$100M ARR with <100 Employees: AI startups are defining new standards
Will the AI era belong to small teams?
Hey, Pierre-Jean here ๐ Welcome to this new edition of The Growth Mind!
Today, Iโm sharing insights and data on how AI-native companies are scaling faster than ever, redefining what great growth looks like.
โฑ๏ธ Reading time โ 5 minutes
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AI native companies are growing fast, with teams leaner than ever before
Iโve recently come across this great chart made by Newfund Capital, an early-stage VC based in Silicon Valley and Paris, showing how AI native companies manage to grow with much smaller teams.
While $100M ARR used to take 500+ employees in the early 2000sโ, some AI startups are now reaching this point with <100, reshaping the way we envision what is good growth.
Looking back at the past 20+ years, we can separate the type of companies reaching $100M ARR fast in 3 categories:
1๏ธโฃ ๐ฎ๐ฌ๐ฌ๐ฌ-๐ฎ๐ฌ๐ญ๐ฌ โ ๐ง๐ต๐ฒ ๐ต๐๐บ๐ฎ๐ป-๐ฝ๐ผ๐๐ฒ๐ฟ๐ฒ๐ฑ ๐ฑ๐ถ๐ด๐ถ๐๐ฎ๐น ๐ฝ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ๐
ARR per employee โ $70k - $200k
This was the era of marketplaces and consumer platforms.
An era where a lot of existing services needed to be digitalized (eg. Airbnb for booking a night in someoneโs house, Doctolib to get a medical appointment). Those companies needed 500 to 1,500+ employees to reach $100M ARR.
2๏ธโฃ ๐ฎ๐ฌ๐ญ๐ฌ-๐ฎ๐ฌ๐ฎ๐ฌ โ ๐ง๐ต๐ฒ ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐-๐น๐ฒ๐ฑ ๐ด๐ฟ๐ผ๐๐๐ต ๐ฒ๐ฟ๐ฎ
ARR per employee โ $200k - $350k
Entered the era of product-led growth, where B2B SaaS startups were revolutionizing the way we buy software, by adopting an approach where the product is the main growth driver, and not the sales team anymore.
They โconsumerizedโ the way B2B SaaS grew, leading to a better ARR per employee. Slack, Loom or Calendly are perfect examples of it.
Those companies needed 300-500 employees to reach $100M ARR.
3๏ธโฃ >๐ฎ๐ฌ๐ฎ๐ฎ โ ๐๐-๐ฝ๐ผ๐๐ฒ๐ฟ๐ฒ๐ฑ ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐
ARR per employee range โ $1M - $2M
Weโre now in the AI era, where companies of less than 100 employees are reaching $100M ARR.
Those startups manage to grow fast with small teams, thanks to products that scale and operations that are more automated than ever before.
Some of the most famous ones are Cursor and Midjourney, but Open AI is also in similar standards.
ARR per full-time employee (FTE) is then reaching higher standards
ARR (annual recurring revenue) per employee was already a super important metric for SaaS businesses. The more revenue per employee you make, the more chances to be profitable. But standards are likely to be redefined if we look at AI native startupsโ trajectory.
Early 2024, Kyle Poyar, the author of
, shared the following benchmark of what is a good and great ARR per FTE:
Whatโs interesting to see is how things changed in a few months. The best performing AI companies, with an ARR per employee > 1M$, are outperforming by far (>3x) what was considered as โgreatโ. Of course, they are outliers yet, but theyโre shaping a new trend.
Even at a smaller stage, some AI companies are already crushing it. Take Lovable example: they reached 17M$ ARR with a team of 15 employees, only 3 months after their launch ๐
Another great example, but this time at a much larger scale, is Open AI. Itโs quite hard to have very precise date data about their revenue and number of employees, but we estimate that in late 2024:
Open AI Revenue was ~$4 billion (source: https://sacra.com/c/openai/)
~3,500-4,000 employees worked at Open AI at this time
So the ARR per FTE is estimated โ 1M - 1.2M per employee
Take this data with caution, as itโs only an estimation. But it gives us an order of magnitude.
Are we going to see the end of large teams? How will it shape the tech economy in the future?
โIn my little group chat with my tech CEO friends thereโs this betting pool for the first year that there is a one-person billion-dollar companyโ
Sam Altman
A year ago, Sam Altman predicted that AI would soon enable a single founder to build a unicorn without having to hire employees.
Weโre not there yet, but there is a trend going in that direction. Iโm not sure about its impact in 10+ years, but here are a few key factors I wanted to go through:
1/ Small teams can achieve more than ever before. But the hypergrowth of some amazing companies might also be misleading.
Thanks to AI, you can now automate or at least reduce the time spent on many individual tasks. Meaning you can do more with fewer people. Weโre still in the early stages of the AI curve, so I believe that companies that are crushing it yet are surfing on a strong wave. Everyone wants to use AI for everything, so the demand is huge, while the offer of great products is still relatively low. With more competitors popping up in the future, things might tend to come back to โnormalโ.
2/ AI is reshaping the software/app industry as Shopify/CMS did with E-commerce. Competition will become more intense.
With fewer barriers to create softwares/apps, weโll likely see thousands of similar products popping up. Distribution, coupled with a good product sense, will then become even more important. We saw this in the last 5-10 years, when dropshipping became a strong trend, helped by the rise of Shopify and other CMS that reduced the complexity of building an online store.
90%+ products will probably fail, but itโs an opportunity to create, especially for non-tech people.
3/ With โlow qualityโ tasks (partially) automated by AI, having good taste and being capable of taking the right decisions will be your superpowers.
We already seeing AI used strongly for:
handling basic support tickets
writing/reviewing code
assisting in content creation/ideation
That means some of the tasks needing a human will be soon (or already are) partially or fully automated. Nothing to fear in my opinion, as itโs how the world always evolved since the Industrial Revolution. But the purely โsoftโ skills, like understanding user needs or having a good taste when building a product or a campaign, are what differentiate you. As it has always been, being adaptable and a continuous learner are strong strengths.
In short, exciting times ahead ๐
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