The geography of the AI economy today is highly skewed, echoing the broader digital economy’s concentration in a few prosperous metros. The Bay Area “superstar” region, along with 13 “early adopter” metro areas like Boston, Seattle, and Austin, dominates AI activity, accounting for over half of AI-related jobs, patents, and investment 1. Meanwhile, scores of other cities and towns have little to no AI presence. This winner-take-most pattern, driven by clustering of talent and capital, poses a challenge: without intervention, AI could exacerbate regional inequalities. However, shifts are underway that could redistribute some of this growth. This section examines the current landscape of AI’s economic geography and identifies how strategic actions might channel more AI development into America’s smaller cities and towns.
The Metro AI Divide. As of the early 2020s, nearly all significant AI R&D companies, prominent AI startups, and top AI research universities are located in large metropolitan areas. According to Brookings, beyond the Bay Area and the early adopters, there are about 87 “potential adoption centers” – mostly mid-sized metros – that have some AI activity but at much lower levels . These include places like Pittsburgh, Omaha, and Richmond, which often host a major company or university driving local AI use. Collectively, these potential hubs produce about a quarter of U.S. AI patents and companies and ~30% of AI jobs . While significant, that output is spread thin across many locales, and each of those cities individually has only a tenuous foothold in the AI sector . Rural areas and small inner-ring suburbs, for their part, barely register in such analyses except as places where AI might be adopted in local industries (like using AI in agriculture or mining) rather than created.
The implication is clear: if left purely to market forces, a few cities will capture the lion’s share of the AI boom, just as a few captured social media or biotech. This concentration yields powerful innovation clusters but leaves other regions economically behind. It can also create vulnerabilities – for instance, housing and infrastructure strains in the boomtowns, and missed opportunities elsewhere. Recognizing this, policymakers have begun to pursue a more distributed growth model. The CHIPS and Science Act of 2022 included provisions for Regional Technology and Innovation Hubs (“Tech Hubs”) specifically to “build global economic leadership by unlocking development in new places”. In October 2023, the Economic Development Administration designated 31 Tech Hub regions across 34 states signaling a commitment to seed innovation ecosystems outside the usual suspects.
The Role of Remote Work and Migration. One of the most significant shifts since 2020 is the normalization of remote and hybrid work, especially in tech sectors. This has begun to decouple some jobs from geography. During the COVID-19 pandemic, many professionals left expensive coastal cities in favor of smaller cities or suburban/rural areas where they could work from home . Even after offices reopened, about 30% of workdays continue to be from home nationwide. As a result, population flows have favored smaller metros over large ones recently. In 2021–2023, central counties of the 12 biggest metros lost around 8% of their population (versus trend) while outer suburbs and smaller cities gained residents 2. Roughly 42% of movers from big cities relocated outside those metro areas entirely, typically to smaller cities or towns rather than other large cities.
This “donut effect” – the shift of people outward – creates an opportunity for regions that previously suffered brain drain. Talent is a critical ingredient for AI growth, and now more tech talent is geographically dispersed. A data scientist from San Francisco might be telecommuting from Boise or a cloud engineer from New York working from Greenville. Additionally, programs like Tulsa Remote (which offers $10,000 and other perks to remote workers who move to Tulsa, Oklahoma) have actively drawn skilled individuals to smaller cities. By 2024, Tulsa Remote had attracted over 3,400 remote workers, injecting an estimated $622 million in new income into the local economy 3. Each transplant not only spends locally but often spurs indirect job creation (with one study showing a 4:1 return in local economic output per dollar spent on such incentives). Importantly for AI, many remote workers are in tech occupations. When a cluster of remote tech workers forms in a smaller city, it can create a nascent tech community – seeding meetups, startups, and increasing demand for local tech infrastructure (like co-working spaces, better broadband, etc.).
Beyond “Winner-Take-Most”: Strategies for Spread. While remote work moves individual brains, building a lasting AI cluster requires local institutional capacity. That’s where the Tech Hubs program and similar state initiatives come in. By providing federal funding and designation, these hubs aim to catalyze partnerships among universities, community colleges, industry, and government in a given region. For example, a designated tech hub in the Midwest focusing on AI in manufacturing might receive grants to build an AI prototyping center, train workers in AI-driven production, and attract startups and venture capital to that specialization. Such place-based investments reflect a strategic shift: rather than fight market forces directly, leverage regional strengths (like an automotive hub in the Midwest or an agriculture region in the Plains) and infuse them with AI capabilities.
There is precedent for tech dispersal. In the mid-20th century, the U.S. deliberately spread aerospace and defense R&D across many states (partly for political reasons), giving rise to tech centers in Southern California, Seattle, St. Louis, etc. In recent years, we see smaller metros rising as tech centers: Denver–Boulder, Raleigh–Durham, Salt Lake City, even though they started with far fewer advantages than Silicon Valley. Key factors in their rise included strong research universities, quality of life that attracted talent, and often some anchor companies or federal labs. For truly small towns, the formula might involve smaller-scale anchors – for instance, a community college with a cutting-edge AI program, a niche AI lab that found success there, or a local industry adopting AI at scale, like a mining town using AI for mineral exploration, thereby attracting AI service providers to set up an office.
