Friday, August 14, 2026

The age of the solopreneur

More solo founders, growing faster, powered by AI

By Ernie Tedeschi, Marisa Rama, and Chris Cruickshank. Excerpts:

"This post advances three related arguments. First, solopreneurship is growing faster than employer-business formation, and the acceleration is validated by multiple independent data sources, making it unlikely to be driven by a fraud wave. Second, both the number and share of solopreneurs reaching meaningful income thresholds is rising. And third, early signals indicate that AI is filling the capability gaps that once made hiring necessary—and doing so fast enough to show up in the income distribution. 

New business applications in the Census Bureau’s Business Formation Statistics have been flashing an unusual signal for the past 18 months. New business applications are filings with state agencies and the Internal Revenue Service that precede actual commercial activity. These new applications reaccelerated beginning in late 2024, after spiking in 2020 at the beginning of the pandemic and remaining elevated thereafter.

This acceleration, however, is not being driven by applications from businesses that have a “high propensity” or likelihood to become employers."

"Businesses that signed up on Stripe after 2023 reached material transaction volumes earlier than the sign-up cohorts that preceded them. The share of businesses (not just solopreneurs) reaching $1 million in cumulative revenue within a year after going live on Stripe was roughly 30% higher for the 2025 cohort as it was for the 2023 cohort, and it was roughly 3x higher for the 2025 cohort than the 2019 cohort. If more recent sign-up cohorts were increasingly driven by inactive businesses, we would expect more time to material volume thresholds, not less."

"the story of spiking business applications is not confined to the United States. New business registrations have risen roughly 40% in Australia, 70% in Finland, and 80% in France since 2017, with meaningful acceleration in 2025 alone. Multicountry acceleration across different regulatory environments argues for a more fundamental driver than fraud activity. And in France, where more granular data is available, the surge in business formation is driven primarily by solo founders or microentrepreneurs rather than by traditional employer businesses—similar to the US."

"In 2023, roughly four million Americans earned their primary income as solopreneurs, generating over $100,000 in annual revenue. That figure has risen substantially from the mid two-million range of the early 2010s"

There is "a consistent upward trajectory in both the count and share of solopreneurs earning above various income thresholds."

"We find that there has been a substantial increase in the number of solopreneurs earning over $100,000 in our index, but an even larger increase in the number earning at higher income thresholds, with a clear acceleration since 2023. More than twice as many solopreneurs earned over $1 million in 2025 than in 2023, and close to three times as many crossed $5 million and $10 million.

Perhaps even more interestingly, the share of solopreneurs earning above these income thresholds has also doubled in the last two years, suggesting that—rather than the surge in business applications reflecting low-quality experimentation with a few lucky standouts— the cohorts of new solopreneur businesses might actually be of higher quality than in the past."

"It seems likely that AI is one of the primary drivers of both the acceleration in solo business formation"

"An agent can now help you find the best tools for your business and handle your integration with minimal support."

"The recent growth in nonemployer businesses shows a positive relationship with industry-level AI adoption, suggesting that higher AI adoption has been broadly consistent with more growth in nonemployer applications"

"Part of the reason businesses historically tended to be built by groups was that a single individual rarely possesses all the skills needed in the entrepreneurial journey. Whether it’s how to evaluate or size a market, code an app, price a product, write and execute a marketing campaign, or close a deal, AI (and AI-augmented software) can fill many of the gaps that founders previously turned to another human for."

Conclusion

While the recent surge in US business formation is not reflected in high-propensity applications, the evidence points toward a structural increase in genuine small business activity over 2025 and 2026, driven by solopreneurs. Preliminary evidence of growth in AI tool usage and solopreneur growth in high-AI-adoption sectors suggests that advances in AI are responsible for a meaningful portion of this growth. We believe AI is lowering barriers to business formation and growth by expanding the capabilities of solopreneurs, further improving tools and platforms that cater to new businesses, and creating a new set of opportunities for entrepreneurs to pursue. Whether the magnitude of this effect is as large as the most optimistic readings of the data suggest remains to be seen, but we believe we might be in the early innings of a fundamental acceleration in business formation—which could have ripple effects throughout the economy."

Wednesday, August 12, 2026

The Seasonally Adjusted CPI Was Up 0.074% in July

Here are the changes in the seasonally adjusted CPI for the six months ending in June: 

Jan. 0.1708%
Feb. 0.2670
March 0.8651%
April 0.6400%
May 0.4729%
June -0.4220%
 
The last decline before June this year was June 2024 when it was -0.042%.
 
See Consumer Price Index for All Urban Consumers: All Items in U.S. City Average from FRED (Federal Reserve Economic Data) compiled by the Research Division at the Federal Reserve Bank of St. Louis for data on the seasonally adjusted CPI.  

That site shows a graph but if you click on the Download button you will get the actual numbers in Microsoft Excel.

The Consumer Price Index for All Urban Consumers: All Items in U.S. City Average (CPIAUCSL) was 332.813 in July and 332.568 in June. Since 332.813/332.568 = 1.00074, that means it was up 0.074%. If we had that every month for 12 months the CPI would be up just 0.888%.  

