How much of the internet is AI-generated now?

A representative sample of websites from the Internet Archive (2022-2025) measured with a state-of-the-art AI text detector finds that "roughly 35% of newly published websites were classified as AI-generated or AI-assisted" by mid-2025, up from zero before ChatGPT's launch in late 2022. This is the first large-scale empirical baseline for a phenomenon previously discussed only through anecdote and speculation (the "Dead Internet Theory").

What the data shows:

• Semantic diversity correlates negatively with AI text prevalence — ideas converge as AI content grows
• Positive sentiment correlates positively with AI text prevalence — the internet gets more upbeat
• Factual accuracy shows no statistically significant change
• Stylistic diversity shows no statistically significant change

The perception gap. A user study found that the majority of US adults believe all four hypotheses (reduced semantic diversity, increased positive sentiment, decreased factual accuracy, decreased stylistic diversity). People who do not use AI or use it infrequently believe in the negative impacts more; those who hold negative views of AI believe more strongly in the hypotheses. The perception of harm exceeds the measured harm on two of four dimensions — but is validated on the other two. Public fear is neither paranoia nor prophecy; it is half right.

The semantic diversity finding is the key result. Stylistic diversity is preserved — the words vary — but semantic diversity declines. This mirrors the pattern from since Do different AI models actually produce diverse outputs?: surface variation masks idea convergence. The internet is saying the same things in different ways.

Connection to model collapse. Since Does training on AI-generated content permanently degrade model quality?, the 35% AI content baseline establishes the starting condition for recursive degradation. If future models train on web crawls that are already one-third AI-generated, the tail distribution loss accelerates. The semantic diversity decline measured here may be the early empirical signal of model collapse manifesting in the wild, not in lab experiments.

The positive sentiment bias confirms what the homogeneity research predicts: AI output defaults to agreeable, constructive, and upbeat framing. Since Does AI homogenize culture the way mass media did?, the sentiment shift represents the AI culture industry's affective signature — systematically positive, systematically inoffensive, systematically unremarkable.

The factual accuracy non-finding is surprising given hallucination concerns but may reflect selection effects: AI-generated websites that contain obvious factual errors may be less likely to persist in the archive, or factual accuracy may be domain-dependent in ways the aggregate measure misses.