What words does ChatGPT use most?

The recurring ones are elevated synonyms for ordinary words and formulaic connectives: delve, leverage, utilise, robust, landscape, realm, tapestry, testament, furthermore, moreover, and hedges like can potentially or may help to. None is wrong in isolation. What marks generated text is finding five or six of them clustered in a few hundred words.

Why does AI overuse the word delve?

Its frequency in model output far exceeds its frequency in ordinary English. The leading explanation involves the preference-rating stage of training, where raters whose regional English favours more formal diction shaped which drafts scored well. Whatever the cause, it makes a useful marker precisely because so few people say it naturally.

Does removing these words make text undetectable?

No. Detectors do not check for a vocabulary list; they measure statistical predictability across the whole text. Swapping flagged words for synonyms leaves the sentence structure, rhythm, and hedging untouched, which is where most of the signal lives. Structural editing does far more than vocabulary substitution.

What should I use instead of these words?

Mostly the plain equivalent: use for utilise, help for facilitate, look at for delve into. But a surprising number need deleting rather than replacing — it is important to note that, in today's fast-paced world, and in conclusion usually improve the sentence by their absence. Vague intensifiers like significant should be replaced with an actual number.

How do I check my draft for these phrases?

Three minutes with Ctrl+F. Search for leverage, landscape, robust, and delve; more than one or two across a full article warrants a second look. Then search for it is important to note and in today's, which are almost always deletable in full. Then significant and very, each of which either gets a number or gets cut.

15 Words and Phrases That Give Away AI Writing

Q: Are these words banned from writing?

No, and treating them as banned makes writing worse. Robust is precise in statistics. Framework is the right word for a framework. Furthermore is fine when a genuine additive relationship needs marking. A word list identifies candidates for scrutiny, not prohibitions, and prose that visibly avoids ordinary vocabulary reads as strained in its own way.

The specific words and phrases that overwhelmingly show up in AI-generated text — and what to use instead so your writing reads naturally.

Every writer has verbal tics. AI models have them too — except a model's tics are shared across millions of outputs, which is exactly why they're so recognizable. If you've read enough AI-generated content, certain words start jumping off the page before you've even processed the sentence around them.

Here are 15 of the most common offenders, organized by why they show up so often, plus what to write instead.

Phrases that pad without adding meaning

1. "It's important to note that" — If it's worth saying, just say it. This phrase almost never changes the meaning of the sentence that follows it.

2. "In today's fast-paced world / digital landscape" — A scene-setting phrase so generic it could preface literally any sentence about any topic. Cut it and start with your actual point.

3. "At the end of the day" — Meant to signal a bottom-line conclusion, but it usually just delays getting to one.

4. "When it comes to [topic]" — A throat-clearing opener. Try starting the sentence with the topic itself instead.

5. "Needless to say" — If it's needless to say, don't say it.

Words that sound substantial but say little

6. "Landscape" ("the competitive landscape," "the regulatory landscape") — Nearly always replaceable with a plainer word: "market," "rules," "field."

7. "Realm" ("in the realm of," "within the realm of possibility") — Adds formality without adding information.

8. "Robust" — Used to describe everything from software to strategies to arguments, to the point that it's stopped meaning anything specific. Say what's actually strong about it.

9. "Leverage" (as a verb) — "Leverage synergies," "leverage your network." Almost always replaceable with "use."

10. "Delve" — A small but reliable tell. Most human writers say "look into" or "dig into," not "delve into."

Transitions doing too much work

11. "Furthermore" / "Moreover" — Formal connective tissue that AI text reaches for constantly, often between two sentences that don't need a bridge at all.

12. "That being said" — A hedge before a hedge. Usually the sentence works fine without it.

13. "In conclusion" — A closing paragraph doesn't need to announce itself. Readers can tell when a piece is ending.

Hedges that avoid commitment

14. "Can potentially" / "May help to" — Doubled-up hedging (potentially and may) that avoids saying anything definite. If you believe something works, say it works, with the specifics that back it up.

15. "A testament to" ("a testament to its resilience," "a testament to the team's hard work") — A stock phrase for praising something without describing what's actually praiseworthy about it.

Why this list matters more than it seems

None of these words are grammatically wrong, and using one occasionally isn't a problem — real writers use hedges and transitions too. What gives AI writing away isn't any single word on this list; it's the density. When five or six of these show up in a single 300-word section, that clustering is the actual signal, because a human writer's vocabulary naturally varies more than a model's does.

