It's been almost half a year since we got powerful enough models, and I'm wondering, where are all those great things that were created with them? Maybe it's just me, but nothing has changed in my life so far. No improvements, but definitely, I need to be more careful when reading, listening, watching, and using things, as bad quality slowly creeps everywhere.
We have replaced multiple 100k contracts from SaaS vendors with fully AI created alternatives. AI is a tool. In the hands of talented and efficient workplaces, it is like any tool. But, if you give the latest DeWalt OMT to a person who doesn't know or is scared of it, and put them in an organization that is full of politics and bureaucracy, then that tool is going to look useless.
I'm seeing a ton of niche apps being built that otherwise wouldn't have been. As an example, NegPy is an app that gives you much more precise control when working with film negatives, and has been built largely w/ AI tools. There are a small couple of other photography related niche apps I've seen taking off, for example, for managing your Fuji recipes. I'm working on a Lightroom replacement myself, which I never would've taken on before AI tools.
In terms of personal life, I certainly find AI tools pretty useful especially given how awful Google is now, and coding tools are indispensable at work.
You’re all confirming the point by quoting niche examples of things that wouldn’t sustain a million dollar a year market, let alone contribute to a 6 trillion dollar one.
You explained the problem brilliantly.
Frontier models are great at making you tinker and come up with shit you wouldn’t have done because there is zero value in it and you would have had to bet a value N (time, money) to obtain before this investors-subsidized almost-free software existed.
This is deluding individuals and CEOs and everyone who seems incapable to abstract from the sycophantic personal experience into systemic thinking.
To be fair, LLMs have been engineered to give this illusion, so the fault lies with the grifters controlling them.
Now are there useful applications of these tools (not gods) that might justify a sizeable new tech market?
Absolutely yes!
Is that market ever be going to be worth trillions a year? LOL hell no.
I'm de-FAANG-ing my life. One AI subscription can do the lift of a lot of other subscriptions when it comes to putting OSS tools on my homelab, and I truly don't need _everything_ when I'm on the go.
I remember making a comment here on HN a couple weeks ago.[0]
One of the things that was promised in 2024 was a "deflationary spiral" for physical goods and the economy in general because of insane efficiencies that AI would supposedly bring. I believed that whole-heartedly and I was a huge AI fanboi even as my artists friends and Lib Arts friends were complaining.
We're in almost October 2026 now and they're nowhere in sight. We have a bunch of unreliable agents that do clerical and design work here and there, but where are all the industrial productivity boosts? If AI were so good, large industries and factories should be adopting them as a never-before-seen scale. Where are they?
It's actually is an interesting point. On personal level I've built a few products but I did spend a ton of time exploring things I was really curious about that will never amount to anything practical beyond satisfying my curiosity.
Most big companies are performance theaters see token maxxing as one prominent example.
But go and talk to small companies. What they are able to pull off is just incredible. More features in shorter time. Improved UX and client satisfaction.
On a society level 6 months is nothing. This will take about 10 years to penetrate all organizations I assume.
I just invented a simple upgrade script for my father's ancient Fedora install. I've gone from version 33 to the latest(44) with a simple utility I one shot in 5 minutes.
Since Fedora moves old releases to some mirror it's a nightmare to update old installs.
Now I did it very conveniently.
Did I build a space ship with the help of ChatGPT? No.
Is it useful to me? Yes.
I'm doing many much cooler things that I haven't released yet but I am launching projects I never dreamed I could do as a solo dev in 2-3 months.
I did some projects, but there are some things that I don't like. For example, when I wrote a program for my old ThinkPad, I didn't only create a useful utility for myself, but also learned and practiced Qt/C++. Now, I don't learn anything new, nor do I practice my skills when I "create" something. Maybe, the things I'm learning are how to prompt LLMs, add necessary skill files, and so on.
I've been working on my project, a paid mobile app, for five months now.
I'm pretty confident I can release it in October, after some 500 hours of work.
Usually in these discussions I get "so it has zero users then".
One time someone on here told me that for AI to prove its worth for software engineering, my application would need to be in use already for at least ten years.
I run my own custom version of BlueBubbles and a locally run clone of Wispr Flow.
In addition, I've vibe-coded lots of nonsense throwaway apps that helped me with a one time boring task.
