Recently, a home in Hollywood Hills, Los Angeles, sold for about $30 million. Lucy Guo, a co-founder of Scale AI, which she left in 2018, was the buyer. She was not a software salesperson. She didn’t introduce a product. She just kept her stock long enough for Meta to invest $14.3 billion in the business she had previously assisted in founding. That purchase conveys a message. The AI boom is no longer theoretical, it claims.
According to MIT principal researcher Andrew McAfee, nothing quite like this has ever occurred in over a century of data. Not the boom in railroads. Not on the internet. Not even the age of smartphones. Right now, artificial intelligence is producing wealth that is concentrated more narrowly and moving more quickly than anything economists have charts for.
It’s nearly impossible to accept the numbers. According to CB Insights, there are currently 498 private AI companies worth at least $1 billion, with a total estimated value of about $2.7 trillion. One hundred of them were established after 2023. Earlier this year, Bloomberg estimated that at least 15 billionaires with a combined net worth of $38 billion had already been produced by just four of the biggest private AI companies. Since then, that number has most likely increased.
Some of these founders are remarkably young. Anysphere’s CEO, Michael Truell, is 25 years old. Only a few weeks after his company’s June valuation of $9.9 billion, it was reportedly being offered valuations closer to $18 to $20 billion. After leaving OpenAI last year, Mira Murati raised $2 billion in what is reportedly the biggest seed round in history, valuing her new business, Thinking Machines Lab, at $12 billion before most people had even heard of it. These are not fortunes that develop gradually. The speed at which they are being put together makes the dot-com era seem slow.
San Francisco has undergone an almost theatrical turnabout after a few uncomfortable years of being portrayed as a warning about urban decline. According to New World Wealth and Henley & Partners, the city now has 82 billionaires, compared to 66 in New York. Last year, more homes than ever before sold for more than $20 million there. The irony that a city that was being written off is now being acquired, mostly by the same industry that hardly existed ten years ago, is difficult to ignore.
However, the more you examine the story, the more intricate it becomes. Nobel laureate Joseph Stiglitz, who has studied capitalism’s distribution and hoarding of its profits for decades, is pessimistic about the future. The 83-year-old economist from Columbia University is witnessing AI speed up the same trends he documented throughout his career. AI enables businesses to eliminate labor from production, concentrate profits higher, and shift the costs of disruption to the workers who are least able to bear them. He has stated unequivocally that AI will exacerbate inequality in ways that are already severe and have the potential to become structural in the absence of intentional intervention.
AI could eliminate half of all entry-level white-collar jobs in one to five years, according to Anthropic CEO Dario Amodei, who is reportedly now a multibillionaire as his company pursues a $170 billion valuation. According to Mustafa Suleyman, CEO of Microsoft AI, the majority of white-collar jobs could be completely automated in 18 months. These are not outlandish predictions made by detractors. These evaluations come from the developers of the technology.
The industry hasn’t completely resolved this tension and might not want to. The loudest voices advocating for calm about the implications of AI are frequently the same individuals who are accumulating extraordinary wealth from it.
Elon Musk has discussed government-provided universal high-income checks. According to reports from Sam Altman’s OpenAI, AI can lead to more affordable products and quicker medical advancements. According to Peter Thiel, worries about AI fall somewhere between nothing and an overreaction. It is worthwhile to consider whether these assurances are genuine or merely practical, particularly when those providing them stand to benefit the most from the public’s acceptance of the current situation.
Whether policy will keep up with this change is still up in the air. Bernie Sanders has been remarkably straightforward in framing it as a fairness issue: if AI is producing previously unheard-of wealth, then who really benefits? The laborers whose work produced the models? The customers whose information fed them? Or primarily the engineers, investors, and founders who are already at the forefront of the sector? Thus far, it appears that the latter is the answer.
Genuine fortunes, genuine innovation, and genuine uncertainty are all being produced in roughly equal measure by the AI revolution. The billionaires have already arrived. The question of what their wealth means and who else gains from it is still being worked out.
