AI and the NEW New Geography of Jobs
In part two of our AI series, Julius Probst, PhD explores its potential impact on where jobseekers work and live, drawing connections to earlier tech booms.
Photo Credit: NASA
In his influential 2012 book The New Geography of Jobs, economist Enrico Moretti argued that America’s economic future is shaped by a growing divide between superstar cities — think San Francisco, Boston, Seattle — and the rest of the country.
These “brain hubs” have attracted a large pool of talent, capital, and high-paying jobs since the ‘90s. Meanwhile, less-educated, blue-collar regions stagnated in an economy increasingly driven by knowledge work and tech.
But what if that dynamic is about to reverse?
While our last AI piece focused on the AI investment boom, we may also be witnessing the dawn of a new, new geography of jobs — one where the white-collar metros that once thrived on intellectual labor become more exposed. In contrast, some blue-collar intensive regional labor markets may prove to be more resilient in an age where automation targets desktop jobs instead of manual work.
The old geography of jobs based on manufacturing
Before the knowledge economy took over, America’s economy was built on factories. After World War II, some of the best jobs in the country weren’t behind a computer screen but on assembly lines in booming Rust Belt cities.
In Detroit, auto plants churned out millions of cars a year, powering the rise of the middle class.
Pittsburgh was known as “Steel City,” home to massive mills that supplied the raw materials for everything from skyscrapers to battleships.
Cleveland and Buffalo were key players in metalworking, shipbuilding, heavy machinery, and chemical production — mid-sized cities that punched well above their weight in industrial output
What made these cities special wasn’t just their industrial output but the quality of their jobs. You could work in a factory and still own a home, raise a family and enjoy a secure retirement. These were often union jobs with solid pay, benefits, and job security. College wasn’t a requirement. This was the old geography of jobs, centred around the Rust Belt.
But after a period of rising productivity and global competition — coinciding with China becoming the world’s industrial powerhouse — American manufacturing employment started its economic decline. It began slowly before accelerating in the 1980s.
The New Geography of Jobs based on tech
As America’s industrial jobs were automated, a new economy was built around innovation and knowledge work. Instead of factories, tech companies, pharmaceuticals, finance, and research universities became the drivers of growth. These new jobs didn’t spread evenly across the country but clustered tightly in a handful of large, high-skill metro areas on the coasts.
San Francisco, Seattle, Boston, New York, San Jose, and Washington, D.C. became magnets for talent and capital. They offered dense networks of startups, top-tier universities, venture funding, and high-paying white-collar jobs. Software engineers in Palo Alto, biotech researchers in Cambridge, bankers and quants in Manhattan: the new knowledge workers, many of whom were immigrants.
This shift is what Moretti called the new geography of jobs. In a knowledge-driven economy, jobs and innovation tend to cluster, creating a positive feedback loop between talent concentration and firm location.
Over time, these superstar cities surged ahead not only in job creation but also in wages, productivity, and wealth, leaving the top 1% of households with around 18% of total income.
But there was a downside as the rest of the country started to stagnate. Even within these booming metros, inequality surged.
Wealth accumulated at the top, particularly in tech and finance, while many others faced stagnant wages paired with rising living costs. The influx of high-paying jobs drove up housing prices, pricing out working- and middle-class residents.
Service workers — waiters, baristas, delivery drivers — were essential to the ecosystem but couldn’t afford to live near their workplaces.
So, while a handful of cities prospered, the economic divide between places and people grew wider. And unlike the old factory towns, the benefits of the new economy were less broadly shared as many service workers did not benefit from the increase in prosperity in the superstar cities.
AI and the NEW New Geography of Jobs
With the rise of AI, we may be on the cusp of yet another major shift that you might call the new, new geography of jobs — and this time, the disruption is targeting some of the very cities that flourished in the last round.
The coastal finance and tech hubs are more exposed to AI-driven automation. That’s because AI doesn’t automate repetitive blue-collar work but rather white-collar tasks in law, marketing, software development, design, and finance. Many of the very knowledge workers who once defined the new economy may now find themselves in the crosshairs of generative AI.
At the same time, these cities are grappling with a growing unaffordability crisis. For many, the dream of living in a successful metro area has turned into a financial burden. If the core draw of a superstar city — proximity to high-value, in-person work — diminishes for some workers in an AI-driven, remote-friendly world, then what’s left to justify high living costs?
This creates an opening for America’s second-tier cities: places like Austin, Raleigh, Nashville, Columbus, Phoenix, and Boise.
These places offer more affordable living, improving infrastructure, and a growing tech-savvy workforce. If AI continues to decentralize knowledge work and level the playing field, it’s possible we’ll see a broader distribution of opportunity and a revival of these once-overlooked metros, especially with remote and hybrid work being much more prevalent than a few years ago.
And rural America is benefiting from another trend entirely: the rapid build-up of large data centres and related infrastructure — power stations, electricity grids — fuelling the AI economy. Remote areas in states like Virginia, Texas, Ohio and Arizona are experiencing local growth booms as investment spending ramps up.
What does this mean for recruiters?
So will AI flatten the map, or reinforce it? That will be the big question shaping the new, new geography of jobs in the coming decade. The early signals are mixed. The big coastal hubs continue to enjoy many advantages — like thick labor markets, financial and business networks, existing infrastructure — that other cities do not.
Nevertheless, we are seeing signs that AI is already affecting the geographic distribution of jobs. This time, second-tier cities and rural America might participate in the growth boom rather than lose out. A more diversified economy, with gains spread more evenly across the country, would be a welcome change. But it will also bring along new challenges. Companies will not necessarily be able to find all the workers they require in the areas where the work needs to be done.
Our next piece digs into the economics of these local labor market booms — and what they mean for hiring costs and recruitment strategy in the places where the AI economy is being built.