The responses you’re getting are quite telling. LLMs have unlocked a whirlwind of shit where we can no longer trust most things, communities are suffering with noise, lack of water, increased energy prices, mass surveillance is rapidly increasing, private information is being leaked and sold…
But hey, you can now close yourself off even more, not interact with anyone or develop a skill to get a dumb bash script for a menial task you wouldn’t miss that much anyway if you didn’t have it. Woopie, totally worth it!
I think what's lost on the general public who mainly thinks AI is ChatGPT, is that these companies are gunning for knowledge worker salaries. That by itself is ~$30T/year globally. Nothing else justifies the infra spend. Data center investment is a bet that they will be able to virtualize knowledge workers in the next 5 years.
Warehouse and factory labor is the next largest market for AI/robotics, at about $7T/year globally.
The bubble question is really about the target year. Will these companies start on a trajectory where AI begins eating these massive markets before investors lose faith?
To me it looks like one of these is true:
(1) this is indeed a bubble, and AI will turn into a useful tool integrated into everything but fall short of expectations. We'll see some significant multiple compression in the share prices of these core AI companies, but they'll remain good investments in the long term.
(2) this is a real transformation, the investment was worth it, and these companies will earn massive revenue while causing Depression-era levels of unemployment (24% if half of knowledge workers and factory/warehouse workers can get jobs).
Basically, the revenue required to justify the infra spend requires that they start eating existing industries, because that's certainly not going to come from ChatGPT/Claude subscriptions.
They talk a bit about where the AI companies are supposed to get their revenue from. I’d like to see these analyses go a step further and talk about how those AI customers are supposed to come up with that money as well.
For example, the article suggests $1T from enterprise productivity tooling. A quick Google suggests the global enterprise productivity tooling market is only worth about $0.1T right now.
Do we really expect all the world’s corporations to suddenly up their annual spend by 1,000% on average? Why?
Keep in mind wealth is not a fixed thing. If AI makes their businesses more productive, it would allow the creation of more wealth, giving them more money to pay for AI with.
This of course hinges on the big if: does AI create wealth? I think yes, but maybe not $6 trillion of it in five years.
> This of course hinges on the big if: does AI create wealth? I think yes, but maybe not $6 trillion of it in five years.
There is also the question of time scale. Growing a market takes time. Assuming the numbers above are the right order of magnitude, we are not going from 0.1 to 1 in a year. So even if the number would make sense over longer time frames, it can still be unsustainable for a significant amount of time before that.
Like the Internet at the end if the 1990s, basically.
At a time when corporate CEOs are largely saying that they can't see that AI has improved office productivity at all, why should we believe that a killer productivity application of genai that's amazing enough to justify an order of magnitude increase in enterprise spending on productivity tools is just around the corner?
Maybe they are speeding up things that were not the bottleneck or don't matter. Or LLMs speed up the time to learn, "well this idea probably sucks actually", which is great, but in the end there is still no good idea. For software dev, it had already gotten pretty efficient before LLMs came around - the business of making software demanded it. There are still gains to be had no doubt, but many will have less impact.
I'm using claude to make gaming mod apps I never would have bothered to code before, but they have zero monetizable value. There is demand for sure, but somewhat ironically, copyright/IP/TOS law stands in the way. The thing which committed the biggest copyright infringement in human history lets me make another thing which I can't release because of copyright law. I'd get cease-and-desisted instantly if I did so.
The latest BCG report I saw on this was the one from this summer that found that employees are saying they're saving time, but businesses still haven't figured out how to turn that into dollars.
And employees self-reporting that they saved time doesn't necessarily mean they actually save time. Humans are famously crap at estimating that sort of thing.
But does crazy speedup of tasks actually yield more productivity? Or does it yield greater numbers of pointless tasks?
Anecdotally, I've seen management using AI to produce more and more flashy looking dashboards and interactive displays of various metrics. Will this help our bottom line?
I think you are mixin wealth with money. In the short run it is a near zero sum game: money should go from A (now obsolete) to B. For example, brick and mortar shops replaced by online shops. For example horse business going bankrupt while car business is booming. Wealth is created in the form of more convenient shopping or travelling, not as $$$. AI might help some businesses with their productivity (creating new wealth), but those business are expected to divert $6T from current expenses (wages, or non AI tooling) towards AI pockets, or steal $6T market share from non-AI business.
>For example horse business going bankrupt while car business is booming.
