> the frontier labs are priced according to the narrative that they have produced or will in the very near future produce a fully automated drop-in replacement for most knowledge workers...
Even assuming this is how the AI companies are being valued (they're not), the numbers are off.
The "value" of most knowledge workers -- based on what enterprises currently pay for them -- is $50 - 70 trillion annually. It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing.
So if their hypothetical revenues are double-digit trillions and valuations are some multiple of that, the entire AI industry would be valued at double-digit trillions at the least.
Yet cumulatively the industry (the frontier labs + the SWAG estimate of the AI parts of all the other players) are valued at, say, ~6 - 7 trillion? Which seems like a fair approximation of how much knowledge work they can currently automate.
You’re right; given that most of the money in the AI market is injected through OpenAI and Anthropic (which collect it through both selling equity and through customer revenue), the 7-8T is just a derivative of that.
When thinking about these valuations, shouldn’t we try to quantify how much knowledge work becomes obsolete if other knowledge workers are automated? I.e. there are a huge amount of knowledge workers employed in businesses that create tools for other knowledge workers. AI won’t automate their work, those businesses will just cease to exist.
And then there’s the second order effect: if all the knowledge workers get automated, who is going to buy the stuff that’s produced?
I think you are committing the lump of labor fallacy [1]. Lots of jobs will disappear, but others will appear. Lots of things (both intellectual and material) that are produced nowadays by humans will be produced in the near future by AI. But humans will be needed to do new things.
Take the Hugging Face incident. Why did it happen? Because the people whose task was to set up a testing framework took shortcuts. Why did they? Because there weren't enough people who were assigned to do the job. Why not? Because the job is too new and not enough people are qualified to do it. It's a job that simply did not exist 3 years ago. But 3 years from now, this job might very well employ tens of thousands of high skill knowledge workers.
That’s fair. I guess I’m also thinking that whatever new kinds of intellectual work that arise from the introduction of AI could be also done by AI. But maybe this comes from a lack of imagination again.
Oh for sure, this was a simplistic analysis assuming AI adoption caps out at some X% of job responsibilities where X << 100%.
Unfortunately, I fear that may not be the most likely outcome. I've posted some comments on this before, but when I start thinking about how deeply everything will change once people figure out how to properly leverage AI, I see no outcome other than significant, widespread job losses.
As you indicated, at that point we will have much a bigger problem than the valuation of the AI industry. I'm not sure how it will get solved, I just know it will HAVE to be, because it would be an existential problem for everybody: people, governments, even the billionaires! Because now consider the 3rd order effects: if nobody can buy the stuff that's produced, how can billionaires get even richer? ;-)
> The "value" of most knowledge workers -- based on what enterprises currently pay for them -- is $50 - 70 trillion annually.
What do you mean? The sum of ALL US salaries is $13.4 Trillion per year. According to google $65T is the sum of ALL salaries Globally (not just knowledge workers). It's not reasonable to assume AI is a drop-in-replacement for any job yet (perhaps bottom tier customer support from oversees?).
> So if their hypothetical revenues are double-digit trillions and valuations are some multiple of that
So you're sort of premising here than more than 16% or 1/6 of all the world's jobs get replaced by AI. Hopefully you can understand that's both not the current AI capability and also would be a terrible (unprecedented?) economic shock.
You are comparing company valuations to annualized revenue (as approximated by some fraction of total knowledge worker compensation). Valuations are (roughly) based on the sum of all discounted future cash flows, not just the current year’s revenue.
That's what the 30x instead of 20x multiple is, for a "growth" tech company.
There's no strong evidence that openAI or anthropic will have non-linear revenue growth, so I'm not sure what point you're trying to make. Unless you think they'll fire all their engineers and replace them with agents or something crazy?
It does not have to be 16% of all jobs, but 16% of any given job, i.e. AI stays in an augmentative role rather than a complete job automation. The simplistic analysis is if a tool makes you X% faster, that can be worth X% of your salary to your employer.
Unfortunately, I do fear that AI adoption will go beyond augmentation to automation, and I do fear an economic shock. Just posted this down-thread: <a href="https://news.ycombinator.com/item?id=49722616">https://news.ycombinator.com/item?id=49722616
You said 10s of trillions of dollars of revenue, which when the sum of all salaries is 65T, is minimum 15.3% of all salaries best case. It really feels like you're just pulling numbers out of nowhere here.
