Why AI writing sounds like AI, and how to make it sound human

The easiest way to make AI-generated text sound more human is to break the patterns. This means varying sentence length, removing stock words like "genuinely", "roughly" and "for instance", breaking the templated structure, and stripping bold, headers and bullets nobody asked for, and replacing claims so general they could be about anyone with details only you know. Cut any warming up at the start and recapping at the end, and read it out loud. A better prompt helps a little. Running the draft through a second model that specializes in rewriting helps more, because no model can see its own habits.

How do you make AI text sound human?

Edit for the things readers notice, and put back what only you know. We've seen many people make the same mistakes when writing with AI, so it's easy to tell you how to fix them. Here they are, starting with the one that pays off most.

1. Add your own information. If you prompt "Write me an email to send to a prospect as a follow up", then that's all the AI has to go on. It will write you the average follow-up email ever sent to a prospect. Give it the prospect's name, what they said on the call, the one number they care about and what you want them to do next, and the draft has something to say. No amount of editing adds substance that was never in the prompt.
2. Remove intro and summary sentences. AI loves to warm up to the point ("I hope this email finds you well", "In an era where...") and then sum up at the end what it's already told you. Delete the first and last sentence of each section and see whether anything is missing. Usually nothing is.
3. Vary your sentence length. Humans tend to vary their sentence length a lot more than AI rewrites do. We've seen it in our data. Make some sentences really short and others really long, and feel free to start sentences with "And" or "But" if that's how you'd say it.
4. Replace common AI words. Every model has words it reaches for when it has nothing specific to say. This year (2026) it's less "delve" and more "genuinely", "honestly", "roughly", "plenty of", "essentially" and "for instance". Swap in the specific thing, or delete the word. Most sentences get stronger without it.
5. Break out of templates. You don't always need an intro, three points and a conclusion. You don't always need three points in a list. Sometimes two will do. If a section only needs two sentences, stop at two. And strip formatting you didn't ask for: in our tests, AI drafts added bold phrases, headers and bullet lists even to emails.
6. Read your content out loud. Your ear catches what your eye skims: the sentence you'd never say, the phrase from a brochure, the third "additionally". If you wouldn't say it to the reader's face, change it.
7. Have someone else look over it. This can be a colleague or a different AI model, as long as it isn't the one you used to write the draft. The reason is further down.

For more on each of these points, see our guides to signs of AI writing (the 2026 list) and words and phrases AI uses too much, with what to replace them with.

Why does AI writing sound like AI?

AI writing sounds like AI because language models are trained to pick the most likely next word, and then further tuned to give the kind of answer people rate highest. Both of those things push towards the middle of the road. You get text that is fluent, safe and very much like everything else the same model writes.

If you train a language model on the entire internet, it can write in thousands of different voices. If you then train it more by having people (or other language models) score the answers it gives and teaching it to give answers that score highly, it becomes much better at giving useful answers. But it also narrows down to the handful of defaults that reliably score well. This is called mode collapse. In plain English, the model stops using most of its range. Ask a chat model to tell you a joke a few times and you'll often get the same handful of jokes. Ask it to write an email and you'll get the same handful of sentence shapes.

No single word gives AI away. AI writing often has the same rhythm, the same transitions, the same structures and the same polite enthusiasm. One "crucial" is fine. A paragraph where every sentence is the same length, starts in the same place and lands on a neat point reads like a machine, even if every word in it is ordinary.

Here's something that sounds like AI writing: "Empower your team to streamline workflows, enhance collaboration, and drive meaningful results with our cutting-edge platform." Nothing in it is wrong, and it could describe ten thousand products. A human who knows the product would write something that couldn't apply to any other product: "Nobody needs the Monday status meeting any more, because everyone can see who's blocked." That sentence is uneven and specific.

Rhythm is one of the clearest signs. We measured the coefficient of variation of sentence length for a held-out set of 471 passages from our rewriting study. The human originals came in at 0.65, but after rewriting by OpenAI models it dropped to 0.59, and after Claude to 0.56. So the AI versions had a more uniform rhythm. We also measured the share of sentences that started with a joining word like "And", "But" or "So". In the bloggers' original passages, 12.0% of sentences started with one of those, but it fell to 9.7% after OpenAI and 5.0% after Claude. When writing from scratch, the writing is more even, though only slightly (0.50 for the human originals vs 0.47 for the drafts). One model, GPT-5.4 mini, was noticeably more even than the others (0.43). Sentences starting with "And", "But" or "So" are about as common in the AI drafts as in the human writing (3.4% vs 3.8%), so some of the 12.0% was probably a habit of the four bloggers. Those small conversational joins are part of how people sound, and the models smooth them away.

