As AI becomes more productive, it could leave behind ordinary households who are more exposed to job loss, weaker safety nets, and higher utility costs—but it doesn’t have to be that way, according to a new memo from OpenAI.
In the 13-page report, Industrial Policy for the Intelligence Age: Ideas to Keep People First, the company warns that AI could wind up “controlled by, and benefiting only a few,” unless governments act fast to spread the gains more broadly.
Anxiety about these kinds of disruptions is already starting to crop up.
“People are already concerned about what AI will mean for their lives—whether their jobs and families will be safe, and whether data centers will disrupt their communities and raise energy prices,” the memo states.
For the housing market, that concern is not hard to imagine.
Housing is especially exposed to this shift through the link between job security and demand, the public funding that supports housing assistance and other safety-net programs, and the rising cost of essentials like energy.
OpenAI’s answer is striking: Taxes tied to automated labor, a public wealth fund that could distribute returns directly to citizens, and rules meant to keep households from subsidizing AI infrastructure.
Why households and housing could be exposed
At the core of the housing market’s exposure is the connection between job security, income, and housing demand.
“When you see a pullback in higher-income employment in a given metro, housing demand in that market tends to feel it, because those workers are disproportionately the buyer pool,” John Macke, research manager at John Burns Research and Consulting, tells Realtor.com®.
In November, Macke authored an analysis finding that high-income job losses were cooling housing demand in many major metros, with weakness concentrated in the information, professional services, and financial activities sectors.
But he’s careful not to overstate AI’s current role in the housing market.
“There is so much economic uncertainty and volatility that has nothing to do with AI,” he says, pointing to tariff policy, interest rate uncertainty, and geopolitical risk.
“It’s genuinely difficult to isolate any signal that might be coming specifically from AI disruption. What we can point to is the wave of corporate layoff announcements we’ve seen over the last several months, many of which have explicitly cited AI and automation. That suggests disruption is starting to happen. But we’re still very early in the process,” he adds.
The memo, however, sees a future where it will be easier to point directly at the technology for this type of disruption.
“As AI reshapes work and production, the composition of economic activity may shift—expanding corporate profits and capital gains while potentially reducing reliance on labor income and payroll taxes,” it states.
If that happened at scale, the housing market would feel it quickly. Job loss can make it harder to keep up with a mortgage, and widespread income shocks can also strain the safety-net programs households rely on.
We saw a version of this during the Great Recession, when state tax collections fell 8.5% in 2009 even as Medicaid enrollment rose by nearly 3.3 million people in a year.
OpenAI’s fix: Tax automation, share the upside, and shield households
But again, according to the memo, this is an avoidable future—and the company lays out ways policymakers could redirect some of that upside back toward the public.
One of its clearest proposals is to modernize the tax base by taxing automated labor. In practice, that could mean taxing a company’s use of AI or robots to replace routine work, rather than relying as heavily on wages and payroll taxes to fund core public programs.
But there’s some evidence from South Korea—the country with the highest robot density—that taxing automation comes with trade-offs. In 2023, there were more than 1,000 robots installed per 10,000 workers, according to the International Federation of Robotics. The United States, by comparison, had only 295.
In response, the country adopted a quasi-robot tax in 2017 by scaling back tax credits for automation. But a 2025 paper found that affected industries reduced robot installations by 28% compared with their Japanese counterparts. Importantly, the policy had no statistically significant effect on employment on average.
While it’s not a clear apples-to-apples comparison, it does hint at the difficulty in finding a tidy replacement for long-entrenched tax systems—a problem currently plaguing lawmakers across the country as they try to replace or reduce revenue from property taxes.
The company also calls on policymakers to “create a Public Wealth Fund that provides every citizen—including those not invested in financial markets—with a stake in AI-driven economic growth.”
Such an idea wouldn’t necessarily amount to a universal basic income—a popular idea that some progressive tech futurists like Andrew Yang have long called for. But it would more evenly share the AI gains that are now concentrated among the people who work for these companies and their stockholders.
But the memo’s most immediate proposal for households may be its call for AI data centers to invest more in the energy grids and utilities that they depend on.
“AI data centers should pay their own way on energy so that households aren’t subsidizing them,” it reads.
Realtor.com has previously reported that AI data centers are driving up electricity demand, fueling fears that the cost of expanding the grid could ultimately be passed on to homeowners through higher utility bills.
In fact, by 2029, consumers and small businesses could see their electricity bills increase 70% due to surging energy demand from AI data centers, according to a report by the Jack Kemp Foundation.
Why OpenAI says the conversation cannot wait
The company is careful to present these proposals as early and exploratory, not as a final blueprint. But OpenAI is just as clear that it doesn’t see this as a distant problem.
“Unless policy keeps pace with technological change, the institutions and safety nets needed to navigate this transition could fall behind,” the memo reads.
That urgency stands alongside a great deal of uncertainty about what AI will actually mean for the economy, labor market, and housing demand.
“It’s too early to say with confidence whether AI will be a net negative for the kinds of workers who drive housing demand, or whether productivity gains get captured in wages and end up being supportive,” says Macke.
That is the tension running through OpenAI’s memo. The full scope of the threat is not yet measurable, especially in housing. But OpenAI argues that waiting for the disruption to become obvious could leave households, workers, and the public systems they rely on trying to catch up after the fact.