Yes, say the sum of all salaries paid be employers is $65T, and if AI accelerates workers by 15.4% -- studies and survey data actually suggest it's closer to 33% already e.g. <a href="https://www.stlouisfed.org/on-the-economy/2025/nov/state-generative-ai-adoption-2025" rel="nofollow">https://www.stlouisfed.org/on-the-economy/2025/nov/state-gen... -- that is worth 15.4% of 65T which is 10T, which is already "double-digit trillions" as I said.
Assuming a 33% boost takes it to ~20T annually, which is technically "10s of trillions of dollars" in revenue. And these numbers are from before agentic tasks arrived on the scene, so the actual productivity boost and corresponding value to employers is likely even higher.
Did you read your link? It says that 33% of people adopt AI, not that AI makes all workers 33% more effective, that would be absolutely insane. For that to be true we'd expect to see either companies who use it have revenues all suddenly jumping 33% (which we have not seen) or laying off 33% of their staff (which we have not seen and would also be catastrophic in the short term at least).
I'm not really going to belabor this point more, because it really sounds to me like you haven't even done the most cursory exploration into this and the people who have give an estimate of 7-10%[1] (and only a small fraction of that value would be captured by the AI provider). All the best.
Yep, I read the link, their detailed paper (<a href="https://s3.amazonaws.com/real.stlouisfed.org/wp/2024/2024-027.pdf" rel="nofollow">https://s3.amazonaws.com/real.stlouisfed.org/wp/2024/2024-02...) and I also played with their data tracker here: <a href="https://www.genaiadoptiontracker.com/#explore-data" rel="nofollow">https://www.genaiadoptiontracker.com/#explore-data
Toggle "Work hours using genAI" and "Time savings due to genAI" so see what I mean. You can also toggle between various industries, which is eye-opening because even industries like "Agriculture, Forestry, Fishing, and Hunting" are seeing productivity gains!
And if you do not want to read the detailed paper, they have a follow-up article here: <a href="https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity" rel="nofollow">https://www.stlouisfed.org/on-the-economy/2025/feb/impact-ge...
Specific quote:
> Using our data on generative AI use, this estimate implies that, on average, workers are 33% more productive in each hour that they use generative AI. This estimate is in line with the average estimated productivity gain from several randomized experiments on generative AI usage.
What we HAVE seen is that the national labor productivity has gone up by 1.3% since ChatGPT was released, and it lines up very well with all the other data and studies they cover... AND your reference, which predicted a 1.5% growth back in 2023!
> It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing.
Future supply and demand will set the price - not what is paid today. If supply by open models is vast and cheap, I can't see that the entire knowledge industry can hold the current size. It'll rather collapse to a fraction of its current value.
> The "value" of most knowledge workers -- based on what enterprises currently pay for them -- is $50 - 70 trillion annually. It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing.
I don't think that AI companies can charge the same. The human workforce can charge these costs, because of scarcity. But AI systems won't be scarce, it's just a matter of who can run inference cheapest. Plus you still have the human workforce, which might be forced to offer their time for less money.
In one case (financial services) it's thought that expertise is valuable at V=S^2/b4 where V is value, S is skill and b capacity (the leverage available to the manager/expert. b erodes as it becomes harder to find examples of things that are not done well, so if you manage $1bn you might find lots of miss allocations that you can exploit with just that $1bn really effectively, but if you manage $10bn it's much harder to find good places for the extra $9bn. A low hanging fruit effect.
Anyway, that double hit - raw skill and the amount of times you can supply the skill makes the value of skill (V) convex, and it means that in a perfect market (heh heh heh) someone running $100bn is worth 1000's or maybe 10,000's of an average joe expert.
Now, if AI is trusted to run the top 0.1% of everything and has the skill to do it at human top level expertise, then your calc holds. If it's the case that it isn't then more than half of that value disappears. If it's not even top 1% then chop out another 25%.
That implies that we need a lot of trust and a lot of AI capability before these valuations stack up, and it also implies that all other competitors and incumbants are going away. I do not think that Citidal or Bridgewater are going to let Anthropic or OAI take them without a fight. They might lose - but there is a decent bet that they don't. I don't think that many professions like Lawyers or Doctors are just going to roll over and cede their monopoly rights to OAI or Anthropic either.
