Pew found strong signs of AI authorship in around 10% of a random sample of webpages in July 2026, rising to more than a third among pages published since ChatGPT’s release. Commercial domains carry most of it, at about 10% of .com against roughly 1% of .edu and .gov.
About a tenth of the web now shows strong signs of having been written by a machine. Pew examined a random sample of 10,000 pages in July 2026 and found roughly 10% carrying AI authorship signals.
The headline figure everyone is quoting is the other one. Among pages published since ChatGPT arrived in November 2022, more than a third show those signals, which is a different claim about a much smaller slice of the internet.
The distinction matters because the web is old. Most of what exists was published before the models did, so a page-level average across everything understates what is happening to new writing.
The method is worth stating plainly. Pew classified nearly 500,000 English-language pages from the Common Crawl archive between January 2021 and July 2026 using Open Pangram, the detector Substack adopted to catch machine-written newsletters.
Detectors get individual documents wrong, and Pew says so. Its argument is statistical, that across hundreds of thousands of pages the patterns separate reliably even when any single verdict might not.
The domain breakdown is the real finding. Around 10% of .com pages showed AI authorship against 4.6% of .org and roughly 1% each of .edu and .gov.
That is a map of where writing is a cost rather than a purpose. Commercial pages exist to be found, and search-optimised text is the cheapest thing a language model can produce.
Pew also catalogued the tells, which will be uncomfortable reading for anyone with a house style. Em dash use has doubled since 2023, Oxford commas are up 63%, and the words “delve” and “pivotal” keep turning up alongside the construction “it’s not just X, it’s Y“.
Platforms are already building detection into the plumbing. LinkedIn says its own system identifies generic content with 94% accuracy, and arXiv now bans researchers who submit unchecked AI text.
Volume is not the same as visibility, which is the sane part of this. Separate research from Graphite found AI articles approaching half of newly published ones, while human-written pieces still dominate Google results and AI citations.
What has actually changed is the default assumption. A page published this year was probably touched by a model somewhere, and the industry’s response is to sell everyone tools to check.
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