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Innovative technologies are creating powerful businesses at an unprecedented rate, new data suggests. Artificial intelligence startups are seeing revenue faster than previous waves of software companies, according to new data. I’m raising it.
Top AI groups reach multi-million dollar sales within a year, according to an analysis of payment information by fintech group Stripe. This is much faster in the startup life cycle than comparable non-AI technology groups.
The findings come as investors raise questions about the economic benefits of generative AI and how Big Tech will benefit from the trillions of dollars of investment expected next year in the computing infrastructure that supports this technology. It was announced in
But the data shows that young AI companies have more momentum than other highly touted tech startups of the past, especially in the “software-as-a-service” category.
Stripe, the $65 billion Silicon Valley giant, has compiled data on the annual revenue of the 100 most profitable private AI companies using its payments platform as of July 31, 2024, in 2018. Data was obtained in comparison to a peer group of promising SaaS startups as of July 2019. .
Stripe’s customers include some of the most high-profile AI groups, including OpenAI, Anthropic, Mistral, GitHub, and Midjourney.
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Data shows that AI startups in this cohort took a median of 11 months to reach $1 million in annualized revenue after their first sale on Stripe, compared to previous generations of SaaS companies. It was 15 months.
The AI startup, which has grown to over $30 million in annual revenue, achieved this milestone in 20 months. That’s five times faster than SaaS companies in the past.
However, a report released this month by Goldman Sachs notes that the computing infrastructure required to run and train AI models comes at a significant cost, stating that “Today’s AI winners are no longer capital-light businesses. ”, he expressed concerns about the profitability of the AI business.
Stripe’s data shows how AI startups, many of which are the latest incarnations of SaaS businesses, are adapting to these market trends by building experimental products that customers are willing to pay for. It reflects the presence of animals.
Launched in November 2022, ChatGPT, OpenAI’s AI chatbot, reached 100 million users within two months of release, making it the fastest-growing consumer application in history.
OpenAI has launched a subscription service for businesses to access ChatGPT, which has brought the company $3.6 billion in annual revenue, according to people familiar with the group’s finances. But the company is investing well over $5 billion a year in training new models.
“Unlike past generations of software companies, AI companies are under pressure to build monetization faster because they pay significant compute costs to begin with,” said Stripe’s head of information. Emily Sands says.
There is also a global demand for generative AI (software that can generate multimedia such as text, code, images, audio, and video). According to Stripe data, around 56% of AI companies’ revenue comes from overseas.
This demand has benefited AI image and audio generation groups such as ElevenLab, a London-based unicorn that makes AI voice software, and German AI language translation venture DeepL.
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“We find that in countries including Singapore (and) Iceland, more than 3 percent of the population actually buys from these top 100 AI companies,” Sands said. “This is truly a global phenomenon.”
Stripe itself is currently training AI models based on over $1 trillion of data annually across billions of transactions and millions of businesses to build more personalized checkout and payment processes. I am.
The speed of monetization reflects the ability of startups such as OpenAI, Anthropic, Google, and Meta to bring new products and features to market built on rapidly changing AI models, which can be used to improve transcription and applications. form the base. Coding assistant.
Byron Dieter, a partner at Bessemer Ventures, which invests in SaaS companies, says the problem with big software companies is that they have outdated technology architectures and are inherently slow, but startups have the proposition to quickly increase productivity. said.
“We’re seeing many (AI) companies go from zero to tens of millions of dollars (in revenue) within a few years,” Dieter said.
Additional reporting by Richard Waters
