AI companies a small fraction of shrinking Series A deal count
US Tech Series A deal count continues to fall into August. All data from Crunchbase.

AI companies a small fraction of shrinking Series A deal count

US Tech Series A deal pace continues to fall into August, as is readily apparent from the plot above.

The upcoming Klaviyo and Instacart IPOs will give us an important market reception test. If they go well then investors can see a clear path to venture liquidity, which should begin to increase appetite for commitments into venture funds, and in turn from venture funds into startups. If they go poorly, we’ll have to wait a bit.

So, is it just AI companies that are raising money in the current environment? Is the AI wave still building or has it already crested? I pulled the data in the plots below to look into this topic a bit.

Percentage of US Tech Seed and Series A announced financings with "ML" or "AI" in company name or Crunchbase company description.

Given the current startup echo chamber hype around AI, I would have assumed the fraction was significantly higher than the data above shows. Since the counts are small, the data bounces around a fair bit month-to-month, so I also plotted below are the cumulative ratios since January 1, 2022, which gives another view of the same underlying data.

Cumulative percentage of US Tech Seed and Series A "ML" or "AI" companies. Same underlying data as plot above.

The AI wave is clearly still building, but reflects a relatively modest fraction of all financings. At some point AI/ML capabilities will be taken as a given and not a key part of the description. Like “our offering makes use of the Internet” would sound odd today, but is probably true for most startups. I don’t think we’re close to that point for AI/ML.

My definition of “ML or AI in Company Name or Description in Crunchbase” isn't perfect, but it's pretty good and I don't think it has any major systematic inclusion/exclusion biases built into it. Does that definition Under-report or Over-report? One could argue “Under-report”: if a company is AI/ML focused but didn't put that is description. One could also argue “Over-report”: if a company tangentially has some AI/ML capabilities, but added it to their description for marketing purposes. I think the “Over-reported” argument probably dominates in the current environment.


Nicholas Fok

Quantitative Finance Leader & Successful Founder | Investor | Mentor | Focused on AI Innovation

1 周

It's interesting to see the ongoing interest in SW companies within AI. Do you think this trend will continue, or might we see a shift towards HW or service infrastructure in the near future? What other sectors do you think are gaining traction in fundraising efforts?

回复

Great insights! It's intriguing to see how AI companies are navigating the evolving Series A deal landscape amidst the current funding environment. The data provides a refreshing look beyond the AI hype, showing that while the wave is still building, AI companies make up a relatively modest fraction of total financings. As AI/ML capabilities become more integral to startups, the distinction between 'AI-focused' companies and those using AI as a part of their solution may indeed blur over time. However, for now, AI remains a driving force in innovation across industries. For anyone looking to dive deeper into the companies pushing the boundaries of AI, MobileAppDaily’s Top artificial intelligence app development company directory is an excellent resource. It highlights the leading firms shaping AI technology today. Exciting times lie ahead, and I look forward to seeing how the market evolves, especially with these groundbreaking companies at the forefront. https://www.mobileappdaily.com/directory/artificial-intelligence-companies/in?utm_source=linkedin&utm_medium=hc&utm_campaign=mad

回复
John Brewer, Jr.

CEO, President at Amorphyx Inc.

1 年

I bet if you charted the physical location of deal closings in August, the results would cluster around Lake Tahoe... ??

回复

It would be interesting to see where the rest of the venture dollars are going outside of AI, and also how they are allocated within AI to sub segments. Are the newly funded startups focused on the SW, HW or services infrastructure or are they moving up the chain to the application layer?

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