We're not paying enough attention to Anthropic adding $6 billion ARR In February
This fact flew under the radar because all the attention is on war and oil. No one made a post about it. People are still not seeing AI stock growth potentials. AI stocks are still hugely under appreciated in terms of growth.
Anthropic added $6 billion ARR in February alone. ([Source](https://finance.yahoo.com/news/anthropic-arr-surges-19-billion-151028403.html)) February only had 28 days.
In July 2025, Morgan Stanley made an estimate on Anthropic:
>In its note, Morgan Stanley forecast Anthropic's revenue will grow from $4 billion this year to $10 billion in 2026 and $19 billion in 2027. The bank's analysts then assumed Anthropic gross profit margins of 60%, and estimated that 75% of related costs are spent on AWS cloud services.
They estimated $4b vs $9b actual in 2025. They estimated $10b total in 2026. Anthropic is already at $19b by end of Feb. $25b by end March at the same rate. **In other words, Morgan Stanley's picture of AI has been so wrong, it's downright laughable. They're likely going to be off by a factor of 10x.** Most of Wall Street and stock investors have been wrong on AI. They simply can't comprehend exponential curves. Humans are really bad at seeing exponentials. Human minds default to linear. There's actually lot of research on this.
You hang around r/investing to look for an edge right? Here's the edge: Wallstreet was off by 10x in estimating AI growth. Even if they've corrected their models, they're likely still vastly underestimating. The vast majority of r/investing members (representing the degen retail investors) still think AI is a scam and will collapse soon. You can tell because the negative comments below here will have far more upvotes than positive ones. Anti-AI comments will have 10x more upvotes than pro-AI comments. Scroll down and see for yourself. Both Wall Street and retail are extremely skeptical on AI despite the growing evidence of exponential scaling.
If you are not buying the dip on AI stocks, what are you doing?
To help you undertand what $6 billion in a month is:
* 1x Palantir annual revenue
* 5x Figma
* 1.34x Snowflake
* 1x Atlassian
* .25x Adobe
* .17x of SAP
* .14x of Salesforce
In a single short month, Anthropic added 1x Palantir annual revenue and 1.34x Snowflake. Think about this.
At the same growth rate, Anthropic will be significantly bigger than companies like Adobe, SAP, Salesforce by the end of 2026. In fact, if Anthropic added another $6b in March, they'll be at $25b ARR, the same size as Adobe.
All reports indicate that Anthropic could have added a lot more but are severely compute constraint. All developers know this already because Clade Code goes down frequently because they don't have enough compute to serve demand.
Your most likely thought is, well they can make a lot of money but are they making a profit? They're not profitable but they are on the way.
Anthropic CEO has repeatedly said that their gross margins on inference is 50%+. OpenAI CEO has said the same thing. Independent token analysis confirms this: [https://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/](https://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/)
There are also a ton of small inference providers on OpenRouter, and they are most certainly not going to inference at a loss since market share doesn't matter for them. They need to make more money per token than they lose because they do not have billions in VC backing.
So if they in such high demand, why can't Anthropic and OpenAI turn a profit? Because they don't need to yet. They're spending their money on the AGI race by training bigger, smarter models. Competition between OpenAI, Anthropic, Google, Meta, Chinese AI companies are intense.
So how can they ever make a profit then?
1. Inference revenue is outpacing training cost. This is happening now. In the past, training might have cost OpenAI/Anthropic 80% of their revenues. Today, it's a smaller and smaller pie as inference market explodes. Training is cost. Inference is profit. Inference profits need to grow faster than training costs and it is.
2. Many competitors will drop out. When competitors drop out, training costs do not need to rise as much. Given enough time, many tech fields are a natural monopoly or duopoly. Think Google search. Windows & MacOS. iOS and Android. Everyone expects foundational AI models to be a monopoly or duopoly because smaller competitors will not be able to come up with the compute to compete in training state of the art models. Leading AI model companies will run away as they make more money, use that money to train bigger models, leading to more users, leading to more data to train, etc. It's a flywheel effect. You can already see this today. Even if Apple threw all their profits into building a competitive state of the art models against OpenAI, Anthropic, Google, they can't. It's too late.
There are a lot of wrong takes on AI on r/investing. The goal posts keep moving. I've heard it all here:
* There is no demand or demand is "fake".
* AI is not useful or hallucinates too much.
* If AI is so useful, then where is the revenue?
* Ok, there is revenue, but where is the profit? <-- we are here
**tldr: Wallstreet still thinks AI is growing linearly when it's growing exponentially. Retail thinks AI is going to collapse. The war has given you a golden opportunity to buy the dip on AI stocks before everyone can comprehend its exponential growth rate.**
