{"id":463,"date":"2026-09-24T11:30:00","date_gmt":"2026-09-24T03:30:00","guid":{"rendered":"https:\/\/imtiajwrites.com\/blog\/?p=463"},"modified":"2026-09-15T09:47:29","modified_gmt":"2026-09-15T01:47:29","slug":"ai-words-to-avoid","status":"publish","type":"post","link":"https:\/\/imtiajwrites.com\/blog\/ai-words-to-avoid\/","title":{"rendered":"AI Words to Avoid: 218 Terms Ranked by Evidence (2026)"},"content":{"rendered":"\n

Every list of AI words to avoid makes the same silent mistake. It puts delve<\/em> next to leverage<\/em> next to tapestry<\/em> and tells you to cut all three, as if they were the same kind of claim. They aren’t.<\/p>\n\n\n\n

Delve<\/em> was measured. Published studies found it disproportionately frequent in specific model outputs compared with a human baseline. Tapestry<\/em> is perceived: readers say they associate it with AI writing, which is real information about how you’ll be read, but nobody measured its frequency. And leverage<\/em> is neither. It’s a word an experienced editor would question for vagueness, and the honest thing to say is that it was a problem in corporate writing twenty years before anyone typed a prompt.<\/p>\n\n\n\n

Three different claims. Three different levels of confidence. One list that pretends they’re identical, which is why running it as find-and-replace makes writing worse.<\/p>\n\n\n\n

So this reference does something the others don’t. It grades every entry by the evidence behind it, using a three-tier system I’ve come to call the Choudhury Tiers, and it tells you when to keep the word as well as when to question it. There are 218 entries: 117 words and word families, 83 phrases, and 18 structural patterns, checked through September 2026, with sources for each. The full sortable workbook is FREE to download<\/a>, with the source URL and evidence scope for every entry. The complete list is also on this page below; no email required.<\/p>\n\n\n\n

One disclosure, because I’d expect it of anyone else: I built this reference with AI research assistance, then reviewed the sources and the reasoning. The tiers, the editorial calls, and the mistakes are mine.<\/p>\n\n\n\n

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The Choudhury Tiers<\/strong><\/h2>\n\n\n\n

The Choudhury Tiers grade AI-associated vocabulary by evidence strength: Tier C for words measured as over-frequent in model output by a published study, Tier H for words readers report associating with AI, and Tier E for words an editor would question on quality grounds without claiming they mark AI authorship.<\/p>\n\n\n\n

Tier C, corpus association.<\/strong> A study compared model output against a specified human baseline and found the word disproportionately frequent. This is the strongest evidence available, and it’s still narrow: it applies to the models, prompts, and genres that study used. A word that spiked in scientific abstracts from one model in 2024 may not spike in news writing from a different model in 2026.<\/p>\n\n\n\n

Tier H, human-reader association.<\/strong> Readers, or researchers reporting readers’ explanations, or editors, have identified the word as something they associate with AI. This is a perception, not a frequency. It’s worth knowing because your readers carry those perceptions, but it isn’t a validated test of anything.<\/p>\n\n\n\n

Tier E, editorial caution.<\/strong> Worth inspecting for vagueness, inflation, clich\u00e9, or a borrowed voice. Not claimed as an AI marker. Most of the words that trigger a reader’s “this sounds like marketing” reflex live here, and many of them predate language models entirely.<\/p>\n\n\n\n

Why the tiers matter more than the words: one of the corpus studies behind Tier C found conservationist<\/em>, firsthand<\/em>, and introspective<\/em> over-represented in model output. Those are ordinary English words. They appeared on the list because a narrow research sample happened to contain no human uses of them, and a zero in a small sample is a fact about the sample, not about human writers. Any list that hands you those three as “AI words” without the tier label is teaching you to distrust perfectly good English.<\/p>\n\n\n\n

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