America’s new no-employee small business owners start hot in AI era

It takes hundreds of billions of dollars for the tech giants to scale artificial intelligence, but it takes just a few AI tools for the smallest companies in the U.S. economy to get up and running with a cost-competitive business model. 

Alex Willen expects the 12 e-commerce brands he operates with no employees to generate between $2.5 million and $3 million this year. Kristin Ginn left Microsoft in March and started trnsfrmAItn, an AI-adoption consultancy. Seven months later, she has roughly $250,000 in business received or contracted through year-end with no employees or regular contractors. 

“The biggest misconception is that it’s just about individual productivity; it’s actually about leveraging AI to perform tasks that previously required a whole team,” said Stanford economist Erik Brynjolfsson.  

Early research on the impact of AI within the solopreneur business world bears watching. 

According to Liya Palagashvili, a labor economist and director of the Labor Policy Project at George Mason University’s Mercatus Center, new business formation is rising in direct correlation to applications unlikely to become employer firms.

In industries highly exposed to AI, business applications without early signs of hiring rose 26.8% from the first quarter of 2024 through the first quarter of 2026, from roughly 222,000 to 281,000 per quarter. 

Over the same period, applications in those industries with stronger indications of eventually becoming employer businesses fell 6.4%. In construction and wholesale trade, which Palagashvili used as a comparison group, non-employer-type applications declined 0.4%. 

“What AI is doing is giving those capabilities directly into the hands of the individual,” she said.

Palagashvili cautioned that the findings are preliminary and descriptive and do not establish that AI caused the increase. The Census-based measure identifies applications without indicators associated with near-term payroll or hiring plans; it does not show that those businesses ultimately remained one-person firms or never hired employees.

But Willen shows what the economics can look like. 

Anthropic’s Claude helps with bookkeeping, customer service, advertising, and inventory across his businesses, while OpenAI image tools perform work that once went to photographers and designers. 

Without AI, Willen said, “I’d probably need one other full-time person, plus I’d need to use contractors for photography, design, bookkeeping, and ad management.” 

A traditional product photography shoot could cost $2,000 to $5,000, and a designer $300 to $1,000 for new listing images, he said. 

When AI directly eliminates one of those expenses, Willen said, “that money just goes into my pocket.” 

AI has also allowed him to pursue revenue channels he would not have previously considered. After acquiring Lone Trail, a hunting-gear brand selling binocular harnesses, packs, and other outdoor accessories, Willen said its Shopify site accounted for roughly 1% of sales. Rather than shut down the channel, he used ChatGPT and Claude to rebuild the site and AI to help run Meta advertising. In a recent 30-day period, he said, Shopify accounted for roughly 30% of Lone Trail’s revenue. 

“That’s going to end up being at least six figures of annual revenue that would not exist without AI,” Willen said. 

Ginn’s business shows how quickly a new entrant can reach meaningful revenue without first building an organization around it. She uses AI to help with proposals, pricing, strategy, and other work and is exploring an AI agent to perform part of a labor-intensive client process. 

A survey conducted by accounting and invoicing software company FreshBooks identified similar behavior more broadly. Seventy-nine percent of solopreneurs said they had tried AI before hiring someone for a task they could not perform themselves (the same figure was 86% among when including microbusiness owners). AI allows them to “look much bigger than they are,” FreshBooks CEO Shaheen Javadizadeh said.

But among existing small businesses, the available data tells another story. Gusto, a payroll and HR software company that serves small businesses, tracked businesses after they adopted AI and found their headcount was about 7% higher after a year than a comparable businesses that knew about AI but had not adopted it. Among firms with fewer than 10 employees, AI adopters grew headcount about 10% more than comparable non-adopters.

Willen’s experience also highlights a tradeoff in the new business model: operating with fewer people does not eliminate reliance on larger technology platforms. Roughly 80% of its overall revenue still comes through Amazon, and he uses Meta and Shopify to expand direct sales. Ginn has no staff, but LinkedIn has been one of the biggest drivers of customers to her consultancy, she said. 

Brynjolfsson said the proliferation of smaller producers can actually increase the value of the platforms that connect them with the buyers. 

“There’s this long tail of products, but at the same time, big platforms like Amazon are more powerful than ever because they aggregate all of these and they bring them together,” Brynjolfsson said. 

But the relationship is not as simple as labor savings flowing directly to Big Tech. Willen said some of the money he saves becomes profit, while Ginn spends less than $60 a month on paid AI tools.  

AI can make it economical for more small producers to exist. And as core business production becomes cheaper, small businesses place greater focus on customer acquisition and distribution, Brynjolfsson said. 

Brynjolfsson believes that while solopreneurs will thrive, use of AI will at the same time lead to the creation of even larger firms, on average, than exist today. 

In a September research report titled “AI’s Use of Knowledge in Society,” Brynjolfsson and Zoë Hitzig, a researcher at the Anthropic Institute who studies the social and economic impacts of AI, argue that as AI codifies knowledge previously scattered among workers and enables more information to be aggregated and acted upon centrally, firms will grow larger on average, while industry concentration increases and local managerial autonomy declines. The researchers say early evidence is largely consistent with those patterns.  

That’s bad news for medium-sized companies. Brynjolfsson predicts AI could contribute to a “hollowing out” of midsize firms — very small teams capable of doing more at one end and giant organizations exploiting AI and scale at the other. 

“The fat in the middle — the layers of management focused on internal coordination — will likely be significantly reduced,” he said. 

Adam Branch has experienced a version of that shift from inside two very different technology companies. 

Before founding rhino.ai, an enterprise software company that uses AI to modernize legacy systems, Branch built Incentive Technology Group, a traditional technology services company that grew to roughly 500 employees. Under that model, winning more work meant hiring more people, he said. 

“With rhino.ai, we’re building AI software to do more of the work those teams used to do,” said Branch. 

Rhino.ai has roughly 50 employees. Branch estimates comparable modernization work can now be performed with three to four times the productivity per employee. 

His team estimates labor represented roughly 85% of operating spending at ITG, and technology about 5%. At rhino.ai, Branch puts labor at roughly 40%, while technology, including cloud, software, and AI models, represents about 25%. 

AWS sees a similar loosening of the relationship between revenue and headcount among AI-native startups. Its Engines of Growth research, an independent global study of 3,413 startup founders and senior leaders across 20 countries, found those companies grew revenue an average 156% annually versus 65% for startups overall, while more than half generated over $400,000 in revenue per employee. The report focused on companies under five years old that use AI in its most advanced forms. 

“Growth used to be tied directly to how many people you could hire,” said Ruba Borno, vice president of AWS Specialists and Partners. “Now founders can scale with technology, not just headcount.” 

Brynjolfsson does not see the result as simply Big Tech winning at everyone else’s expense. Entrepreneurs can keep some of the productivity gains, consumers get more choice, and platforms benefit from supplying the technology and connecting more producers with customers, he said. 

“The platforms and the people who are creating the tools are winning because they are able to sell them, the solopreneurs are winning because they are able to use them, and the consumers are winning because they are getting new products that they didn’t get before,” he said. “It’s mostly a bigger pie, so it’s a win-win-win — a triple win.” 

What AI may change is the shape of that bigger pie, he said. 

“Whenever there’s a technology change, a platform change, obviously it benefits the companies that are creating those platforms and technologies,” Brynjolfsson said. “But it also benefits new entrants who can start fresh.”