You’re sitting at your desk, reading an email. It’s well-written. Formal, even. Then you hit it: This is a pivotal moment for our company’s synergy.
You can’t help it, your eyes glaze over. You’ve just stumbled onto a tell. It’s the geeky equivalent of finding a pattern in a sea of noise, except instead of a bug in a video game, it’s a flaw in the prose. You can’t unsee it.
You’re not alone if you get this feeling. A recent Pew Research Center survey found that 76% of Americans say it’s important to distinguish between AI and human writing, but only 12% feel confident they actually can. That gap is exactly what we’re here to close. Welcome to your field guide to the “AI words to avoid,” a practical look at the linguistic fingerprints machines leave behind.
We’re going to dig into the words and phrases that scream “artificial intelligence,” why they sound that way, and how to talk about it all like a human. Think of this as your cheat code for the most passive-aggressive boss of all: the machine.
Key Takeaways
“Delve” is a canonical tell, but the real signal comes from overused patterns like “provide valuable insights,” which appears a massive 902 times more often in AI text.
The reason AI falls back on these words is a mechanism called reinforcement learning from human feedback, where models latch onto words that human evaluators rewarded during training.
The most effective way to avoid false flags isn’t a better detector, but rather adding the personal insight and messy specificity that no algorithm can fabricate.
Table of Contents
Why AI writing sounds the way it does
AI-generated text carries statistical fingerprints, and learning to read them is more of a pattern-recognition game than a vocabulary list. The core reason is baked into how these models work. Large language models like the one powering ChatGPT, which launched in November 2022, generate text by predicting the next most likely word. That’s it. It’s a super-powered autocomplete, chewing through a massive amount of training data to guess what should come next.
But the why behind the “delve” obsession is even more interesting. It’s not just about statistical probability, it’s about reinforcement. During training, models use a technique called reinforcement learning from human feedback (RLHF). Human evaluators would rate different responses, and models learned to favor the words those evaluators approved of. To keep your creativity and originality at the core of your work, co-create with AI rather than letting it take the lead.
As it turns out, somewhere along the line, “delve” was the word that scored points with the judges. It didn’t appear by accident, it was a learned behavior rewarded into existence.
This process leaves distinct signatures that stand out to a trained eye. While AI is good at organizing ideas, improving readability, and speeding up content creation, it often lacks the personality and creativity that make writing distinctly human.
Why certain words get picked up and repeated
When you read an AI-generated essay, you’re actually seeing the output of that RLHF reward loop. It’s why you get a formal, robotic tone, repetitive phrasing, and a distinct lack of personal stories or unique perspectives. The text tends to be predictably polished, yet completely hollow. This is also why AI loves to hedge its bets with qualifiers like “generally speaking” or “to some extent” to avoid sounding absolute.
The result, when it goes wrong, can be painfully stiff. It’s the verbal equivalent of wearing a suit to a hackathon.
The AI tell lexicon: words and phrases to avoid
The lexicon of AI tells is your working list of words and phrases to spot, and swap for more natural alternatives. Think of it as building a mental library of “living” signatures. The pattern of overuse is more telling than any single word. So, let’s get into it and uncover the list of overused AI words that should be on your radar.
Delve into
Start with the poster child, the benchmark by which all other tells are measured: “delve.” Its more sophisticated cousin, “delve into,” means to investigate deeply. On its own, it’s a fine phrase, but AI leans on it constantly. A freshly written article hitting that word for the third time is a huge red flag, and now the floodgates open.
The phrase “let us delve” is a walloping 123 times more frequent in AI text. This didn’t go unnoticed by researchers, either, with the word “delve” doubling in frequency on the web in the months after ChatGPT launched.
Underscore
Next up is “underscore,” another word that loves to make things sound more important than they are. While “highlight” is often a human’s first instinct, “underscore” feels like reaching for a more formal, more official word. GPTZero and Pangram both flag it as a consensus tell.