But the thing that's most different about AI writing is that it lacks specifics. It has no skin in the game, no memory of the meeting and no opinion it would defend, so it generalizes and hedges. The claims it makes could apply to any company, any product, any job candidate. That's the hardest thing to change by editing words, because nothing in the text could only have come from you. Merriam-Webster has a word for the result: "slop", its 2025 word of the year, defined as "digital content of low quality produced usually in quantity by means of artificial intelligence". If you want to know more, our guide to what AI slop is covers how that label took hold and why it now sticks to anything that reads as generic.

There's another reason it's hard to fix AI writing with the AI that wrote it, which we'll come to in a minute. It also has its own guide: why your AI can't fix its own writing.

What are the signs of AI writing in 2026?

Delve used to be a tell, but now it's not. Em dashes are a tell for some models but not for others. When asked to write from scratch, today's models use formatting much more than people do (bold, headers and lists), even in emails. When asked to polish writing, they add filler words like "genuinely", "roughly" and "for instance". And in both cases they write with a more even rhythm than people do.

We ran two studies. In the first, we compared 7,554 pairs of passages. In each pair, the first passage was written by a person and posted on a blog before ChatGPT launched (November 2022), and the second was the result of a 2026 AI model asked to polish or rewrite it. The AI models used were Claude Opus 5.5 (Anthropic), GPT-5.5 and GPT-6.1 (OpenAI), DeepSeek V4.1 Flash, GLM-5.3, gpt-oss-120b, Kimi K3, MiniMax M3 and Qwen 3.8 Max. There are about 1.2 million words on each side.

In the second study, we asked four AI models from 2026 (Claude Sonnet 5.5, GPT-5.4 mini, Gemini 3.8 Flash and GLM-5.3) to write 1,177 drafts from scratch based on notes from real pieces of writing that people had written before ChatGPT. We asked the AI to write the same kind of writing as the original human document (one of 20 kinds of writing, like emails, forum posts, news, recipes and academic abstracts), in a similar tone, point of view and length. We also built a human baseline of 53,616 documents from before ChatGPT, totaling 22.2 million words.

The results, per 1,000 words:

"Delve": it is basically absent on both sides, in both studies. "Delve" was the big tell in 2023, but it has been trained out of the models, so scanning for it now tells you almost nothing.

Formatting: the biggest tells when the AI drafts from scratch are formatting. Even though the prompt said nothing about formatting, the drafts had 10.1 bold phrases, 4.2 markdown headers and 8.9 bullet lines per 1,000 words (compared to 2.4 bullet lines in the human originals). The AI even bolded things in emails (5.8 bold phrases per 1,000 words). It bolded things the most in event pages (22.1), docs (20.6) and how-tos (19.1). We don't give a ratio for bold or headers because most of the human documents were stored as plain text, so we can't know how much bold the originals had: only about 1% of them kept any bold markup. Pangram, which compared formatted text, found that AI uses 43 times as much bold and 23 times as many headers. The drafts also used 2.5 times as many colons as the human originals (9.6 vs 3.8) and about 8 times as many emoji (0.92 vs 0.11).

Em dashes: they're a tell for some models but not others. When asked to rewrite, the AI used 4.14 em dashes per 1,000 words, compared to 2.56 for the four bloggers. (That's 1.6 times as many, but keep in mind that those four bloggers used about 3.5 times as many em dashes as the 0.73 we counted across 22 million words of all kinds of writing.) When asked to write from scratch, the AI used the em dash character 6 times as much as the human originals (4.31 vs 0.72), which points the same way as Pangram, who found it to be about 10 times as much. But people use a lot of dashes in other forms, like two hyphens ("--") or a hyphen with spaces on either side (" - "), so if we count those, the gap isn't as extreme: the human originals had 2.97 per 1,000 words while the AI drafts had 4.67. The number of em dashes varies widely between AI models in both studies, with Claude using the fewest (Claude Opus 5.5 had just 0.10 when rewriting, and Claude Sonnet 5.5 had just 0.09 when drafting from scratch) and GLM-5.3 using the most (10.75 when rewriting, 11.13 when drafting). Wikipedia's page on Signs of AI writing now lists "Overuse of em dashes (2022–September 2026)" under historical indicators. See why ChatGPT uses so many em dashes for more on that.