But also the car business is far larger than the horse business ever was. It is not zero-sum; every time Henry Ford's factory spit out a new model T, real wealth was being created.
Money is just a standin for wealth. If we suddenly doubled the amount of wealth in the world, we could just print more dollars to match - or the existing dollars would just become worth twice as much.
Indeed, although there are also pressures pushing banks to lend out money regardless of created wealth. This is why there's so much investment into stupid things like AI - they call it TINA or "There Is No Alternative" (to put your dollars into). The scale of AI is as big as it is because there were huge pools of money sloshing around looking for things to invest into, that's the underlying problem that caused the RAM crisis, not AI itself.
More productivity might translate into more revenue, but more productivity doesn't necessarily create more wealth.
For example, if I'm a landlord that uses AI to more intelligently price rental increases to maximize profit without attrition, I have created more revenue but not more wealth.
Indeed, it is hard to say exactly how much wealth the internet creates, but it's a lot. E-commerce alone is $30 trillion industry; some estimates put the total economic value of the internet at $200 trillion or higher.
That said, this came too late for investors in the dot-com boom. AI investors may find themselves in a similar situation.
And, perhaps more to this particular point, it came too late for vendors behind the dotcom boom. Lucent Technologies no longer exists. WorldCom no longer exists. Cisco is a shadow of its former self, with a stock price that only recovered last year.
The dotcom bubble burst because the development of the internet could not keep up with expectations, even though investors were correct in principle with their assumption it would generate swaths of wealth. For AI the hope is that AI itself will start to push its own development and adoption sooner rather than later, so the timing issue that killed dotcom investors might instead make AI investors insanely rich. That's why we're still seeing heaps of money getting dumped into it.
It isn't exactly not a zero sum game either though. If you want to sell something you have to have willing buyers with either funds on hand or sufficient credit to make the purchase. So yeah that 6T gotta come from somewhere.
Customers coming up with it is basically fine*, but it's also why the SpaceX IPO chose to use "TAM" as a big number to dangle before investors: if you can do the work of {$6T + markup}/year worth of desk jobs, that's your customers.
However, customers coming up with the money is the easy half of the problem. The hard part is having them pay you.
Wikipedia's valuation is on the small side of {number of people on the internet worldwide} * {peak price of Encyclopaedia Britannica} † despite containing a lot more content.
LLMs can only chase high margins while they're ahead of their competitors; the moment the investment stalls, open weighs catch up, they loose their edge. Cloud compute providers still win on supplying inference, but there too competition will likely lower margins, not justify huge valuations.
NVIDIA may remain as valuable as today, but their P/E ratio will likely shrink a lot even while keeping up the price.
Model makers still have a problem here even if the tech is so useful it rapidly grows the economy: "free" is right behind them almost immediately after they stop.
* under the assumption the tech is real; there's plenty of people here on Hacker News who still dismiss it as a "scam"
† that would be about 13 trillion USD, from what I read
From other business owners. If this hypothesis is true, they're saying the share of wealth controlled by labour goes dramatically down, and the share of wealth controlled by capital goes dramatically up. So most of your revenue will come from capital holders instead of labourers.
1) This would make stocks worth a lot more and produce more dividends so everyone owning stock would get money to spend.
2) Governments effectively indirectly own ~40% of all business profits via corporate taxes, capital gains taxes, dividend taxes, sales taxes. So governments would also have more revenues to spend/redistribute (this depends on governments not wasting it, spending it on wars etc.)
#1 is still mostly just moving money from the poor to the rich. Most people working for a wage are going to be in the bottom 80%, yet the top 20% own over 80% of the stocks.
All money is a merry-go-round when you get down to it.
That doesn't mean the wheels won't fall off, they fall off pretty regularly as is.
The difference between this loop and the previous loops, is that people making the tech used to be pretty straightforward ("invest in me, your money will let me make a machine that lets me fire 90% of my peasants and we can share in the savings"), while today they're all "invest in me, either this will kill everyone or just make the concept of money irrelevant, either way rotflmao".
The historical precedent is those people get other jobs, and/or everyone else in the economy gets richer faster than they get poorer.
If this does or doesn't happen with AI kinda depends how fast it makes multiple different sections of the population unemployed, rather than just one group like "software developer" or "vehicle driver".
That's very much not what happened in the Industrial Revolution. Hand weavers were relatively well-paid, and the new factories were more likely to employ the urban poor - including kids - than to give jobs to people who used to be hand weavers.