Pivotal
“Pivotal” is another favorite for overstating the importance of something. Simpler alternatives like “important” or “crucial” often do the trick, but “pivotal” carries a sense of drama that AI just can’t resist. For instance, “plays a pivotal role in shaping” appears 131 times more often in AI text than in human writing. There’s nothing wrong with “important” now and then, especially if it means saving yourself from sounding like a PR bot.
Realm
“Realm” is a classic example of a perfectly good word that’s been weaponized by natural language processing. The next time you reach for “realm,” try “area” or “field” instead. The word “realm” just means a field, domain, or area of interest, but it feels like writing from a fantasy novel. Detectors like Pangram flag it, and its plural form, “realms,” is also suspect.
Harness
“Harness” is the kind of word that sounds active and powerful, which is exactly why AI loves it. In the tech world, no one just “uses” AI; they “harness” its power to shape the future. This gives me a great segue to the simpler, better alternative: “use.” It’s the natural, human choice.
Illuminate
“Illuminate” sounds poetic, but in the context of a technical write-up, it’s usually just “explain” wearing a costume. The meaning is fine, but the word has become such a cliché that it’s almost a parody of itself. Save “illuminate” for actual light sources and use “explain” to get your point across clearly.
Shed light on
If you’re looking for the biggest red flags, look no further than phrases like “shed light on.” It’s another metaphor that AI simply cannot get enough of. This phrase is so overused that it’s a screaming tell, appearing 130 and 120 times more frequently in AI-generated text.
That being said
In place of “that being said,” a simple “however” or “even so” is much cleaner. This transition phrase shows up constantly as a default way to add a caveat, and it’s a core part of the AI’s narrative DNA. Once you’re looking for it, you’ll notice it sneaking into AI writing all the time.
At its core
When introducing a definition, AI loves to fall back on “at its core.” It’s not wrong, but it’s a default opener. Before you let the machines take all the credit, try “fundamentally” or “essentially” to mix up the rhythm.
To put it simply
AI uses “to put it simply” as a signal that it’s about to explain something. It’s a self-aware wink to the user that they’re about to get a breakdown of a complex idea. Human writers tend to just explain things directly, making phrases like this a unique tell.
This underscores the importance of
The phrase “this underscores the importance of” is a compound tell: it’s a clunky merge of “underscores” with a prepositional phrase. This is the kind of phrase that makes AI writing sound stiff and textbook-like. Try “highlights the need for” or simply “shows” for a more direct approach.
A key takeaway is
When you see this phrase, you know the AI is wrapping up. It’s a formulaic way to emphasize a central point. “The main point is” or “one important lesson is” might feel less repetitive after the fifth or sixth use in a single document.
From a broader perspective
This one is a surefire way to signal you’re about to get philosophical, even if you’re just summarizing. “When you zoom out” or “on a larger scale” feel more natural and less like a lecture.
Generally speaking
If you’re looking to sound more decisive, you might want to follow the lead of Hemingway and avoid this one. “Generally speaking” is a way to state something as a general rule, but it always feels like you’re hedging your bets. After a while, it just becomes noise.
Typically
“Typically” is a subtle tell, but it’s there. It’s just a more formal-sounding “usually” that models embrace, adding to that slightly stiff, professor-stuck-in-the-80s feel.
Tends to
Like “typically,” “tends to” is a standard hedge that makes a claim sound softer. It’s not as loud as “delve,” but it’s a frequency marker. A shorter “is often” or “usually is” is usually a better fit.
Arguably
“Arguably” is AI’s way of sounding balanced and thoughtful on a topic on which it has no actual opinion. Technically, “some may say” is a bit wordy. But it’s a clear marker of a machine trying to sound like it’s having a considered debate with itself.
To some extent
When a model needs to sound nuanced, it whips out “to some extent.” It’s a non-committal qualifier that softens a claim. “Partially” or “to a certain degree” are slightly better, but cutting it entirely often gives the sentence more power.
