Breitbart Business Digest: The Blue-Collar Boom Inside Anthropic’s AI Model

Demand for Blue-Collar Work Jumps

Artificial Intelligence’s Blue-Collar Boom

What if the future of AI’s impact on the economy is not a jobs apocalypse but a blue-collar renaissance?

Anthropic, the company behind Claude, this week released a paper examining what our economic future might look like with AI. An economics team at Anthropic modeled three possible economic futures through 2030. They depend on how capable AI becomes, how widely businesses adopt it, and how easily workers adjust. The authors attach no probabilities to these scenarios, and they shouldn’t be taken as mutually exclusive. What happens could well fall somewhere in between.

In the modest scenario, GDP is 1.6 percent above its no-AI path by 2030, annual growth reaches 2.4 percent, and the job market barely changes. The extreme scenario produces an economy 32.4 percent larger than the no-AI baseline, growing at 15.4 percent annually, but with overall unemployment at 11.9 percent. AI gets much more work done while many displaced people struggle to find another job.

The substantial scenario—the middle ground between the nothing much happens modest scenario and the science fiction-like extreme scenario—deserves a closer look. It describes a powerful productivity and investment boom with plenty of work left for human beings.

By 2030, the substantial scenario puts GDP 8.3 percent above its path without AI. Annual growth reaches 5.4 percent, compared with two percent in the baseline. The capital stock is 13.8 percent larger. That means more productive equipment and other assets available to businesses.

In the Anthropic model, jobs are treated as a collection of tasks. As AI is adopted, it takes over some of those tasks and helps people perform others. AI also allows new tasks to appear—perhaps ones we have never before considered. In Anthropic’s substantial adoption scenario, AI could handle half of knowledge work by 2030, but most tasks still happen without it.

Let’s look at what happens when a company is considering whether to expand a factory. AI could make engineering, scheduling, and administrative work cheaper. That, in turn, can transform what would have been a marginal project into a profitable one. As a result, the company decides to go ahead with the investment. This creates additional demand for labor. After all, someone must pour the concrete, install the equipment, and keep the machinery running. Savings in the back office become opportunities on the shop floor.

Higher returns encourage additional investment, which makes workers more productive. That creates more work for the building trades and the operators of the factory’s machines. Demand for skilled and unskilled manual labor expands even if those workers never touch AI directly.

In the substantial scenario, real wages in occupations outside knowledge work are 5.9 percent above their no-AI path. This broad category includes service workers and blue-collar workers.

Knowledge workers’ wages, however, are 0.3 percent below their projected path. Employment in knowledge work falls 3.9 percent from mid-2026, largely because so many of their tasks are now being done by AI. Overall unemployment reaches 4.6 percent, against a 3.8 percent baseline. While that’s a substantial increase in unemployment—and if it happened quickly enough, it would set off Sahm-rule-style recession signals—it would still be quite low by historical standards.

The model also assumes wages adjust slowly, which is realistic. Employers have good reasons to avoid pay cuts that damage morale or drive away valued employees. Employees, of course, hate getting paid less for the same work. This is one of the standard reasons why people lose their jobs in downturns rather than employers keeping the same workers on for less pay. The adjustment to lower demand for a certain type of work, in other words, tends to happen through layoffs.

The result is a rise in unemployment. Even if he wanted to, a displaced accountant cannot become an electrician by changing his LinkedIn profile. Workers need to adjust their own expectations about what field they’ll work in and often face retraining costs. Unlike, say, the pandemic lockdowns or a recession induced through monetary tightness, many of the jobs AI displaces are not just going away for a while. They’re likely to be gone forever.

Workers Have Brokerage Accounts, Too

But before white-collar knowledge workers panic, there’s also an upside. Total capital income is 18.9 percent above the no-AI baseline in 2030. Machines perform more tasks, increasing the share going to capital. Before translating that into a tale of impoverished workers and triumphant capitalists, remember that these categories overlap. Workers—especially knowledge workers—are also capital owners, typically in the form of retirement accounts and stock portfolios. Thanks to the Trump Accounts, many young people will become capital owners at a very young age.

