrites baked in. The difference, when it works, is that you stop shipping generic articles and start shipping a system.

And yeah. Readers can tell. Even when they can’t explain how.