Broadly speaking
Just like “generally speaking,” this is a go-to phrase for introducing a generalization. It’s conversation filler and adds no real information. When you see it, you know you’re in for some degree of hand-waving.
Facilitate
“Facilitate” is corporate-speak for “make easier.” Yet, in the world of large language models, this is a vocabulary goldmine. It’s a fancy way to say something that has a much simpler and more direct English equivalent.
Refine
“Refine” is a bit like using a thesaurus. You have to be careful with it because it can easily result in nonsense. But in the hands of an AI, it’s just a way to describe making something better.
Bolster
“Bolster” is another word that sounds like it’s up to no good. In normal conversation, you “support” a claim with evidence, you don’t “bolster” it with data. It’s the kind of academic-sounding word that is a tell-tale sign of a trained algorithm.
Differentiate
“Differentiate” is a more formal-sounding version of “distinguish” or “tell apart.” It’s a core concept for these models, since they’re essentially trying to tell the difference between patterns.
Streamline
Is there a more overused business buzzword than “streamline”? It’s a verb that describes a process, not a magic spell. It’s the kind of word that has penetrated the tech sphere, and its overuse in AI output makes it a dead giveaway.
Revolutionize
To “revolutionize” is one of the biggest hype words around. It’s not just about changing things; it’s about overturning the entire system. This one is so over-the-top that it’s become a major target for platforms like Pangram.
Innovative
“Revolutionize” and “innovative” go hand-in-hand. But just because a model can generate the word doesn’t mean the thing it’s describing is actually new or creative.
Cutting-edge
Another way to signal that something is “new” is to call it “cutting-edge.” This phrase may have lost all meaning. A more honest phrase might be “state-of-the-art.”
Game-changing
If everything is “game-changing,” then nothing is. This hype phrase has been used so much in the tech sector that it’s starting to lose its significance.
Transformative
The wording here is a major tell, but it’s a word that gets slapped on anything that makes a difference, no matter how small. It’s often a sign that the author is trying to add weight to an otherwise minor update.
Seamless integration
A favorite in cybersecurity circles, “seamless integration” sounds great in a press release. If you want to catch the eye of a human reader, however, “smooth compatibility” or “works effortlessly with” is a much better choice.
Scalable solution
Ask three different tech people what a “scalable solution” means, and you’ll get six different answers. That’s because it’s a meaningless phrase meant to sound impressive.
Provide valuable insights
Welcome to the crown jewel of obvious AI tells. “Provide valuable insights” is the king of the hill, the Terminator of AI phrases. It’s a phrase so ubiquitous that it’s practically a punchline, appearing 902 times more frequently in AI-generated text than in human writing. Need something more human? Say “share useful findings” or “show what matters.”
Gain a comprehensive understanding
Similar to its cousin above, this phrase signals a lack of confidence. “Really understand” works just fine, but you’re not wrong if you prefer to sound like you’re selling a course.
Study provides a valuable
Here’s a phrase that feels like you’re writing a research paper. “Offers something useful” or “helps us understand” flows much more naturally than this academic-sounding phrase.
Casting long shadows
Even creative writing is not safe from the uncanny valley. “Casting long shadows” sounds like it came straight from the pages of a novel, as evidenced by it being 561 times more likely to be used by an AI. It’s a dramatic, tense phrase, but it doesn’t belong in a technical explanation.
Left an indelible mark
“Left an indelible mark” should be reserved for important historical moments. Take it from them: your software update isn’t an era-defining event. It’s just a patch.
An unwavering commitment
When you see a lot of adjectives, you know it’s a tell. Adding “unwavering” before “commitment” rarely helps your case and often makes it sound defensive.
Plays a crucial role in shaping
“Plays a crucial role in shaping” is a mouthful that sounds almost plausible, but it’s on the nose. This is a classic example of AI’s tendency to pad its language.
Played a significant role in shaping
This phrase often appears in a historical context to describe something very important. But in a technical brief, it’s better to be direct.
