How AI Became a Power Industry
Karen Hao traces the rise of artificial intelligence through interviews with hundreds of people and a large body of internal records and public evidence. The picture that emerges is not a clean story of scientific progress. It is a story about how a research field became a contest over money, infrastructure, labor, and political influence.
At the center sits OpenAI, but the pattern reaches far beyond one company. A small group of firms came to dominate AI because modern systems require enormous amounts of computer chips, data, electricity, water, and cash. Once progress became tied to scale, only the richest companies could compete, and they began shaping the rules, the story, and the future of the field.
This race has been presented as a mission to benefit humanity. In practice, the benefits and burdens are distributed unevenly. Wealth and control concentrate at the top, while many of the costs fall on data workers, artists, local communities, and people whose information is taken without meaningful consent.
The language around AI often makes this concentration of power seem natural or inevitable. Terms like intelligence, learning, and reasoning suggest that machines are steadily becoming minds. That framing helps companies attract funding and public awe, even when the systems are still unreliable pattern matchers that absorb human biases and frequently produce falsehoods.
A wider historical pattern runs through the industry. New technologies are often sold as universal progress while serving the interests of those who fund and own them. AI follows the same path. It promises abundance and efficiency, but it is being built through extraction: extraction of data from the internet, extraction of labor from vulnerable workers, and extraction of land, water, and energy from communities with less power to resist.
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