Evidence so far is mixed and timing-dependent.

What the prediction claimed
Chamath argued that as LLM-based AI is widely deployed in search and adjacent products, it will:

1. Be strongly deflationary.
2. Drive aggregate industry revenues and profit pools down, including Google’s, unless incumbents cannibalize their existing models.

What has actually happened (through late 2025)

1. Google’s search and ad revenues are still rising in absolute terms.

   • Alphabet’s Google Search & Other revenue grew from about $162.5B in 2022 to $175.0B in 2023 and $198.1B in 2024. Total Google advertising revenue rose from $237.9B in 2023 to $264.6B in 2024, and total company revenue from $307.4B to $350.0B. (reportify.ai)
   • In 2025, Alphabet has reported multiple record quarters, including over $100B in quarterly revenue and roughly 16% year‑over‑year growth, with nearly $35B in quarterly profit. (apnews.com)
   • Google’s search revenue specifically was reported up ~10% year‑over‑year in 2025, not down. (mediaweek.com.au)
     → This contradicts a near‑term drop in Google’s revenue/profit pool.

2. The broader search and digital ad markets are also still growing.

   • Global search advertising revenue reached about $168.9B in 2024 and is forecast to keep growing strongly. (grandviewresearch.com)
   • Overall digital ad spending was about $614B in 2022 and ~$600–740B range in 2024, with projections for continued growth through the late 2020s. (theseoproject.org)
     → At the aggregate market level, revenues are not yet falling; they’re growing, albeit with some deceleration.

3. There is clear deflationary pressure and profit compression for parts of the ecosystem.

   • Google’s AI Overviews/AI search features are measurably reducing click‑through rates and traffic to publishers, with reports of 18–64% drops in organic visits and large CTR declines where AI answers appear. (searchinfluence.com)
   • Multiple reports document steep traffic and revenue declines at news and content sites (e.g., 30–40%+ traffic drops, rising zero‑click searches, and sharp falls in affiliate revenue), attributed substantially to AI summaries and Overviews. (ainvest.com)
   • Analysts also note Google’s ad revenue growth is slowing and that AI features are harder to monetize, while infrastructure capex for AI is surging, pressuring margins. (searchengineland.com)
     → This supports the directional claim that AI in search is deflationary for many incumbents and compresses parts of the profit pool.

4. Incumbent self‑cannibalization is happening, which muddies the counterfactual.

   • Google has, in effect, done what Chamath advised: aggressively integrating Gemini, AI Overviews, and an AI “mode” directly into core search, then adding ads into those AI experiences. (techcrunch.com)
   • Because Google did choose to partially cannibalize its old SERP model, we can’t directly observe the alternative world where it refused to do so and then lost revenue to competitors, as his conditional prediction envisioned.

5. Timing: “as AI becomes widely deployed” is not clearly satisfied yet.

   • LLM‑driven search is still in early deployment: AI Overviews appear on roughly 30–40% of searches, AI “modes” have ~100M MAUs in a few markets, and AI‑driven search ads are only about $1B in U.S. spend in 2025, projected to grow sharply by 2029. (websiteplanet.com)
   • We’re mid‑transition rather than in a mature, fully AI‑dominated search landscape, so his long‑run claim about aggregate revenue and profit shrinkage may simply not have had time to play out.

Why the verdict is “inconclusive” rather than clearly right or wrong

• Against “right”: So far, the aggregate revenue and profit pools for search/digital ads and for Google itself have grown, not shrunk, which contradicts the narrow reading of his claim if judged strictly on 2023–2025 data. (alphaminr.com)
• Against “wrong”: His structural thesis—AI search as a deflationary force that erodes parts of the existing web/media profit pool and pressures margins—is strongly supported by the observed collapse in traffic and revenue for many publishers and the mounting difficulty of monetizing AI search. (ainvest.com)
• Too early: Because LLM‑based search is only partially deployed and AI ad formats are nascent, it’s plausible that aggregate revenues could flatten or fall later this decade, but current data can’t confirm or rule that out.

Given these factors, the fairest assessment as of November 30, 2025 is that Chamath’s prediction is directionally supported in terms of deflationary pressure and ecosystem damage, but its strong quantitative claim about aggregate revenues and profit pools going down has not yet materialized. Therefore the outcome is best labeled “inconclusive (too early)” rather than definitively right or wrong.