A rich tapestry
When a model is trying to paint a picture, it goes for “a rich tapestry.” It’s a vivid image that gets overused, especially when the topic at hand is just a new line of products.
Opens new avenues
“Opens new avenues” is a metaphor that AI adores. This one’s a little too flowery for a technical read.
Help to feel a sense
This is a classic case of a misplaced modifier. “Help to feel a sense” is grammatically awkward, yet AI is trained to reproduce it.
Adds a layer of complexity
Instead of saying “complicates things,” AI reaches for “adds a layer of complexity.” It might be useful to think of this as “muddying the waters.”
Research needed to explore
If your thesis is that we need more research, you’re off to a bad start. This is another one of those filler phrases that has been shot to death.
How to spot AI in the wild
Spotting AI text in the wild is about recognizing patterns, not just a single word on a list. It’s a statistical exercise, not a word search. This creates a more complex set of tells that go beyond single words. These are the stylistic tics and formatting choices that give a machine away, and they’re often more reliable than any single word. Researchers collected monthly data from Common Crawl spanning January 2021 through July 2026, described as ‘as close to a full scrape of the observable internet as they can get.’
Punctuation and rhythm tells
In a 2023 study, researchers at the Pew Research Center found some compelling punctuation tells. The number of em dashes in text has doubled since 2024, and the use of Oxford commas is up 63%. Negative parallelisms (“it’s not X, it’s Y”) have nearly tripled. These are the quirks of a model’s statistical tendencies.
It’s also fascinating that different models have different “tells.” ChatGPT tends to use em dashes more than a human, while its rival, Google’s Gemini, uses them less.
Formatting and structural tells
Beyond individual words and punctuation, there’s the bigger picture of structural tells. Look at the use of predictable formatting: title-case headings and neat bullet points. The prose often has a uniform rhythm and might use “hollow” transitions that don’t hold up to close inspection.
Why AI detectors flag your writing
The real risk of AI-flavored writing isn’t just that someone might feel like it’s robotic; it’s that detection tools can flag you, and those tools are less reliable than you’d hope. The tools work, but they’re not perfect, and their use case has real-world consequences.
How AI detection works
AI detectors use statistical analysis to try and figure out if a human or a machine wrote a piece of text. They look at word choice, sentence rhythm, and that punctuation distribution we just talked about. Advanced algorithms can then integrate semantic analysis, looking at the meaning behind the words, along with syntactic patterns, to make a judgment. It’s a multifaceted process, and it rarely comes down to a single factor.
The commercial stakes of a false positive
But here’s the problem: these tools are imperfect. GPTZero, founded in January 2023, self-reports a 99% accuracy rate on AI text detection, but also admits its false positive rate is under 1%. That’s 1 in 100 people who might not have done anything wrong. The same tool that powers plagiarism checks in 3,500 colleges says its accuracy improves with longer inputs and is strongest on English prose.
As a result, false positives hit non-native English writers the hardest, which is why debates about fixed thresholds, such as what is the 30% rule in AI, often miss the point. As the expert said, “I get nervous when we’re trying to use a single score to make a consequential decision, like in a hiring or academic integrity case.”
Humanizing AI text
So, how do you make your writing sound less like a robot wrote it? Start with these simple tweaks.
What humans do that AI can’t
First, cut the hedging qualifiers. Words like “generally speaking” and “to some extent” slow you down and make you sound less confident. Also, infuse your writing with something AI can’t fabricate: personal experience. Add a specific anecdote or a unique point of view.
You can also adjust the tone and style to be more surprising or original. Remember, AI is great at organizing ideas and making text more readable, but it often lacks the personality and creativity that only you can bring.
The practical rewrite process
Don’t just rely on a thesaurus. Think of your first AI draft as a sketch, not a final product. You have to take the most valuable human asset, your own voice, and inject it into every sentence. A 2024 study of over 12,000 human essays found that human writers used over 11,000 unique words, while AI used only 7,000.
