Workers First: Rethinking AI Wealth Beyond Promises

If Vivek Ramaswamy's headline is inviting workers to “build wealth in the AI era,” here’s the thing: the headline is doing almost all the heavy lifting. The Wall Street Journal opinion piece, at least from the excerpt available, gestures at a big question and doesn’t quite show its work. I actually agree with the basic impulse you can infer from that title — making sure ordinary workers capture gains from automation matters. Anyone arguing that the spoils of powerful technology should be reserved for a tiny circle of shareholders and executives is not exactly defending common sense.

The part that resonates is the word “wealth,” not “wages.” Ownership changes incentives; it changes outcomes. Wage growth and asset-building are not the same thing. You can be paid a decent hourly rate and still watch the real wealth accrue to whoever owns the machines, data, and IP that amplify your productivity. History’s industrial experiments with mutuals and co-ops weren’t charity projects; they were attempts to hack bargaining power by changing who owns the means of production, not just who knows how to operate them. That’s the upgrade people actually want.

But if the argument ends up being, “train harder, hustle smarter, start a company,” then yeah, no — that’s a thin playbook for mass economic inclusion. Not everyone can transform retraining into entrepreneurship. Not every job displaced by automation reappears as a shiny new role waiting to be filled after a single reskilling course. I saw autonomous kiosks at CES last year that were slick as sin — you could order a latte without ever seeing a cashier. Cute demo. Not a universal social contract. And certainly not a serious answer to, “Who owns the upside when half the value chain is software?”

Ramaswamy has been a prominent voice in public debates; his attention to workers’ prospects is welcome. But when the story centers too heavily on skills, it quietly shifts the burden onto individuals while leaving market structures largely untouched. Employers are the ones positioned to capture productivity gains. Platforms set the tolls. Capital pools in familiar places. Those mechanisms shape outcomes more than whether a worker knows this year’s hot AI framework.

So if the article is going to argue that workers will thrive by increasing human capital, that argument also has to wrestle with corporate governance and ownership. Employee stock options and profit-sharing sound like bridges between labor and capital, and sometimes they are. But ask anyone who’s watched their options disappear in a down-round or expire after a layoff — vesting schedules, dilution, lack of secondary markets, and the timing of exits turn “ownership” into a lottery ticket. These are not footnotes. They’re the wiring diagrams that decide whether an equity story ever becomes a bank account balance.

Look at a company like Publix, which is structured as an employee-owned grocery chain. It hasn’t turned into a utopia, but it’s a real-world test of how different ownership models reshape behavior. On the tech side, plenty of unicorns dangle equity as a lifestyle accessory while staying private for as long as possible; workers end up long on paper wealth and short on rent money. The AI boom is already running this script: engineers and early hires at model labs get equity in entities whose long-term trajectory is anyone’s guess, while contractors labeling data fight for basic benefits. Same “AI era,” wildly different relationship to ownership.

There are mechanisms that could share AI gains more broadly: worker cooperatives, broad-based equity grants, portable benefits tied to a worker’s own “stack” of skills, and tax incentives that tilt the playing field toward labor-friendly ownership structures. You can even go weirder: data trusts where communities negotiate how their data trains models, or sector-wide funds that hold AI equity and pay out to workers the way some regions handle natural resources. None of this is free-market fairy dust. These are explicit choices — by lawmakers, boards, and investors — about who gets to stand closest to the money printer when automation hits scale.

Cue the pushback: markets and entrepreneurship create the most wealth, and heavy-handed policy will smother innovation. Sure, but that’s only half the story. Markets are great discovery engines; they are not moral systems. They’ll happily concentrate returns wherever the rules allow. You can be intensely pro-entrepreneurship and still insist on guardrails that nudge firms toward broader sharing of upside. Those aren’t contradictions. They’re complementary design choices. Smart policy doesn’t tell startups which product to build; it tells them which outcomes are non-negotiable if they want the privilege of limited liability and access to public infrastructure.

Here’s where Ramaswamy’s usual lenses — individual agency and market solutions — do some real work, and also where they hit their limits. Emphasizing agency helps prevent a drift into fatalism; people should absolutely be learning, experimenting, and taking calculated risks in an AI-rich economy. But if that story underplays collective bargaining, defaults in corporate law, and the power of capital allocators, it turns “wealth-building” into a self-help genre. You can’t bootstrap your way out of securities rules that lock up your equity or board decisions that time layoffs right before major liquidity events. If your slice of the pie can’t be sold, it’s not wealth. It’s a screensaver.

There’s also a harder question lurking underneath the headline: what counts as “AI wealth” in the first place? Is it stock in the model labs, equity in the application-layer startups, or the compounding productivity gains inside legacy firms that quietly deploy AI to cut labor costs? A warehouse worker whose job is optimized (or eliminated) by AI doesn’t get to pick which layer of the stack they participate in. That allocation is made for them, usually in a boardroom, sometimes with a consulting slide deck that cost more than their annual salary.

I like the idea of citizens owning a real slice of the machinery that amplifies their labor. I also like science fiction that reminds me not to worship the machinery or pretend it hands out justice by default. We can aim for both — ambitious markets and deliberate institutions — if we’re honest about who currently owns what.

My bet: the phrase “build wealth in the AI era” will age well only in places where the fine print on ownership shifts, not just the syllabus on skills.