AI revenues are growing fast, but not fast enough(economist.com) |
AI revenues are growing fast, but not fast enough(economist.com) |
So between $170bn-220bn in annualized AI revenue today. Maybe it doesn't cover trillion-dollar bets but this is a very substantial number.
Brutal stuff.
So from the top it doesn't look like much has changed, whereas workers are trying to offload as much work as they can onto their claude subscription.
People in desperation to min/max work per unit dollar, will leverage AI to free themselves from as much work as possible, while still claiming credit for the work.
So as the labs start ratcheting up the price, people will pay more and more to keep their "secret" assistant.
It could easily turn into a Red Queen situation where companies that don't spend hard on security are going to face huge potential losses, and both sides will be scrambling constantly to get an advantage.
For unskilled people, it creates a false sense of productivity, but if the user of the tech does not understand what they are doing they can’t apply the tool productively or judge its output or deal with the things beyond its ability.
So like all other tools before it: it works best in the hands of a skilled user.
Just like in all other fields.
There is no tool that makes an unskilled user skilled, but there are many that can amplify or extend the capability of skill.
And I run my own firm... but I have to compete against a global market of other programmers using similar tools who are also trying to compete on price, and then there are hordes of new entrants who can vibe-code things that superficially look like they'll meet a customer's needs and are better at marketing than I am, so my area of business gets constrained to just customers who need help after the problems with the vibe-coded solution appear, the vendor who made it is long gone, and they already spent an inordinate amount of money on the vibe-coded solution since they thought it was complete and it looked pretty good.
Agentic coding could help a lot for the latter, not necessarily the former.
If the aspiration of a 10x or more programmer is enabled through AI then the capital class win, in the typical case. Software eats the world.
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> All these complex calculations roughly tally with a much simpler one: adding up the ai revenue of the firms selling most of the ai. Anthropic pulls in perhaps $75bn, annualised; Openai makes tens of billions; Google, via its ai model Gemini, and Microsoft probably get a bit less. SpaceX may have a few billion dollars’ worth of revenue from enterprise aithis year. Meta also makes a few bucks from ai. Add this up and you land at roughly $150bn a year.
Yes, I will concede this point. But how are the Chinese labs going to thrive with giving the weights away for free? Will they suffer the same fate open source database companies did at the hands of AWS?
I noticed that were a lot of traditional, non-tech companies interviewing for AI engineers in the Feb/March timeframe that have halted hiring in those roles entirely. It seems that if those roles didn't close by mid-April that they didn't close at all. This seems to match the timeframe in which cost suddenly became prominent in the AI zeitgeist.
I don't know _anyone_ outside of SV who has successfully replaced even a single employee completely with the current models. Maybe someone has pulled this off in call centers, but the POCs have all failed.
I'm very much pro-AI, but I just think we're on a false summit. As the article points out, there is absolutely no way to recoup the investment costs unless the models allow companies to start displacing human workers by the millions _and_ recapture a significant fraction of the displaced workers total comp. If either of those aren't true, then the bubble is going to pop... soon.
In other words usage per regular worker doesn't matter. Revenue overall does.