As of late 2025, the AI-driven tech cycle is still in its early years, so the long‑run structure of outcomes (many small vs. few huge companies) cannot be reliably judged.

Evidence so far is mixed and often points in the opposite direction of Chamath’s prediction:

• There are very many AI startups and small companies: one analysis estimates over 212,000 active AI companies globally, including ~62,000 AI‑related startups, with ~2,000 new AI companies funded per year from 2013–2024. (startus-insights.com)
• AI startups have attracted an enormous share of total venture capital (about $97B of $209B U.S. startup funding in 2024, nearly half of all VC dollars), and AI accounts for roughly half of new unicorns, leading to 245 AI unicorns worldwide. (entrepreneur.com) This supports the “lots of companies” side of the claim.
• However, capital is highly concentrated in a small number of very large players: in 2025, $118B of AI‑related funding went out by mid‑August, and just eight companies accounted for $73B (62%) of that total, including a $40B raise by OpenAI. (news.crunchbase.com) Valuation tables show a handful of mega‑unicorns—OpenAI (~$157B), Databricks (~$62B), Anthropic (~$60B), xAI (~$50B), CoreWeave (~$23B)—dominating the top tier. (altindex.com)
• VCs and analysts observing the AI boom describe intensifying power‑law dynamics, where a small set of AI companies is expected to capture outsized returns while many others fail. (businessinsider.com) Major research and investment notes also argue that AI’s high fixed costs (compute, data, talent, regulation) structurally favor large incumbents and a few foundation‑model platforms more than in previous tech transitions. (goldmansachs.com)

Taken together, the data show:

• Yes, many AI startups and small firms exist and are being funded.
• At the same time, funding, infrastructure, and market power are extremely concentrated in a small number of giant companies and platforms.

Chamath’s prediction was about the eventual shape of the AI era compared with the last tech cycle (mobile/cloud), which played out over a decade or more. Generative‑AI platforms only began scaling commercially around late 2022; by November 2025 we have only 2–3 years of real data, and the market is still changing rapidly (e.g., leadership shifts between OpenAI, Anthropic, Google, etc.). (globenewswire.com) That is too short a window to know whether today’s concentration persists or gives way to a broader base of smaller, sustainable companies over the full cycle.

Because the relevant “cycle” has not run its course and current evidence is compatible with either future (continued concentration or later fragmentation into many smaller winners), the prediction’s ultimate accuracy cannot yet be determined, so the result is inconclusive (too early).