It took maybe a century and a half for the modern consumer economy to appear. And it didn't happen until money started being shared into the wider economy for political reasons, not technological ones.
Meanwhile the enclosure of common land was catastrophic for rural populations. Sources of food and pasture disappeared as the Big Houses took them over and turned them into huge single family estates.
> The historical precedent is those people get other jobs
Heh, got fired from my old company for reasons not connected to AI. Then couldn't find job. AI suggested one that is perfect for me, helped me put up webpage (I can do everything from electronics/firmware/backend/iot/cad, but nice webpage is not something I can do easily), then helps me every day to learn new things and make useful products I always wanted to make. And I found something safe for now from AI and big companies - making old equipment work with new systems. No one will touch it, because you have only small projects here and can't extract a lot of value at once, but a single person who can do anything with some help from AI can carve out a whole niche.
I think such solution - thousands of small niches by small entrepreneurs (1 person companies) who can use AI for some small skill they are lacking - are our future and they will absolutely extract a lot of money from people, who hope to make some more money with small optimisations of already working businesses. One example of such small optimisation - making a slightly better wood drying controller for small woodmill owner. He already put up small cabinet with cheap tuya controllers and needs to control them though atrocious app. Now I can make a small module that will add several more sensors, give him some simple dedicated control panel on webpage. Not even medium company would make such small product, because planning phase alone would cost more than what I can charge for whole system and do it in a week.
And it all started with one prompt - "Given my CV, what single person job would you recommend?"
"Do we really expect all the world’s corporations to suddenly up their annual spend by 1,000% on average? Why?" Because they will replace people with tools I am guessing?
Ultimately I think they’re looking at the taxpayers to bail them out of this bubble. Everyone knows they over invested, no one wants to admit it because they’ll lose money.
you might make a hypothesis they'd offset operations costs like headcount for this but I think the counterpoint is stronger, if they benefit from increased productivity in your example, why not run more net production from same input.
Still though, the thesis seems based on an assumption that the companies would experience either major growth or major efficiency gain, neither of which really pass the smell test to me. Option 1 growth - money has to come from somewhere ultimately? Option 2 efficiency - put into profit rather than simple offset to AI provider?
Or the AI providers get companies hooked with subsidized pricing that unwinds later and you end up with the Uber/AirBNB situation of market capture and good product reverting to mean level of price/quality over time. Tinfoil hat thinks it ultimately gets squeezed out of retail investors in index funds.
What does this mean? I've been using AI as a replacement for both of those for longer than a year. If I need a PowerPoint file I have it generated off my tooling. Instead of fiddling to align text you say update slide 6 to look like this, strike this sentence. And you can add even more dynamic content. Like live application dashboards connected to real sources.
You can personally do that but I don't see how having ChatGPT means mass uninstalls of excel occur in enterprise. AI using PowerPoint doesn't mean powerpoint got replaced right.
LLMs can use PowerPoint, but also LLMs can write the raw document file directly without the software. One time I asked for a letter and what came out was it doing that.
What really matters with this though is reading other people's documents, whatever format they happen to be in. PowerPoint isn't the only game in town for creating slide decks, but if you want to be sure you can read all the ones sent to you, it used to be the case you'd need a copy.
Used to be. Now the AI can read and summarise the slides for you.
("AI, expand these bullet points into a slide deck" -> "AI, condense this slide deck into bullet points", as the meme goes).
If there are no humans looking at the excel anymore, why is it needed? My guess is all of this office software gets replaced by stuff that looks a lot more low level and controlled by agents, and just converted to a nice view when a human wants to look for some reason.
Agreed. The literal CEOs of these companies, and their acolytes, have been proudly proclaiming that you can replace all types of workers with AI. We know they have their anti-human sentiments but this is nothing new, as you said.
I think we've barely scratched the surface of available 'evil' applications for AI that will be immensely powerful. Building, for example, an application capable of building personalized emotionally targeted advertisements based on a user profile would be incredibly effective and probably expensive but I bet it would pay dividends.
it seems fairly obvious to me that once ai becomes as good as a worker, people will pay a workers wages to use it - 24/7, can't quit, can't complain that badly, no lunch breaks
So we're talking about the complete destruction of the consumer economy.