It was 322.169 in July 2025. Since 332.813/322.169 = 1.033, that means it was up 3.3% over the last 12 months.
 
The non-seasonally adjusted CPI was 333.918 in July and 323.048 in July 2025. That was up 3.37%. So pretty close to the seasonally adjusted CPI. This is well above the Fed's target of 2.0% (although they prefer to use the Personal Consumption Expenditures Price Index which was 3.7% higher in June 2026 than June 2025).
 
For more information see Consumer prices rose 0.1% in July, as expected, putting the annual rate at 3.4% by Jeff Cox of CNBC. Excerpt: 
"A key inflation reading Wednesday showed prices moderating across a range of goods and services, possibly taking the urgency out of an imminent interest rate hike.

The consumer price index, part of the Federal Reserve’s inflation dashboard, showed a seasonally adjusted increase of 0.1% during July, according to the Bureau of Labor Statistics. Excluding food and energy, the so-called core CPI rose 0.2%.

On an annual basis, the inflation rates were 3.4% and 2.5%, both down 0.1 percentage point from June.

All of the readings were line with the Dow Jones consensus forecasts.

Though the levels held well above the Fed’s 2% target, the tame monthly readings, coupled with similarly moderate levels in June, indicate that the energy-fueled burst earlier in the year is easing, though prices remain volatile and subject to constantly changing conditions in the Middle East."

The article also discusses what types of products are going up in price and what is going down. There is a graph of the monthly year-over-year percent change in prices and core prices going back almost 4 years. 

Related material: 

Consumer Price Index for All Urban Consumers: All Items Less Food and Energy in U.S. City Average (CPILFESL) This is also from from FRED (Federal Reserve Economic Data), compiled by the Research Division at the Federal Reserve Bank of St. Louis. It has the seasonally adjusted core CPI.
 
 
 
The Bureau of Labor Statistics makes seasonal adjustments. See Consumer Price Index Summary.
 
The table below has the annual inflation rate since 1914 in the columns labeled CPI %Ch. or CPI percentage change. It is from Consumer Price Index Data from 1913 to 2026 and is not seasonally adjusted. It is also the December to December change in the CPI. That site also looks at how the 12 month average for the CPI changed from one year to the next.  
 

Year

CPI %Ch.

 

Year

CPI %Ch.

 

Year

CPI %Ch.

 

Year

CPI %Ch.

1914

1

 

1944

2.3

 

1974

12.3

 

2004

3.3

1915

2

 

1945

2.2

 

1975

6.9

 

2005

3.4

1916

12.6

 

1946

18.1

 

1976

4.9

 

2006

2.5

1917

18.1

 

1947

8.8

 

1977

6.7

 

2007

4.1

1918

20.4

 

1948

3

 

1978

9

 

2008

0.1

1919

14.5

 

1949

-2.1

 

1979

13.3

 

2009

2.7

1920

2.6

 

1950

5.9

 

1980

12.5

 

2010

1.5

1921

-10.8

 

1951

6

 

1981

8.9

 

2011

3

1922

-2.3

 

1952

0.8

 

1982

3.8

 

2012

1.7

1923

2.4

 

1953

0.7

 

1983

3.8

 

2013

1.5

1924

0

 

1954

-0.7

 

1984

3.9

 

2014

0.8

1925

3.5

 

1955

0.4

 

1985

3.8

 

2015

0.7

1926

-1.1

 

1956

3

 

1986

1.1

 

2016

2.1

1927

-2.3

 

1957

2.9

 

1987

4.4

 

2017

2.1

1928

-1.2

 

1958

1.8

 

1988

4.4

 

2018

1.9

1929

0.6

 

1959

1.7

 

1989

4.6

 

2019

2.3

1930

-6.4

 

1960

1.4

 

1990

6.1

 

2020

1.4

1931

-9.3

 

1961

0.7

 

1991

3.1

 

2021

7

1932

-10.3

 

1962

1.3

 

1992

2.9

 

2022

6.5

1933

0.8

 

1963

1.6

 

1993

2.7

 

2023

3.4

1934

1.5

 

1964

1

 

1994

2.7

 

2024

2.9

1935

3

 

1965

1.9

 

1995

2.5

 

         2025    

          2.7

1936

1.4

 

1966

3.5

 

1996

3.3

 

 

 

1937

2.9

 

1967

3

 

1997

1.7

 

 

 

1938

-2.8

 

1968

4.7

 

1998

1.6

 

 

 

1939

0

 

1969

6.2

 

1999

2.7

 

 

 

1940

0.7

 

1970

5.6

 

2000

3.4

 

 

 

1941

9.9

 

1971

3.3

 

2001

1.6

 

 

 

1942

9

 

1972

3.4

 

2002

2.4

 

 

 

1943

3

 

1973

8.7

 

2003

1.9

 

 

 

 
Here is a timeline graph of this data: