We just pushed a big update to Ramp AI Index.
Available today: token and spend *volumes* not just shares or token counts. Updated weekly.
Model-by-model, including open-source models. And more to come, including team-based spend.
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If you see this chart, know this is my perspective:
the revenue growth path for OpenAI and Anthropic has weakened due to competition.
And that competition is from *other* US models, not China / open source.
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NEW from Ramp data. Despite cost-cutting on AI overall, one area companies are increasing their spend: AI security software.
In the wake of the Hugging Face hack, three of our trending software vendors (depthfirst, Monte Carlo, Antithesis) make software specifically designed to monitor agents in production.
Unclear as to whether any of them would have stopped the Hugging Face attack, which was so hard to track and identify because the agents covered their tracks with falsified logs.
I expect AI security will become a strong headwind to deeper enterprise adoption, at the short-term expense of OpenAI and Anthropic and at the long-term benefit of vertical-specific security software cos.
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OpenAI is winning enterprise spend at the frontier. As of this week, Astra takes 13% of enterprise AI spend vs. Fable (8%) per Ramp data.
Some early thoughts:
1. Anthropic took a big risk in its recent call to pace the frontier. It's frontier model has already fallen behind on adoption.
2. OpenAI's growth is primarily coming from shifts from Sol and some Anthropic models, net-new usage too. That's good for them and suggests some pricing power remains by having a good, competitive frontier model.
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Lately my posts have highlighted cracks in the AI thesis (prices falling, shifts to cheaper models) but my base case is pretty bullish for the main AI labs.
Yes, prices are falling. Yes, we've observed a shift to cheaper models, but OpenAI and Anthropic will maintain their dominant market share. Chinese models are not the threat to AI competition we think. And while OpenAI and Anthropic may see lower margins as they compete on price, so far they've been able to make it up in volume.
thank you @ProfGMarkets for having me
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Every once in a while, I'll get a dm from a stranger who saw me on a podcast or reads my work and has a specific question, and it makes me miss pre-DM twitter days when it was more common to @ anyone publicly and often get a response that was available for everyone to read and reply to
I still get lots of questions in direct replies to my tweets (I respond when i have something to add) but it's rare for someone to write publicly and out of the blue in a way that invites a totally new conversation / discourse
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NEW from Ramp AI Index: AI spend *declined* among the top 1% of businesses spending on AI.
In August, the top 1% of businesses spent $7.2K per employee per month, down 10% from a July peak ($8K).
We're seeing more cracks in the AI thesis as a number of drivers show spend topping out.
My take: it's not because of open Chinese models. It's model wars. Price cuts + a growing share of spend is shifting to standard and lite models (which are already cheaper) over the frontier.
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Early Ramp data (this only runs through the weekend), but looks like Fable 5.1, which got rid of the data retention requirements businesses said was a non-starter to adoption, is doing pretty well.
Now roughly 22.5% of their enterprise spend and rising. For reference, Sol makes up 31% of OpenAI spend.
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New from Ramp data: the latest threat to the AI trade. AI companies' revenues are heavily dependent on a small set of customers. 80% of OpenAI and Anthropic's enterprise revenues come from 1% of their customers, and it's not getting better.
This is a level of concentration risk unseen in any other software category we track. The companies in the top 1% skew heavily toward the tech sector and AI products and services.
What happens in a market correction? All these companies are highly correlated, and an increasing share of our economy is invested in them. Especially as we approach blockbuster IPOs for OpenAI and Anthropic.
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I’m hiring an economist / economics-leaning data scientist to join Ramp Economics Lab.
As AI adoption is approaches 100%, measuring whether businesses use AI is no longer enough. We need new metrics that show how deeply companies are using it, where it creates value, and how AI is changing the economy.
I'm looking for someone full-stack. You will:
1) Develop independent research and build new metrics for Ramp AI Index.
2) Build and design those metrics directly onto our website (we vibecode it ourselves)
3) Present our research externally, on-site with customers or in-person events.
Send your top recommendations!
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Our latest AI model market share estimates about 35% of token spend — via coding agents and other APIs — goes to OpenAI. Per business spend in @tryramp data
I think Cursor will be fine. Strong advantage in compute with SpaceXAI + a compelling and affordable model in Composer with great training data to support coding usecases.
Your economist could never
Ara "Aura" Kharazian never stops never stopping
In all seriousness, Ramp did not invent the concept of a private-sector economics team producing public-facing research.
The big banks have done it for years. Zillow/Redfin/Indeed all made it a central component of their marketing in the 2010s.
We were however the first to do it for a company of our size and scale, and do it well, which I attribute to a few things.
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be sure to like and subscribe for more credible analysis of proprietary data from a highly educated nerd
Fun one with @SoumayaKeynes on the increasing trend of AI startups hiring economics teams!
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What's up with the economics profession? Recently I've been hearing a lot about senior profs dusting off their CVs and trying to get gigs with the AI labs, as well as more arms-length collaborations. Working with an AI lab is seen as very cool. 🧵
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while I agree that it’s more important to think about “gross labor market disruption” than net employment growth impacts, I also think gross disruption has been very small outside of a few pockets
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Really good discussion between @arakharazian and @GavinSBaker here and the replies on the economics of AI.
I like FT’s chart design
Anthropic’s best AI model struggles to attract users as cheaper tools thrive
Anthropic’s best AI model struggles to attract users as cheaper tools thrive
Yes. And the sum has accelerated slightly QTD with a sharper acceleration in August vs. July.
And note that Grok Bot, Grok and Open Source are all likely growing faster than both of the two leading frontier labs.
But at some point going to have to move past second derivatives and focus on first derivatives.
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