The Federal Reserve’s 2022 Survey of Consumer Finances found that 78 percent of households between the 50th and 90th income percentiles owned stocks, directly or indirectly. Among the top tenth, ownership reached 95 percent. That means many of the professionals whose jobs are exposed to AI already have a financial interest in the businesses that are likely to benefit from it.

Here we can extend Anthropic’s analysis. Stronger profits can support investment income and share values, cushioning weaker earnings for professional households. A larger retirement account can also reduce how much a family needs to save from each paycheck. For workers whose wages fall only slightly below their previous trajectory, that offset could be decisive.

The paper does not forecast stock prices or calculate these household offsets. That’s far beyond its mandate. But by any reasonable estimate, investment gains would likely cushion a significant part of the blow of job losses and transition costs for many, many established professionals, although young workers with little invested would remain more exposed.

Of course, while all these layoffs are happening, the Federal Reserve is unlikely to simply be a passive observer. If productive capacity expands faster than spending, unemployment rises, and inflation weakens, the Fed could ease the stance of monetary policy to support demand. Even by standard central bank models, the Fed should also recognize that faster productivity permits faster growth without necessarily creating inflation.

Over the longer run, that does not necessarily guarantee lower interest rates. A vigorous investment boom can increase demand for financing and raise the rate consistent with stable inflation. The Fed must judge which forces dominate. It cannot retrain an accountant, but it can help prevent weak spending from adding another layer of unemployment.

And the displacement of white collar workers may be milder than Anthropic imagines. Anthropic’s model already allows rising demand and new tasks to create work for people, but our economy may prove more resourceful than its assumptions suggest. Our economy’s propensity to utilize the resources available rather than let them waste is evident throughout our history. The blue-collar workers with rising incomes will want financial advice, legal counsel, real estate agents, psychologists, and other white-collar services. As those services become cheaper, more households and businesses will be able to afford them, expanding the market even as AI takes over some of the work.

We’re also likely to discover new occupations in which human expertise remains valuable, including some we would have trouble imagining today. How much of the displacement this will absorb is uncertain, but there are good reasons to expect businesses and workers to find opportunities that a model cannot fully anticipate. Nature abhors a vacuum; and economies abhor unused potential, especially human potential.

Immigration Becomes Obsolete

The economic changes envisioned by Anthropic have important implications for immigration policy. Better technology and more capital allow a slowly growing workforce to produce substantially more. That means that even with an aging population and a slow-growing workforce, we do not need supplementation from foreign workers to grow.

What’s more, mass immigration could do serious damage. The wage gains for non-cognitive workers in the substantial adoption scenario partly reflect their growing scarcity amid rising demand. Large inflows of competing workers could dilute that scarcity value and blunt their wage gains. Protecting those gains gives us a reason to restrain immigration even where hiring is strong.

Similarly, the familiar plea for more “skilled” immigration crumbles in the substantial adoption scenario. For the most part, so-called “skilled” immigrants are cognitive workers. Computer-related occupations accounted for 64 percent of approved H-1B petition beneficiaries in fiscal 2024. With AI doing many of the tasks now performed by cognitive workers, adding skilled immigrants to the workforce will only exacerbate the downturn these workers face.

Immigration, skilled and unskilled, is likely to become largely obsolete as an economic matter.

For blue-collar Americans, the economic future sketched out by Anthropic is very appealing: more equipment to work with, more demand for their skills, and better pay. For white-collar Americans with savings, new jobs are likely to arise, and capital income is likely to substitute for diminished labor income.

Of course, some cynicism is probably warranted. The models were concocted by Anthropic, which has an obvious financial interest in pushing a positive story about AI’s effects on the economy. But the substantive scenario is plausible on its face. And, frankly, we like it a lot better than when the AI guys were insisting no one would ever work again even if we somehow survived an AI attempt to extinguish human life.