Words: when rewriting, among words the bloggers did use, the ones the AI models used disproportionately more in 2026 are "genuinely" (12.5 times higher, 0.58 vs 0.05), "roughly" (7.7 times), "plenty of" (7.2), "essentially" (7.1), "truly" (5.4), "honestly" (5.3), "simply" (4.7) and "rather than" (3.7). The phrase "for instance" is extremely lopsided in our rewriting data: the four bloggers almost never used it, while it appears 0.25 times per 1,000 words in the AI-rewritten passages. When writing from scratch, the list changes: "honestly" (8.3 times the human rate), "whether you're" (7.1), "roughly" (4.7), "rather than" (4.3), "genuinely" (4.2) and "here's" (3.9) lead it, and the drafts used "for instance" and "essentially" less than people did.

Word or phrase	AI vs. people, rewriting	AI vs. people, from scratch
genuinely / genuine	12.5x	4.2x
roughly	7.7x	4.7x
plenty of	7.2x	1.5x
essentially	7.1x	0.4x
truly	5.4x	1.5x
honestly	5.3x	8.3x
simply	4.7x	2.2x
rather than	3.7x	4.3x
for instance	~150x (2 uses vs. 298)	0.3x
whether you're	not measured	7.1x
here's	not measured	3.9x
em dash character (—)	1.6x	6.0x
delve	almost never used	almost never used

Some famous tells didn't show up. Words like "leverage", "tapestry", "testament", "moreover" and "furthermore" are very rare on both sides in both studies. Also, contrary to what you might think, "it's not X, it's Y" is less common in the AI rewrites (0.12 per 1,000 words) than in the texts from the four bloggers (0.17). And it's about the same in the drafts written from scratch as in the human originals overall (0.12 in both). That said, it does appear in some kinds of writing. In our drafts, the AI used it in LinkedIn posts (0 in the human originals, 0.51 in the AI drafts) and academic abstracts (0 vs 0.32). And one model, GPT-5.4 mini, used it about 2.4 times as much as people, while another, Claude Sonnet 5.5, used it rarely. (Those numbers are based on small samples, so take them as a direction, not a precise number.) Pangram found "not just X but Y" at about three times the human rate, and Wikipedia's Signs of AI writing page lists it under "negative parallelisms". See our guide to "it's not X, it's Y" for more.

Other drafting patterns. Lists of three things were 1.4 times as common in the drafts written from scratch (5.60 vs 4.00 per 1,000 words). (Pangram found them about 4 times as common.) Exclamation marks were less common in the AI drafts (3.01 for people vs 1.77 for AI), particularly in LinkedIn posts (8.3 vs 3.4) and newsletters (10.0 vs 5.4). Contractions are not a tell (12.7 for people vs 15.0 for AI).

The kind of writing matters. A tell means more in some kinds of writing than in others. An em dash character in an email is unusual for a person (0.06 per 1,000 words); in a news story it's normal (1.62).

There is some variation across models. When rewriting, Claude Opus 5.5 tends to use "plenty of", "roughly" and "genuinely" more; GLM-5.3 and MiniMax M3 tend to use "genuinely" the most; MiniMax tends to use "actually" the most of any model in the set.

See signs of AI writing in 2026 for a full checklist of tells, and how to tell if something was written by AI, without a detector for how to use these tells on someone else's text.

Can you prompt ChatGPT or Claude to sound human?

To an extent, yes. Prompts can help eliminate some of the worst writing habits and give you a better first draft, but you can't prompt away the telltale rhythm and structure of AI text, because those aren't words you can ban.

What helps

• Try to match a specific writing style. Instead of describing how you want the writing to sound ("casual", "friendly"), try pasting in a couple of paragraphs of your own writing and instructing the AI to match the sentence length and tone.
• Provide lots of information. The more you can tell the AI about what you need it to write (names, numbers, what happened and what you want), the better the output will be. Specific input is the biggest single improvement you can make.
• Be specific about what you don't want. No em dashes, no opening compliment, no summary at the end. The more specific you can be about what you don't want to see in the writing, the more likely you are to get what you want. (In November 2025, OpenAI said ChatGPT now respects "no em dashes" when you put it in your custom instructions. Sam Altman described it as ChatGPT finally doing "what it's supposed to do".)
• Limit the length of your output. Try asking for fewer than 120 words, or three short paragraphs. That cuts the padding before it's written.