The real issue IMO is that is not really what Anthropic and OpenAI are operating on.
That is the after the fact justification of the AGI dollar auction. Each round is kind of 3x the previous cost and neither can really stop because second place in the dollar auction is so much worse than winning.
The only way to stop the auction is one bidder hits a hard budget constraint, both agree to stop, or an outside party breaks the auction.
IMO this is why they want to slow down or have regulation. I think this is also why we see some claims of already reaching "AGI".
The TAM of global knowledge work is just a narrative tacked on after the fact to justify the AGI dollar auction.
The economic fallacy here with the actual valuation is akin to pricing the electric utilities 120+ years ago as some % of the future cash flow of global food production. Take the TAM of global food production and then work back to what % will the electric utilities capture from the advances in the automation of farming? It is nonsense.
The only narrative that actually justifies the capex spend that I can figure out is a first mover AGI monopoly. Even the oligopoly case is hard to justify the capex spend IMO. There is this enormous mismatch between the AGI monopoly and the actual rolling 12-month window of pricing power.
Even the rolling 12-month window of pricing power is going to saturate well before AGI too so it is hard to see how any of this makes economic sense.
Could you say more about the AGI dollar auction? Is that something investors are actually thinking about, or a metaphor for what's happening? From what I've read so far, while AGI is definitely a well-known concept, investors are not really banking on it.
FWIW even without AGI there are indications that all this CapEx spend, even with very shallow adoption, is boosting national labor productivity by 1.3%. That is worth ~$123B based on total wages paid in the US alone: <a href="https://news.ycombinator.com/item?id=49721338">https://news.ycombinator.com/item?id=49721338
As such I don't see the need for AGI for any of this to be financially viable. Whether it is economically and socially viable... that's where I have grave doubts.
But Capitalism really only focuses on the former and not the latter, which is why this will keep getting pushed forward. And that is the crux of the problem.
> It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing
This assumes you don't change the market, but at the scale of (checks notes...) "all knowledge work", that just doesn't hold.
For example if you put 1bn people out of work, you now need some sort of safety net to bail out much of that workforce, a truly unprecedented change. You also lose tens of trillions of dollars of tax revenue.
One solution might be to recoup that cost and lost tax revenue from businesses by raising corporation tax. If corporation tax went from low tens of percent to high tens of percent, would those businesses be able to afford all that AI? No. Same order of magnitude? I doubt it.
There are many possible futures there, but the simplification made in the parent comment is completely unrealistic. The article is right in calling out the valuations as crazy.
The changes that AI technology bring are unprecedented, it’s hard to predict what the impact of widespread adoption will look like. Probably collapse of price as a decentralized mechanism of ressource allocation, and a deep inevitable paradigm shift in economics and politics. It’s as if the actual value of those companies can’t be reliably pinned on any currency amount!
Yes, posted it elsewhere: <a href="https://news.ycombinator.com/item?id=49722616">https://news.ycombinator.com/item?id=49722616 -- this is necessarily a simplistic analysis to address a simplistic point in TFA, but it still kinda-sorta works assuming AI only augments workers and does not replace them wholesale.
I would add to the other comments that are replying below the following thought : replacing workers with AI means less income/spending, which drives the value of those companies down at the same time.
keeda · · focus · HN ↗
> the frontier labs are priced according to the narrative that they have produced or will in the very near future produce a fully automated drop-in replacement for most knowledge workers...
Even assuming this is how the AI companies are being valued (they're not), the numbers are off.
The "value" of most knowledge workers -- based on what enterprises currently pay for them -- is $50 - 70 trillion annually. It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing.
So if their hypothetical revenues are double-digit trillions and valuations are some multiple of that, the entire AI industry would be valued at double-digit trillions at the least.
Yet cumulatively the industry (the frontier labs + the SWAG estimate of the AI parts of all the other players) are valued at, say, ~6 - 7 trillion? Which seems like a fair approximation of how much knowledge work they can currently automate.
flyinglizard · · focus · HN ↗
iron_albatross · · focus · HN ↗
And then there’s the second order effect: if all the knowledge workers get automated, who is going to buy the stuff that’s produced?
credit_guy · · focus · HN ↗
Take the Hugging Face incident. Why did it happen? Because the people whose task was to set up a testing framework took shortcuts. Why did they? Because there weren't enough people who were assigned to do the job. Why not? Because the job is too new and not enough people are qualified to do it. It's a job that simply did not exist 3 years ago. But 3 years from now, this job might very well employ tens of thousands of high skill knowledge workers.
