U.S. small businesses without employees are applying more in AI-exposed industries, as AI gives individuals capabilities that once required teams
CNBC reported that from the first quarter of 2024 to the first quarter of 2026, among industries with higher exposure to AI, the quarterly number of business applications with no obvious signs of hiring rose from about 222,000 to 281,000, an increase of 26.8%. Over the same period, applications in these industries with strong signs of eventually becoming employer firms fell by 6.4%. In the comparison industries (construction and wholesale trade), no-employee-type applications fell by 0.4%.
The data came from a study by Liya Palagashvili, a labor economist at George Mason University’s Mercatus Center. She pointed out that AI gives individuals capabilities that once required teams to complete. The study is a preliminary descriptive result and did not prove that AI caused the growth, and applications with no hiring signs do not mean that a company ultimately remained a one-person operation.
The report gave examples: Alex Willen runs 12 no-employee e-commerce brands and is expected to have revenue of $2.5 million to $3 million this year; Kristin Ginn left Microsoft in March and founded the AI adoption consulting company trnsfrmAItn. Seven months later, she had received or contracted about $250,000 in business, with no employees or regular contractors. Stanford economist Erik Brynjolfsson said that the biggest misconception is that AI only improves individual productivity; in fact, it enables individuals to complete tasks that once required an entire team.
Original sources:
Title: America's newest small business owners with no employees are off to a hot start in AI era Publisher: CNBC Date of publication: 2026-11-07 URL: https://www.cnbc.com/2026/11/07/americas-new-no-employee-small-business-owners-start-hot-in-ai-era.html Nature of source: media report Verification status: Full text read in this report; cross-checked the cited Mercatus research summary and economists' statements Supporting content: 26.8% growth in no-hiring-sign applications in AI-exposed industries, decline in employer-type applications, individual cases, and Brynjolfsson quote
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Palagashvili's data separates application types into those with no early signs of hiring and those with strong signs of being employers. In AI-exposed industries, the former rose and the latter fell, in contrast with non-AI-exposed industries, suggesting that the minimum operational scale may be shrinking. The study explicitly did not establish causality, and the application metrics cannot confirm whether the firms later hired.
The cases of Willen and Ginn show that individuals can use tools such as Claude and OpenAI to cover functions including bookkeeping, customer service, advertising, design, and inventory, while generating a certain level of revenue. Willen said that without AI he would need additional full-time employees and contractors; Ginn launched her consulting business at relatively low tool cost. These are individual cases and do not represent the overall distribution.
Brynjolfsson also pointed out that AI may lengthen the long tail of small producers while strengthening the aggregation power of large platforms, and may also lead to the hollowing out of mid-sized companies, as management-level coordination functions are compressed. Research by institutions such as AWS also shows that some AI-native startups have higher revenue per employee. Current evidence still mainly consists of application data, individual cases, and economists' judgments, and the impact on long-term employment and industry concentration remains to be observed.
ABAB News · Cognitive Law
In AI-exposed industries, applications with no signs of hiring rose, while employer-type applications fell.
Individuals can use existing models to cover functions that once belonged to teams and generate revenue.
The study is descriptive, does not establish AI as the direct cause, and does not confirm the firms' subsequent hiring status.