A quick self-edit test: search your draft (Ctrl+F) for "leverage," "landscape," "robust," and "delve." If you find more than one or two across a whole article, that's worth a second pass.

Fixing this at scale

Manually hunting for these phrases works for a single article, but it gets tedious fast if you're editing AI-assisted content regularly. Our Text Humanizer rewrites exactly this kind of phrasing automatically — stripping hedging filler and generic abstractions while preserving your original meaning — so you can paste in a draft and get back something that doesn't trip these tells. For the structural side of the problem (not just word choice), see why AI writing sounds robotic.

Why these particular words

It is worth knowing why this vocabulary clusters the way it does, because the reasons predict which words will join the list next.

Frequency wins. A model picks likely words. Across a huge corpus, "utilize" is a common formal alternative to "use," "landscape" a common metaphor for a domain, "robust" a common adjective for strength. None is remarkable individually; each is the safe pick at that position, and safe picks accumulate.

Preference tuning rewards caution. Human raters penalise confident wrongness more than vagueness, so hedged phrasing gets systematically reinforced. "Can potentially help" is trained behaviour, not an accident.

Register bleed from training data. Corporate and academic prose is heavily represented, and it is where "leverage," "synergy," "framework," and "a testament to" live. Models produce that register because they read a great deal of it.

"Delve" is a genuine anomaly. Its frequency in model output far exceeds its frequency in ordinary English, and the leading explanation involves the preference-rating stage — raters whose regional English favours more formal diction shaping which drafts scored well. Whatever the cause, it makes a useful marker precisely because so few people say it naturally.

The predictive value: any formal, slightly elevated synonym for a common word is a candidate. When "delve" becomes too well known and gets tuned out, something adjacent will take its place. The category is stable even as the membership rotates.

Words this list gets wrong

Two failure modes worth guarding against, because word-list advice causes real damage when applied mechanically.

These are not banned words. Every one has legitimate uses. "Robust" is precise in statistics. "Framework" is the correct word for a framework. "Furthermore" is fine when a genuine additive relationship needs marking. A list like this identifies candidates for scrutiny, not prohibitions — and writing that visibly avoids ordinary vocabulary reads as strained in its own way.

Density is the signal, not presence. One "landscape" in an article means nothing. Six of these in a 300-word section, alongside uniform sentence rhythm, is the actual pattern. A human vocabulary varies more than a model's, so clustering is what distinguishes them.

The related mistake is assuming the reverse holds. Removing every word on this list does not make text human-written, and their absence proves nothing about authorship. Detectors do not check for them, and neither should readers drawing conclusions about someone's work — the reasoning is in how AI content detectors actually work.

The replacements

A word list is only useful with something to put in the gap.

| Instead of | Try | | --- | --- | | Utilize | Use | | Leverage (verb) | Use, or name the action | | Delve into | Look at, dig into, examine | | Landscape / realm / space | The actual field: "the B2B software market" | | Robust | The specific property: fast, well-tested, hard to break | | Facilitate | Help, let, make possible | | A testament to | Say what it demonstrates and how | | In today's fast-paced world | Delete | | It is important to note that | Delete | | Furthermore / Moreover | Delete, or "and," or start the sentence | | That being said | But, though, or delete | | In conclusion | Delete | | Can potentially help | Helps, or say under what conditions | | Significant / substantial | A number | | Seamless | What does not break, and how you know |

Notice how many entries are just "delete." Filler openers and formal transitions usually need removing rather than replacing, and the sentence is better for it — which is also why substituting synonyms does so little. Swapping "moreover" for "additionally" leaves the structural problem exactly where it was.

A five-minute pass

Search for the four highest-signal words: "leverage," "landscape," "robust," "delve." More than one or two across a full article warrants a second look.
Search for "it is important to note" and "in today's." These are almost always deletable in full.
Search for "significant," "substantial," and "very." Each one either gets a number or gets cut.
Read the first two words of every sentence in one section. Repeated formal transitions surface immediately.
Read the whole thing aloud. Stock phrases are more obvious spoken than scanned.

Steps 1 through 3 take about three minutes with Ctrl+F and catch most of what this list covers.

Our Text Humanizer handles this vocabulary layer automatically while preserving meaning, which is faster if you edit AI-assisted drafts regularly. What it will not do is step 3's real work — supplying the actual number in place of "significant" — because that requires knowing the number. For the structural problems underneath the word choice, which matter more, see 12 sentence patterns that make prose sound machine-made.

Vocabulary is the surface layer. For the habits underneath it — rhythm, specificity, and committing to a claim — see how to write like a human.