[1] <a href="https://en.wikipedia.org/wiki/Lump_of_labour_fallacy" rel="nofollow">https://en.wikipedia.org/wiki/Lump_of_labour_fallacy
jnwatson · · focus · HN ↗
iron_albatross · · focus · HN ↗
bluecheese452 · · focus · HN ↗
keeda · · focus · HN ↗
Unfortunately, I fear that may not be the most likely outcome. I've posted some comments on this before, but when I start thinking about how deeply everything will change once people figure out how to properly leverage AI, I see no outcome other than significant, widespread job losses.
As you indicated, at that point we will have much a bigger problem than the valuation of the AI industry. I'm not sure how it will get solved, I just know it will HAVE to be, because it would be an existential problem for everybody: people, governments, even the billionaires! Because now consider the 3rd order effects: if nobody can buy the stuff that's produced, how can billionaires get even richer? ;-)
zug_zug · · focus · HN ↗
What do you mean? The sum of ALL US salaries is $13.4 Trillion per year. According to google $65T is the sum of ALL salaries Globally (not just knowledge workers). It's not reasonable to assume AI is a drop-in-replacement for any job yet (perhaps bottom tier customer support from oversees?).
> So if their hypothetical revenues are double-digit trillions and valuations are some multiple of that
So you're sort of premising here than more than 16% or 1/6 of all the world's jobs get replaced by AI. Hopefully you can understand that's both not the current AI capability and also would be a terrible (unprecedented?) economic shock.
farrellm23 · · focus · HN ↗
zug_zug · · focus · HN ↗
There's no strong evidence that openAI or anthropic will have non-linear revenue growth, so I'm not sure what point you're trying to make. Unless you think they'll fire all their engineers and replace them with agents or something crazy?
keeda · · focus · HN ↗
Unfortunately, I do fear that AI adoption will go beyond augmentation to automation, and I do fear an economic shock. Just posted this down-thread: <a href="https://news.ycombinator.com/item?id=49722616">https://news.ycombinator.com/item?id=49722616
zug_zug · · focus · HN ↗
keeda · · focus · HN ↗
Assuming a 33% boost takes it to ~20T annually, which is technically "10s of trillions of dollars" in revenue. And these numbers are from before agentic tasks arrived on the scene, so the actual productivity boost and corresponding value to employers is likely even higher.
I'm not sure where the disconnect is?
zug_zug · · focus · HN ↗
I'm not really going to belabor this point more, because it really sounds to me like you haven't even done the most cursory exploration into this and the people who have give an estimate of 7-10%[1] (and only a small fraction of that value would be captured by the AI provider). All the best.
[1] <a href="https://www.goldmansachs.com/insights/articles/generative-ai-could-raise-global-gdp-by-7-percent?utm_source=chatgpt.com" rel="nofollow">https://www.goldmansachs.com/insights/articles/generative-ai...
keeda · · focus · HN ↗
Toggle "Work hours using genAI" and "Time savings due to genAI" so see what I mean. You can also toggle between various industries, which is eye-opening because even industries like "Agriculture, Forestry, Fishing, and Hunting" are seeing productivity gains!
And if you do not want to read the detailed paper, they have a follow-up article here: <a href="https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity" rel="nofollow">https://www.stlouisfed.org/on-the-economy/2025/feb/impact-ge...
Specific quote:
> Using our data on generative AI use, this estimate implies that, on average, workers are 33% more productive in each hour that they use generative AI. This estimate is in line with the average estimated productivity gain from several randomized experiments on generative AI usage.
What we HAVE seen is that the national labor productivity has gone up by 1.3% since ChatGPT was released, and it lines up very well with all the other data and studies they cover... AND your reference, which predicted a 1.5% growth back in 2023!
fittingopposite · · focus · HN ↗
Future supply and demand will set the price - not what is paid today. If supply by open models is vast and cheap, I can't see that the entire knowledge industry can hold the current size. It'll rather collapse to a fraction of its current value.