Hard to see how Google or Facebook keeps their advertising models in that environment. There aren't enough construction workers and data scientists to buy everything.
I truly don't think anyone serious believes that, but if they pretend to believe it and preach it aggressively they might make out with an historic payday and stick the rest of us with the bill. People did the same with Crypto, with NFT's, with a bunch of things for as long as the ball is rolling.
Even if they were right... they don't really understand mass unemployment of that scale, right? Hungry people with a lot of time on their hands are known to get particularly inventive to entertain those who own too much.
AI is the second Industrial Revolution! You cannot use outdated notions. The nature of work and value creation itself is changing. Those who do not embrace AI will be left behind. Soon AI will accelerate in its ability to self-improve resulting in general artificial intelligence. This will result in not just our economy reaching the next level but will illuminate the very nature of knowledge and existence. We will ascend becoming beings made of pure energy.
I have an obvious but different perspective on the article...
Currently, hyperscalers are growing revenues at an impressive annual rate (~20%), which comfortably covers current annual CapEx. While traditional cloud services still drive a large share of this growth, AI services are becoming an increasingly material contributor. So far, so good.
However, the real question is whether a market actually exists to sustain this CapEx spending at scale relative to revenue growth. The current CapEx growth rate (~50%+ year-over-year) has already outstripped revenue growth, and no one truly knows where the trillions in required future revenue will come from.
If this projected revenue growth fails to materialize, tech equities face severe re-rating risk, given that current stock valuations have already priced in these best-case expectations. A market crash unless a real market is discovered.
In summary, nothing new—perhaps just another red flag.
To put this into perspective, healthcare, real estate and banking each earn ~$1.5T in revenue annually. This is REVENUE, not profit which is obviously lower than the revenue in every industry. I fail to understand how AI can achieve $6T in annual revenue when the TAM for healthcare and banking is a quarter of that in the US.
The article says $6T by 2031 and it's global spending, not just in the US.
> Bain forecasts that annual spending on AI infrastructure might hit $1.5 trillion by 2031.
So maybe in 5yrs it will need enough revenue to cover $1.5T in capex spend globally in a year, investments which as the article mentions is also being supported by governments in "the UAE, Saudi Arabia, the EU, South Korea and the US". ... Or spending growth could lower over the next couple years to be more realistic.
I think their claim they can make, assuming their evidence is true, is
"AI needs $6T in annual revenue for every investment in AI to be profitable"
I think some people will make a lot of money and more people will lose a lot of money.
Most of those investing know this, they are taking the risk of losing a lot to attempt to be one of the ones that make a lot.
A lot of early internet tech companies went bust, a few became extremely successful. At the time I would see high valuations and ask "Yes, but how do they make money". Most of those with an unclear answer to that question are not around now. The ones who had a tangible plan to make money, even if they were making a loss at the time, tended to survive.
There is a lot of Dumb money going into AI, when that is the dumb money of wealthy individuals, I am more than happy to let them receive no return while paying for infrastructure. There's a problem when the dumb money comes from dumb individuals who are routing money from others who do not have a say in how it gets invested.
That is not an AI specific problem, that is a problem where people can make decisions where others carry the risk without their consent. That is the problem that needs to be met head on.
This is like sitting in 1997, confidently assuming all future Internet services would run on one of Sun, Compaq/HP, DEC, or SGI, and projecting costs accordingly.
Then again, investments in AI are 1-2 % of worldwide GDP I think, if you think that this technology can probably increase efficiency at least a couple of times in anything that has to do with information processing it doesn't seem so ridiculous. The electric grid, railroads and other large-scale infrastructure required similar amount of investments, though they took much longer. I guess the main risk here is the speed at which everyone races to capture this market as unlike electricity or railroads this revolution is entirely digital so competition happens nearly on a global scale and everything is much faster. That is probably the main risk, going this fast will definitely cause overshoots in one or the other direction.
> forecasts that annual spending on AI infrastructure might hit $1.5 trillion by 2031.
> ...
> sustaining this level of investment would require an AI market approaching $6 trillion annually
This is a 2031 projection of a 6T market, but somehow the article editorializes this into 'justifying' a boom?
That segment would include innovations in search, advertising, autonomy and physical AI, analysts at Boston-based Bain said.