One notable trend is venture capital slowly extending beyond its traditional havens. As of a few years ago, 75% of U.S. venture capital still went to three states (CA, NY, MA) 4, but initiatives like Steve Case’s Rise of the Rest have highlighted startups in dozens of other cities and facilitated more funding for them. Many of these startups are leveraging AI in sectors like ag-tech (agricultural technology in places like St. Louis or Fargo), fintech (in Charlotte or Birmingham), or energy tech (in Houston, which though a large metro, historically was not a “tech” hub in the software sense). If capital flows diversify, it will reinforce a broader geography for AI development. Goldman Sachs, for instance, has established investment funds focusing on “Opportunity Zones” (distressed areas eligible for tax-advantaged investment) which include many rural and small-town locations, channeling money into projects that might involve data centers or tech parks in those zones 5.
Local Assets and Niche Leadership. For many smaller communities, the realistic path is not to become the next Silicon Valley in a broad sense, but to carve out a niche in the AI economy. That could mean specializing in a domain of AI that aligns with local strengths. A few examples: Dalton, Georgia – a town known for carpet manufacturing – could become a hub for AI in advanced manufacturing (with factories adopting robotics and AI quality control, and perhaps a small R&D outfit focusing on textile AI). Or consider Lincoln, Nebraska, surrounded by agriculture – it could focus on AI in precision farming (drones, sensors, and AI analytics to boost crop yields), with the University of Nebraska’s ag tech research and local agri-businesses forming a cluster. Already, some rural areas are seeing tech startups in agriculture, supported by land-grant universities and USDA grants.
Another asset of small towns is community cohesion and the possibility of public buy-in. When a town rallies around an economic development vision, things can move faster than in a big city with fractured interests. For instance, El Dorado, Arkansas (population ~18,000) launched a successful tech incubator and coding academy by uniting local business leaders, the municipal government, and an educational nonprofit, branding the effort as part of the town’s renaissance. Such community-led initiatives can make a place attractive for state or federal support, because they demonstrate local commitment. Moreover, smaller communities may more readily embrace innovation that brings jobs – for example, residents of rural Hermiston, Oregon, welcome data centers as a good fit (200 stable jobs without overwhelming the town) , whereas in dense Silicon Valley suburbs, residents often oppose new data centers or housing due to NIMBY concerns. This attitude advantage can be part of a small town’s pitch: “We are open for business and can get projects done.”
Risks and Realism. Spreading the AI economy is not without pitfalls. A major concern is the “skills gap” – many smaller communities lack workers with advanced degrees or coding expertise. If an AI company locates in a small town but can’t find talent locally, it will import workers, which can create cultural frictions and still leave locals unemployed. To avoid this, workforce development (discussed in depth later) must go hand in hand with infrastructure investment. Another risk is that some places pour resources into chasing “the next Silicon Valley” when fundamentals (like location or connectivity) might be too unfavorable – leading to boondoggles like empty tech parks. Strategic assessment is needed: some towns will emerge as winners in attracting AI activities, others may better focus on related areas (like supplying components, or providing remote services into the AI economy).
Brookings’ analysis cautions that building a significant AI cluster is challenging and few places might truly become self-sustaining hubs. But it also notes that all regions should at least consider how to leverage AI for their economic vitality—whether through adoption in existing industries or niche innovation. The goal is not to have an “AI lab in every county,” but to avoid a scenario where entire swathes of the country derive no benefit from a technology that will reshape the economy. By aligning national initiatives with local leadership, the U.S. can mitigate winner-take-most dynamics. In essence, economic geography is policy-sensitive: thoughtful intervention can bend the arc from extreme concentration toward a more distributed pattern.
In conclusion, the current geography of AI favors large, established tech centers—but the map is not fixed. Remote work, targeted investments, and local ingenuity are already expanding the boundaries of where innovation happens. The small town’s future need not be one of perennial catch-up. With infrastructure deployment and intentional talent development, communities once considered economically peripheral can become active nodes in the AI economy. This shift won’t happen automatically. It requires a workforce strategy that prepares local residents not only to fill jobs—but to shape, manage, and co-own the future of AI. The next section explores what that looks like: an AI working class built from the ground up.
- Brookings Institution. The Geography of AI: Who Will Benefit from the Artificial Intelligence Revolution? 2021. https://www.brookings.edu/research/geography-of-ai
- Economic Innovation Group. The New Map of Economic Dynamism: Migration Trends Post-COVID. 2023. https://eig.org/economic-dynamism-map
- Tulsa Remote. 2024 Impact Report. Tulsa Remote, 2024. https://tulsaremote.com/impact
- National Venture Capital Association. NVCA Yearbook 2023. 2023. https://nvca.org/research/yearbook
- Goldman Sachs. Opportunity Zones: Unlocking Capital for Economic Development. Goldman Sachs Asset Management, 2023. https://www.goldmansachs.com/citizenship/urban-investments/opportunity-zones/