Where it stops

• Ban lists turn into whack-a-mole. If you tell it not to use certain words ("delve") or punctuation (em dashes), it'll often use a different word or punctuation to do the same thing ("dig into", colons, semicolons).
• Instructing it to vary sentence length doesn't work. You can't reliably prompt an LLM to write in a naturally varying rhythm. If you instruct it to vary sentence length, it'll just write in a different, equally consistent pattern.
• Instructions fade in a long conversation. The longer you talk to an AI model, the more likely it is to drift from your instructions and revert to its default style.
• It still has nothing to say. A prompt can't give the model the meeting you were in or the opinion you hold.

In some cases, a good prompt may be enough, especially if you read over the AI's output before sending it. If you're writing a quick note or Slack message to a colleague, this may work. But for writing that goes to people who don't know you yet, or who will judge your company by it, you'll want to consider a second pass.

To learn which settings, custom instructions and prompts make your AI writing tool sound more human, check out how to make ChatGPT sound more human or how to make Claude write like a human.

Why can't your AI fix its own draft?

If you ask the model that wrote your draft to "make it sound more human", it will write the rewrite in its own characteristic way, which is to say, in the same way it wrote the original. The model can't see its defaults as defaults. To the model, they are what good writing looks like. So whatever it writes will have the same tells as before, or else new tells, if you push it to write differently.

Our data backs this up. In each pair, the input is human-written and the output is produced by a model instructed to polish the writing. Across all models we tested, the rewrites used the word "genuinely" 12.5 times as often as the human writers, "honestly" 5.3 times as often and "simply" 4.7 times as often, and they wrote with more uniform sentence length. If polishing human writing makes it read more like AI, having the same model polish AI writing won't make it read less like AI.

Worse, many models, when asked to make text "more human", overcorrect and get casual, adding "honestly", "here's the thing" or a rhetorical question. That's the model's idea of how people talk, and readers spot it just as fast.

This is the main reason we made Zavus a different model from the one that writes the drafts. It's critical that the rewriting model be trained only to write in a way that sounds human and, just as important, that it is not the same as the drafting model, and so doesn't share its blind spots. For more, including mode collapse and why a second model helps, see our guide on why AI can't humanize its own writing.

What about AI humanizers?

There's a problem with a lot of AI humanizers: they make writing worse. Many were originally made to get around AI detectors, which means they change the statistics of a piece of text by using weird synonyms and rearranging sentences. That doesn't make the writing better, and it can change the meaning of what you wrote.

In August 2026, the AI editor at Tom's Guide, Amanda Caswell, tried out a bunch of popular AI humanizers. She found that they made her writing much worse: they filled clear sentences with weird synonyms, made the rhythm choppy, and in one test replaced a 15,000-year timeline with "centuries". For writing that you're going to put your name to, that's far worse than just sounding a bit robotic.

So, when you're looking for an AI humanizer, look for the same things you would in a human editor:

• Make sure it keeps the meaning of your text. It shouldn't miss out any points that you made, and it shouldn't add new ones.
• Make sure it doesn't change any facts. Names, numbers, dates, prices and quotes should all come back exactly the same.
• Make sure it doesn't change the structure. Headings, paragraphs and the order that you make your points in should all stay the same, so that you can drop the new version in as a replacement for the old one.
• Make sure that the person you're sending it to will believe that you wrote it. If you read it out loud, would you be happy for them to receive it?
• Make sure it's convenient enough to use. If you have to copy your text out of the AI tool you're using, paste it into a website, then copy it back out again, you're not going to do it every time.

Whenever you try a new AI humanizer (even ours), try it out on a paragraph of text that has a few numbers and a name or two in it, and check that every one came back right. It's harder for a rewriter than it sounds. (That's why Zavus tells your agent to check the new version against the original before showing it to you.) For how to add a humanizer to the AI tools you're already using, see how to add a humanizer to Claude, ChatGPT, Cursor and Claude Code.

Why does it matter for business writing?

Because people are increasingly wary of AI writing. They're getting better at telling when something is AI writing, and they read it as a lack of effort on your part. Both of these things reflect badly on you and your company.