Consumer-focused services, which includes subscriptions and advertising revenue, is seen to contribute $200 billion to $400 billion
So not $6T of ARR subscription sales, but $6T of "economic enablement". By 2031, the global economy is estimated to add another $40T of economic activity to GDP. So AI needs to account for 15% of that.
To avoid this becoming a “tail wags the dog” scenario, folks who have money would need to spend it. We told people for 20 years to “learn to code”. Technology is, outside of healthcare, the leading profession for upward economic mobility.
What happens when the adoption of AI destroys the middle 60% of the bell curve of programmers and technologists? How will the middle class of people spend money on products/services if they don’t have a job?
We can’t both create wealth and destroy jobs with nothing to replace them.
America has little to no manufacturing base.
Technology and finance has been its differentiator economically speaking for job creation. Both are at risk from AI adoption. Businesses have to sell to someone, and at the moment it’s not clear — if the stated goals of revenue are to be believed, how that can happen.
Same thing that happened to blue collar work witch used to be the path to the middle class before the 1990s. The economy managed to create plenty of wealth without doing anything for 40% of the population.
I can't think of any use case for AI that is a necessity for myself (or people I know), even if coding agents (which I use every day) disappeared tomorrow it would only be a minor inconvenience that I had to write my own code again. Now lets contrast that with electricity or internet, if either of those went offline I would be on a call trying to get them restored asap, now as far as I know neither of those industries bring in $6T in revenue.
If agentic coding isn't dramatically changing your productivity you're getting left behind. There's a clear difference between vibe coding and AI assisted software / systems engineering from how I think about things. With AI you can be massively more productive. I do a lot of things beyond code and this is what I've built in 2026 (quick snip from scc, it has proper excludes for node_modules and other pulled in deps that I didn't build) from ~code/ on my dev box:
Zitron has been talking about this for some months now. The numbers fluctuate, I think $6T is the highest I've seen but low-end is about $1T that doesn't exist today.
An issue is that if you’d have believed him two years ago and taken your money out of the market or even shorted it, you’d have lost money over and over again while he’s continued to pipe exactly the same tune.
“Being right at the wrong time is as good as being wrong” - Howard Marx
I don’t think Zitron is recommending anyone short anything. That’s carries a ton of risk.
What you consider “losing money” I might consider “choosing not to participate in an ongoing global financial scam at the cost of my retirement growing slightly slower for a while”.
I wish people would realize that Zitron is nothing but a grifter who saw an avenue for content and went all in.
I don’t even disagree with some or even a lot of his takes, it’s just he is singularly a content generator with a track to run on. Look at his previous work, it’s much of the same kind of attempts at being relevant.
To me he’s nothing more than a drive time radio host, shouting about something just to fill the air
I think Zitron's biggest mistake is making too many concrete and confident assertions without enough backup. Yet the AI safety doomers have basically never been right either, but nobody seems to mind that; clearly they'll be right when they're right, just wait for it?
Just for fun, I'll join in myself and make two bold half-hearted predictions that will surely be wrong:
- Zitron is wrong about the details, but right about the ultimate fate of the AI companies. Turns out AI is useful after all, it just isn't able to justify trillions of dollars in expenses. Shit falls through hard. Probably not an AI winter, but more like the dotcom bubble, as many have already predicted for years. Everything looks rosey right up until the first domino falls.
- The AI safety doomers are right, just not any time soon. Turns out our depth of understanding what intelligence really means was severely lacking; it's hard to quantify and we never had so many things testing it. Eventually, we really do discover why LLMs emergent capabilities really are inherently limited in ways that just make their ability to meaningfully "escape" less scary, and maybe architectures emerge without these limitations, just not yet. The fight with LLMs and malicious use winds up looking a lot more like a supercharged version of the current fights we have with dumber bots. Everyone winds up having to fight LLMs with LLMs, and this new world eventually pushes both good and bad new legislation in its wake, finally actually pushing responsibility for AI misfires, but probably in a way that is at least as bad as it is good, creating chilling effects and harming competition unnecessarily, because that's just how things go. Maybe we eventually do crack true super intelligence where it's a full superset of human mental facilities, and then geopolitics maybe gets as interesting as it ever has been in history. Probably not in a way that is fun for people living through it.
I can't blame Zitron. It's fun to pretend to be able to predict the future. I still broadly agree that the financials don't really seem to make that much sense even if he clearly keeps getting the details wrong.
