The AI Stock Boom Is Creating Millionaires Overnight—and Leaving Everyone Else Behind

The money isn’t the most peculiar aspect of the AI stock boom. It’s the velocity. Little things like people talking more quickly, phones being held a little closer, and lunch conversations shifting from “how’s work” to “what’s your strike price” without any preamble are all signs of it. The atmosphere has that familiar buzzy sheen in some parts of San Francisco and the Peninsula, as if the city has been turned back on.

With his badge swinging and his backpack still wrinkled from the shipping box, a young engineer exits a rideshare near a glass office tower. Ten minutes later, someone is describing a secondary tender offer in the same manner that people used to describe a vacation, inside a lobby that has a subtle scent of espresso and freshly installed carpet. Not quite a cash-out. Not just yet. However, a door opened, allowing private shares to be converted into actual funds in a bank account. There’s a feeling that something more akin to a jackpot schedule has taken the place of the previous timeline, which was to work for years and save for decades.

Two engines are operating simultaneously in the boom. Anything that appears to be AI distribution or infrastructure has been rewarded by public markets, which has caused a few names to become well-known, much like “FAANG” did. Simultaneously, private AI firms are snatching up funds in rounds so big they resemble GDP figures, inflating paper wealth that can instantly make an average-looking team into millionaires on spreadsheets. This might be the largest wealth-creation frenzy that many of us will ever experience, and it’s still unclear if it will result in enduring new industries or a hangover.

The fact that some people are becoming wealthy isn’t the only thing that makes it seem unfair. It’s the funnel’s narrowness. The boom is personal if you work for the right company, live in the right zip code, and have the right amount of equity. If not, you take in the headlines, charts, memes, and the occasional widely shared screenshot of a brokerage account as if it were theater. The disparity is not just about income; it’s also about access to the upside, and timing, geography, and networks are limiting access.

It’s difficult to ignore the geography portion. The ripple can be seen a few blocks from a venture firm’s office: a new café serving $9 coffee, a line of people in black sweatshirts comparing model benchmarks, and a real estate agent discussing “inventory” as if it were a rare mineral. This same neighborhood was experiencing the post-pandemic slump a few years ago, with empty storefronts and “for lease” signs curling at the edges. The sidewalks appear to be packed once more, and the crowd appears well-funded.

Outside of the boom zones, however, the AI rally may seem like a far-off weather system. While dealing with layoffs, hiring freezes, and managers subtly promoting “efficiency,” which entails fewer people doing more work, office workers in other cities hear about valuations and unicorn counts. Investors appear to think AI will increase productivity globally, but the timing is cruel and the checks are coming in unevenly. Wages move more slowly than costs. Always had.

A significant portion of the narrative revolves around stock options, which carry a unique form of psychological trauma. Even if they continue to eat the same desk salad and wear the same beat-up sneakers, an employee can feel broke on Monday and wealthy by Friday. To put it politely, the majority of that wealth is illiquid, or not spendable. However, it alters posture. Instead of discussing rent, they start discussing tax strategies. As the graph continues to rise, they begin to use terms like “concentration risk” and then disregard them.

Within the boom itself, the class divide is also less pronounced. Founders and early workers receive equity that counts. In order to be close to the action, later hires frequently receive lower pay and pay higher living expenses. The campuses are maintained by contractors and support personnel, such as food service, cleaning, and security personnel, who are paid more than those in the surrounding communities. It’s difficult not to notice the two streams of workers leaving the same location at dusk, each with a completely different future attached to their pay, as you watch shift changes outside a sleek building.

The logic of the market seems clear: talent should be compensated, innovation should be funded, and risk should be rewarded. Messier is the lived version. Some startups are working hard to create tools that have the potential to revolutionize software, logistics, or medicine. Others are selling a vibe, honing demos, and riding a story. It’s still unclear if public markets can accurately distinguish between the two when enthusiasm is running high, and the line between the two can be blurry in the moment.

There is folklore associated with each boom. Sock puppets and day traders were common during the dot-com era. This one has founders raising money, model releases, and GPU shortages that make their first product appear to be a side project. It can be exciting. For a small group, it can also feel like a machine that transforms attention into wealth, then asks everyone else to appreciate the results.