You don't have to take our word for it. A Gartner survey of 1,006 US consumers in May and June 2026 (published in September 2026) found that 65% of people think brands are creating too much AI-generated content for marketing, and 57% say that content has made them less trusting of brand messaging overall. And journalists are even more wary. In a Medianet survey of 803 journalists in January 2026, 48% of journalists said they can "almost always" tell when a pitch was written by AI.

If you send a template-style cold email, it's far more likely to get deleted. If you're pitching journalists or investors, your pitch is likely to be lumped in with all the other AI pitches they receive. And if you're posting on LinkedIn, a post full of stock phrases tells your network you didn't write it. Even if you're advertising a job vacancy, if your job ad is similar to all the other job ads, you're more likely to attract people who apply for lots of job ads.

We're not saying you shouldn't use AI at all. The vast majority of pieces of writing benefit from a first draft, and AI is the quickest way to create one. The draft just isn't the finished piece.

The stakes are highest if you're sending cold outreach, pitching journalists or investors, communicating with customers or writing a post that a large proportion of your network will see, because those readers owe you nothing. That's where one generic paragraph can cost you the reply.

For content on your site, Google's guidance on generative AI content says it will be held to the same standards as other content and that AI can be a useful way to help with topic research and add structure to a piece. But it warns that using generative AI to produce many pages without adding value for users may violate its spam policy on scaled content abuse. It also advises that all AI-generated content should be fact-checked and reviewed. Check out our guide on whether Google penalizes AI content, which covers the 2026 updates.

We also have guides for the people who send the most AI-assisted writing: sales teams, marketers, founders and recruiters.

What should you check before you send anything AI-written?

Use this checklist for everything AI-drafted you send out under your name. Most of it takes seconds.

1. Are the facts correct? LLMs can be prone to hallucination, and if you're running the content through a rewriter, the chances are it might change some facts. Double-check names, numbers, dates, prices, job titles and links.
2. Is there something unique in the piece? If anyone could send the piece to anyone, then it's probably not that good. Add something unique: it could be a small detail from a call you had, a number only you know or even an opinion.
3. Have you removed all the fluff? LLMs like to warm up before getting into the meat of the piece, and they like to recap afterwards. Remove all the "I hope this finds you well", "In today's world" and "In summary".
4. Do your sentences vary in length? One of the giveaways of LLMs is that the sentences tend to be the same length. If a run of them are, split one in half or merge two.
5. Have you removed all the common LLM words? Search your piece for "genuinely", "honestly", "roughly", "plenty of", "essentially", "for instance", "truly", "simply" and "crucial", and make sure you've removed them (or kept one if it's the only word that will do).
6. Are the em dashes earning their place? Some LLMs love using em dashes. One is fine, but if you find three in a paragraph, remove most of them.
7. Have you broken up templates? LLMs fall into the same templates: three bullet points, three adjectives, three benefits, and bold phrases or headers in an email. Break the pattern somewhere.
8. Have you shortened it? LLMs tend to be verbose, so remove any sentences that say something you've already said.
9. Have you read it out loud? If you stumble over a sentence or cringe at something, change it.
10. Would you be comfortable saying you used AI to help write it? Using AI isn't something to be ashamed of. Write the best piece you can that sounds like you. Hiding the tool was never the point.

Where does Zavus fit?

Zavus is a separate rewriting model built only to make writing sound human. When your AI rewrites its own draft, it still sounds like AI. So Zavus isn't another prompt or skill. Your agent hands the finished draft to a different model, gets the rewrite back and gives it to you.

It works inside the agents people already write with, through MCP: Claude, ChatGPT, Claude Code, Cursor, Codex, Copilot, Windsurf and Gemini CLI. Setup is one paste. Put this prompt into your agent and sign in when it asks:

Set up Zavus for me. Add the MCP server at https://api.zavus.ai/mcp and name it "zavus". I'll sign in when it asks. Once it's connected, humanize a short paragraph (Zavus needs at least 40 words) to check it works. From then on, run finished writing meant for other people, like emails to clients or customers, posts and announcements, through Zavus's humanize tool before you give it to me.

From then on, your agent runs finished writing meant for other people through Zavus's humanize tool: emails to clients and customers, posts, pitches, outreach and announcements. Your own notes and the agent's explanations to you are left alone. On the Team plan you can also call Zavus from your own software through the REST API. Step-by-step setup for each tool is in how to add a humanizer to Claude, ChatGPT, Cursor and Claude Code, and the technical details are in the Zavus docs.