_ink_ · · focus · HN ↗
I don't think that AI companies can charge the same. The human workforce can charge these costs, because of scarcity. But AI systems won't be scarce, it's just a matter of who can run inference cheapest. Plus you still have the human workforce, which might be forced to offer their time for less money.
sgt101 · · focus · HN ↗
In one case (financial services) it's thought that expertise is valuable at V=S^2/b4 where V is value, S is skill and b capacity (the leverage available to the manager/expert. b erodes as it becomes harder to find examples of things that are not done well, so if you manage $1bn you might find lots of miss allocations that you can exploit with just that $1bn really effectively, but if you manage $10bn it's much harder to find good places for the extra $9bn. A low hanging fruit effect.
Anyway, that double hit - raw skill and the amount of times you can supply the skill makes the value of skill (V) convex, and it means that in a perfect market (heh heh heh) someone running $100bn is worth 1000's or maybe 10,000's of an average joe expert.
Now, if AI is trusted to run the top 0.1% of everything and has the skill to do it at human top level expertise, then your calc holds. If it's the case that it isn't then more than half of that value disappears. If it's not even top 1% then chop out another 25%.
That implies that we need a lot of trust and a lot of AI capability before these valuations stack up, and it also implies that all other competitors and incumbants are going away. I do not think that Citidal or Bridgewater are going to let Anthropic or OAI take them without a fight. They might lose - but there is a decent bet that they don't. I don't think that many professions like Lawyers or Doctors are just going to roll over and cede their monopoly rights to OAI or Anthropic either.
randyrand · · focus · HN ↗
You need to think in terms of supply and demand.
The demand is there, but the supply is also going to skyrocket. Free open weights models will contribute to supply too.
There will be a new equilibrium that’s hard to predict.
webern777 · · focus · HN ↗
That is the after the fact justification of the AGI dollar auction. Each round is kind of 3x the previous cost and neither can really stop because second place in the dollar auction is so much worse than winning.
The only way to stop the auction is one bidder hits a hard budget constraint, both agree to stop, or an outside party breaks the auction.
IMO this is why they want to slow down or have regulation. I think this is also why we see some claims of already reaching "AGI".
The TAM of global knowledge work is just a narrative tacked on after the fact to justify the AGI dollar auction.
The economic fallacy here with the actual valuation is akin to pricing the electric utilities 120+ years ago as some % of the future cash flow of global food production. Take the TAM of global food production and then work back to what % will the electric utilities capture from the advances in the automation of farming? It is nonsense.
The only narrative that actually justifies the capex spend that I can figure out is a first mover AGI monopoly. Even the oligopoly case is hard to justify the capex spend IMO. There is this enormous mismatch between the AGI monopoly and the actual rolling 12-month window of pricing power.
Even the rolling 12-month window of pricing power is going to saturate well before AGI too so it is hard to see how any of this makes economic sense.
keeda · · focus · HN ↗
FWIW even without AGI there are indications that all this CapEx spend, even with very shallow adoption, is boosting national labor productivity by 1.3%. That is worth ~$123B based on total wages paid in the US alone: <a href="https://news.ycombinator.com/item?id=49721338">https://news.ycombinator.com/item?id=49721338
As such I don't see the need for AGI for any of this to be financially viable. Whether it is economically and socially viable... that's where I have grave doubts.
But Capitalism really only focuses on the former and not the latter, which is why this will keep getting pushed forward. And that is the crux of the problem.
danpalmer · · focus · HN ↗
This assumes you don't change the market, but at the scale of (checks notes...) "all knowledge work", that just doesn't hold.
For example if you put 1bn people out of work, you now need some sort of safety net to bail out much of that workforce, a truly unprecedented change. You also lose tens of trillions of dollars of tax revenue.
One solution might be to recoup that cost and lost tax revenue from businesses by raising corporation tax. If corporation tax went from low tens of percent to high tens of percent, would those businesses be able to afford all that AI? No. Same order of magnitude? I doubt it.
There are many possible futures there, but the simplification made in the parent comment is completely unrealistic. The article is right in calling out the valuations as crazy.
AureliusMA · · focus · HN ↗
keeda · · focus · HN ↗
However, I fear reality will be much hairier.
AureliusMA · · focus · HN ↗
bluecheese452 · · focus · HN ↗