This is because humans are messier. 78% of human essays had at least one mistake, versus only 13% of AI essays. We’re also more direct. Human essays led with simpler words like “people,” “also,” and “one,” while AI used more complex vocabulary like “social,” “cultural,” and “individuals.”
The back-and-forth: AI is changing human writing too
The influence isn’t one-directional. As much as AI is trained on human writing, it is also changing the way humans write. This is the fresh angle that turns a static list into a dynamic system. And it’s happening in real-time.
The moving target problem
Researchers have anecdotal evidence that people are changing their writing to avoid AI-associated tells, like em dashes. Plus, just a few interactions with a chatbot can alter your own vocabulary. This makes the whole thing a moving target. The tells themselves are changing: “delve” is already on its way out for newer chatbot versions, and companies like OpenAI are working to control their models’ reliance on the em dash. By the time you memorize the list, the models have already changed.
Using AI responsibly
The most effective way to use AI is as a collaborator, not a ghostwriter. The honest way forward is to be transparent about your process.
The transparency toolkit
If you use a tool like Grammarly, turn on its Authorship feature before you start drafting. It documents your writing process and removes any ambiguity. Cite AI use just like you would any other source. And know your field’s standards for what’s acceptable.
Why human connection beats any detector
The ultimate defense against AI plagiarism won’t be a better detector or a bigger word list; it’s human connection. When teachers know their students, they can spot a misalignment in voice or a strangely complex phrase. It’s the same in any field: a “1984” George Orwell might be a great writer, but if you’re writing about your company’s org chart, human connection is the ultimate truth-teller.
Frequently Asked Questions
What words should I use to avoid AI detection in writing?
To avoid AI detection, swap out common AI tells like ‘delve,’ ‘underscore,’ ‘pivotal,’ and ‘realm’ for simpler, more direct words like ‘explore,’ ‘highlight,’ ‘important,’ and ‘field.’ Also, cut hedging phrases like ‘generally speaking’ and ‘to some extent,’ and add personal anecdotes or unique perspectives that AI can’t fabricate.
What are chatgpt flag words?
ChatGPT flag words are terms and phrases that AI detectors and human readers often associate with machine-generated text. These include ‘delve,’ ‘pivotal,’ ‘realm,’ ‘harness,’ ‘illuminate,’ ‘shed light on,’ ‘that being said,’ and ‘provide valuable insights.’ They appear much more frequently in AI text than in human writing.
What should you not say to AI?
You shouldn’t say anything that relies on overused AI phrases like ‘delve into’ or ‘at its core’ if you want to sound human. Instead, be direct and specific. Avoid asking AI to ‘provide valuable insights’ or ‘gain a comprehensive understanding’—these are tells that signal robotic writing.
How does AI detection work?
AI detectors use statistical analysis to evaluate word choice, sentence rhythm, and punctuation patterns. They look for tells like excessive em dashes, Oxford commas, and negative parallelisms. Advanced tools also analyze semantic meaning and syntactic patterns to make a judgment, but they’re not perfect and can produce false positives.
Why does AI writing sound robotic?
AI writing sounds robotic because models are trained to predict the most likely next word, leading to overuse of certain formal words and phrases. They also rely on hedging qualifiers and formulaic transitions, which makes the text feel stiff and lacking in personality. Human writing is messier, more direct, and includes personal experiences.
What are the most common AI writing tells?
The most common AI writing tells include words like ‘delve,’ ‘pivotal,’ ‘realm,’ ‘harness,’ and ‘illuminate,’ as well as phrases like ‘shed light on,’ ‘that being said,’ and ‘provide valuable insights.’ Punctuation patterns like em dashes and Oxford commas are also strong indicators.
How can I make my writing sound more human?
To sound more human, cut hedging qualifiers like ‘generally speaking’ and ‘to some extent,’ and replace AI-favored words with simpler alternatives. Add personal anecdotes, unique perspectives, and vary your sentence rhythm. Don’t rely on a thesaurus—inject your own voice into every sentence.