Zavus changes wording and sentence structure. It keeps headings, paragraphs and the order of your ideas, so the result drops back in where the draft was. It needs at least 40 words to work with, so one-line replies are left as they are. Billing is on the words you send in.

Here are two examples. The first version in each came from an AI model, and the second is what Zavus returned.

AI draft

Hi Sarah, honestly, I just wanted to reach out and share a quick update on the project. We've made genuinely great progress this week, and the new dashboard is roughly 80% complete. There are plenty of small details left to polish, but the core features are working smoothly. For instance, the export tool now handles large files without any issues. I truly appreciate your patience as we finish things up, and I'm confident we'll have everything ready for review by Friday. Let me know if you have any questions!

After Zavus

Hi Sarah, Just wanted to give you a quick update on the project. We've made some great progress this week, and the new dashboard is about 80% done. There's a bunch of little details to take care of, but the big features are all working. We fixed the export tool so it can handle large files now. Thanks for being patient while we work on this. We should have something for you to review by Friday.

AI draft

Hi Dana,

Thank you so much for taking the time to join our demo on Tuesday — it was genuinely great to walk you through the platform. I wanted to follow up on a few key points we discussed. First, the reporting dashboard can essentially replace your current weekly spreadsheet process. Second, for instance, your team could save roughly five hours a week on reconciliation. Third, we offer plenty of flexibility on pricing for annual plans. I'd love to find a time to explore how we can tailor a solution to your needs. Would you be open to a quick call next week?

Best regards, Sam

After Zavus

Hi Dana,

It was great meeting you for a demo last Tuesday. I wanted to follow up on a couple of things. As we mentioned during the demo, our reporting dashboard can replace your weekly spreadsheet process. That could save your team about 5 hours a week on reconciliation alone. Lastly, we have some flexibility on our pricing for annual plans. I'd like to talk about how we can make this work for you. Is there a time next week that works for you to chat?

Best regards, Sam

Zavus starts with a five-day free trial of the full plan. Starter is 50,000 words a month for $20 a month, and Team is 300,000 words a month shared by unlimited teammates, with API keys, for $100 a month.

If most of what you send starts as an AI draft and ends up in front of clients, customers or your network, a separate rewriting pass is what turns that draft into something that reads like you wrote it. That's the job Zavus was built for.

Frequently asked questions

Is it OK to use AI for business writing?

Yes. Using AI to draft is fine. What readers dislike is writing that is generic, padded or wrong. Use AI for the draft, then add your specifics, check the facts and edit until it sounds like you.

Will removing em dashes make my writing sound human?

Not on its own. In our 2026 data, em dash use varies a lot by model, and Claude used far fewer than people in both our rewriting and from-scratch tests. Formatting, rhythm, stock words and generic content give AI away more than one punctuation mark.

Can people tell when an email was written by AI?

Often, yes. In Medianet's 2026 survey, 48% of journalists said they can almost always tell when a pitch was written by AI. Uniform sentences, stock words and a lack of specific detail are the usual giveaways.

Does Google penalize AI content?

Not for being AI-written. Google says AI content has to meet the same standards as any other content. Using AI to mass-produce pages that add no value for users can count as scaled content abuse under its spam policies.

Does Zavus work with ChatGPT and Claude?

Yes. Zavus connects through MCP to Claude, ChatGPT, Claude Code, Cursor, Codex, Copilot, Windsurf and Gemini CLI. You paste one setup prompt into your agent and sign in when it asks. After that, your agent runs finished writing meant for other people through Zavus before handing it to you.

Sources

1. AI writing tells in 2026: data from 7,554 rewrites and 1,177 drafts, Zavus research, November 2026
2. Wikipedia: Signs of AI writing, Wikipedia, accessed November 2026
3. Signs of AI writing, backed by data, Pangram, accessed November 2026
4. Merriam-Webster names "slop" 2025 word of the year, Gulf News, accessed November 2026
5. OpenAI says it's fixed ChatGPT's em dash problem, TechCrunch, November 2025
6. I tested popular AI humanizers, and they made my writing much worse, Tom's Guide, August 2026
7. Gartner marketing survey finds 35% of consumers rely on influencers less due to AI, Gartner, September 2026
8. Journalists embrace AI despite rising concerns and threat to jobs, report reveals, Medianet, March 2026
9. Google Search's guidance on using generative AI content, Google Search Central, accessed November 2026