Ramaswamy's AI wealth plan misses the worker reality
Vivek Ramaswamy's Wall Street Journal column pitches a vision where workers can build wealth as AI reshapes work. The aspiration is solid; the arithmetic is where things get fuzzy.
Start with what he gets right: focusing on worker wealth, not just “jobs,” is a better lens for the AI era. Jobs can churn, titles can change, but balance sheets are what determine whether families can ride out volatility. Treating workers as potential owners rather than just variable costs is a welcome shift in tone from the usual “learn to code” sermon.
But here’s the thing: tone is not a policy.
Ownership versus odds
Ramaswamy leans on ownership as a path to prosperity. On paper, that sounds great. Ownership gives you a claim on upside; it’s the difference between watching the show and getting a cut of the box office.
Yeah, no: ownership is not an automatic equalizer. It’s a distribution mechanism, and right now it tends to distribute up the pyramid. In tech, equity and cushy employee stock plans skew toward people already plugged into certain networks, schools, and zip codes. Early employees, founders, and investors capture the lion’s share; late-stage hires and rank-and-file workers often get scraps or nothing at all.
Drop AI into that setup and you don’t get a neutral multiplier; you get compounding. Big incumbents can fold AI into existing moats—think cloud providers bundling AI tools into infrastructure—and the gains accrue to existing shareholders long before they reshape hourly wages. The AI “upside” can skip right over the people actually using these tools on the ground.
If the column implies that individuals should simply grab stock plans and plunge into entrepreneurial bets and—presto—wealth, it understates the frictions: access to startup ecosystems, basic financial literacy, risk tolerance when you’re living paycheck to paycheck, and the reality that a lot of people can’t just uproot for a new job cluster. You don’t build broad-based ownership by telling everyone to be more visionary; you do it by changing who can realistically participate.
Science fiction saw this dynamic earlier than Wall Street did. Neuromancer imagined gleaming mega-corps with outsized power; our world is less neon, more spreadsheet, but the basic structure is familiar: a relatively small cadre owns the rails, everyone else pays the tolls.
The retraining mirage
Another comforting storyline in optimistic AI commentary is retraining. I’ll be honest: retraining is necessary. But treating it as a magic eraser for labor disruption is wishful thinking.
The glossy brochure version of retraining misses a few realities. Credentials double as social signals, and a six-month course does not instantly swap you into a new professional class. New roles take time to mature. Jobs cluster in specific regions. If you’re a warehouse worker in a town whose main employer just automated, you can’t teleport to the nearest tech hub because someone on TV said “upskill.”
People need more than skills. They need job ladders with wage growth, income bridges while they transition, and some assurance that the new roles they’re training for will actually exist in their region by the time they’re done.
There’s also a mismatch between how AI actually changes work and how the retraining narrative frames it. A lot of roles will be reconfigured rather than erased. That means the more realistic path is targeted, employer-aligned, ongoing training inside companies—closer to what AT&T tried with its internal reskilling push—rather than a one-time bootcamp that spits you into a crowded market.
The fantasy that a critical mass of displaced workers will all become solo entrepreneurs or high-paid developers has the same vibe as those midcentury ads telling factory workers to become chemists: inspirational copy, thin on scaffolding.
Where markets help—and where they don’t
The likely rejoinder to all of this is familiar: open markets and entrepreneurial energy will sort it out. Given enough room, new industries will emerge, new fortunes will be made, and enough of that will trickle into the broad middle to call it a win.
Sure, but history suggests the default path is winner-take-most. Absent specific institutional choices, distribution follows power, not fairness. Early internet companies didn’t mint a broad middle class of small shareholders; they minted a narrow band of extremely rich insiders and a long tail of users whose “equity” was memes and email addresses.
There are counterexamples worth studying. Employee stock ownership plans at companies like Publix have created meaningful wealth for long-term employees. Worker cooperatives like Mondragon in Spain demonstrate that broad-based ownership can scale without smothering innovation. These models aren’t utopias, and they won’t map cleanly onto every AI firm, but they prove there’s more than one way to structure who benefits from technological growth.
What’s missing in the pep-talk version of AI capitalism is the boring scaffolding: antitrust enforcement so AI incumbents don’t lock in every margin; tax incentives that reward broad-based profit sharing instead of just buybacks; legal and financial support for employee ownership transitions when founders exit; public investment in training hubs outside the usual superstar cities so mobility isn’t a precondition for opportunity.
None of this is as exciting as telling everyone to “think like an owner.” It’s just more likely to work for people who don’t already own much.
Practicality beats platitude
Some of these ideas sound technocratic. Fine. Better technocratic than theatrical.
Ramaswamy’s focus on worker wealth is useful as a starting point; the blind spot is treating personal hustle as a substitute for systems design. You can exhort workers to buy stock while leaving the core rules of the game intact, but that’s like telling marathoners to train harder while the course still has a mile of quicksand baked into the route.
The AI era will boost productivity and corporate profits, just as his column assumes; the interesting question is whether his preferred tools can redirect even a slice of that surge into worker balance sheets without deeper rewrites of ownership and policy.