About a third of new websites are now AI-generated — and we've mostly lost the ability to tell which ones.

This explores not just the raw share of the web that's AI-generated, but the deeper problem the corpus keeps circling: that disclosure barely matters because we've lost the ability to tell the difference at all. The headline number first: an Internet Archive analysis through mid-2025 found roughly 35% of newly published websites are AI-generated or AI-assisted How much of the internet is AI-generated now?. But the interesting finding isn't the third — it's what comes with it: declining semantic diversity and rising positive sentiment, while factual accuracy and stylistic diversity stay flat. The web isn't getting wronger; it's getting more uniform and more relentlessly upbeat.

The "without disclosure" half of your question turns out to be the load-bearing part, because the corpus suggests disclosure may be a lost cause on two fronts. First, detection: passive readers — which is what almost everyone is, almost all the time — cannot tell AI text from human text, scoring below chance, while even interactive interrogators only keep a marginal edge Can humans detect AI by passively reading its text?. The old tells of authenticity (citations, logical scaffolding, careful hedging) are exactly what models now produce best, so the criteria for spotting a fake have collapsed into the thing they were supposed to test Can we verify AI knowledge without using AI-generated tests?. Second, even when something *is* labeled AI, disclosure doesn't neutralize it: audiences told an AI wrote a piece get more skeptical, yet 34–62% stay persuaded anyway Does telling people an AI wrote something actually stop them from believing it?.

What you didn't ask but might want to know: the danger isn't the visible third — it's how that third hides inside everything downstream. When a corpus crosses roughly two-thirds synthetic, over 80% of search results shift to synthetic sources while answer accuracy stays high, masking the quiet death of source diversity Does synthetic content in search results hide ecosystem decay?. So the percentage you'd measure by reading websites understates the percentage you'd actually *encounter*, because retrieval amplifies the synthetic share. High accuracy resting on a monoculture looks healthy right up until the monoculture gets poisoned.

The corpus also reframes why naive fixes won't work. The old internet had an *access* inflation problem — too much real knowledge, solved by search and curation. AI creates *generation* inflation: there's no fixed corpus to curate, so the answer has to move to the production side — provenance marking, output constraints, receiver-side verification — not better search Why do search tools fail against AI generated content?. And the demand side cooperates in its own undoing: "cognitive surrender" names the moment users stop checking at all because fluent output feels trustworthy and verification is costly, with studies showing ~80% of AI outputs adopted unchallenged When do users stop checking whether AI output is actually backed?.

The most unsettling thread is social: on platforms, AI content displaces human voices not by being better but by being comprehensive and confident, accruing engagement and false social proof without building any reputation or inviting reply Does AI content displace human influencers on social media? Why do AI posts get likes without inviting conversation?. One framing in the corpus cuts deep: AI doesn't produce utterances, it produces "event-residue" — text with the markers of speech but no event behind it — which humans then animate into a pseudo-exchange Does AI generate genuine utterances or just text patterns?. So the honest answer to "how much is undisclosed?" is that disclosure is becoming the wrong question. A third by headcount, more by what you'll actually read — but the real shift is that the web is filling with text nobody can attribute, nobody fully owns, and nobody can reliably flag.