> Yet the AI safety doomers have basically never been right either, but nobody seems to mind that;
I don't think that nobody seems to mind that. Pro-AI people make fun of doomers because of their failed predictions of apocalypse at least since GPT-2 days.
I kinda hope corpos with a bunch of money and plenty of normies adopt AI so developers don't get bled (as) dry, esp. given the recent OpenAI changes which I feel like Anthropic is soon to follow.
Edit: explanation of the downvotes would be nice. Dan Luu made a fairly factual article there that explores some of Zitron's claims. And personally I don't see how it's bad to wish for wider adoption of AI so the big orgs get their fill of profit (since enough inference could help fund R&D better) and developers don't have to bear that burden.
Yeah the Dan Luu post was very convincing. People want to believe what Zitron's story is (which I do think there is some truth to) but the facts Zitron uses fail to support the story to the degree of the claims.
I'm fairly confident that the crash will happen because token prices fall through the floor due to competition from the open source models. This will destroy the valuation of the AI firms and their ability to raise capital, so they'll stop spending hundreds of billions per annum on training.
OTOH, this price crash will increase demand for inference. Maybe some data centres will go bankrupt, but the scavengers won't be selling off used TPU's for cheap, they'll operate those data centers to sell you tokens for cheap.
Such an interesting dilemma. Arguably an incredibly transformative new industry for which the market cannot fundamentally bear the costs. (or IDK, does it actually work now?) How will it play out??
I don't care how good AI is at something like software development or whatever task. If customers were paying real prices for usage would any of us be using it?
Any data out there on how far off enterprise API pricing is from actual compute COGS for these models right now?
What's total US annual payrolls? I don't think it's beyond the order of $20 trillion. So they're going to have to replace something on the order of magnitude of half of all jobs OR "create" the difference, in terms of jobs going to AI.
3. This is not $6T of ChatGPT subscription revenue. The article actually specifically says of the $6T, $200-$400B would be subscription and AI app revenue in 2031.
4. The $6T figure is AI "economic enablement". Drugs, robotics, research, coding, manufacturing, materials, etc...
It's less* than that, and if AI replaces workers at that scale it will create such a problem* the system would fall before these companies manage to demonstrate they escaped bankruptcy.
Not going to happen, but also not every company will "win" so all of this revenue doesn't need to be recouped, just the revenue of the market leader/leaders.
The high end sectors using these servers are paying way more than joe consumer and his 30 bux a month. We are already seeing justification for the boom, and I'd expect even more advancements to come in multiple sectors. That number is missing from the article.
Boomers will stop paying for enterprise once it stops being cool
Chatgptd emails are not adding value anywhere
Very few professions if any get anything remotely like the value coders get from LLMs right now
Maybe lawyers or doctors but it's just way too risky error wise
A comma off in a legal doc can end your career
it does seem a lot like the whole AI thing is the market staying irrational a lot longer than the naysayers can afford not to go along with it, but still, nobody can stay irrational forever.
It's clearly a bubble. I'm not sure why more people don't describe it that way. It's a gold rush. People are hoping that everyone else drops out before they do. Nobody thinks all the participants can win. At best one of them can take a small fraction of $6T.
Except that it would be priced based on pass-through prices rather than existing value perception. It used to cost hundreds to send a letter on horseback, it costs pennies to send an email, consumers aren't going to tolerate spending hundreds when they know it take pennies to send.
Models are getting cheaper, and more efficient, but I don't see how they cross the threshold of full autonomous intelligence in the way that an employee needs to be fully accountable for their actions.
In terms of personal life, I certainly find AI tools pretty useful especially given how awful Google is now, and coding tools are indispensable at work.
But taking those bespoke contraptions to market is not something I want to out effort into. Especially when anyone can just clone it with AI.
The AI revolution might not show up so easily in GDP.
Now are there useful applications of these tools (not gods) that might justify a sizeable new tech market? Absolutely yes! Is that market ever be going to be worth trillions a year? LOL hell no.
So where is the value? Have you built that one application you always wished existed but it wasn't available?
One of the things that was promised in 2024 was a "deflationary spiral" for physical goods and the economy in general because of insane efficiencies that AI would supposedly bring. I believed that whole-heartedly and I was a huge AI fanboi even as my artists friends and Lib Arts friends were complaining.
We're in almost October 2026 now and they're nowhere in sight. We have a bunch of unreliable agents that do clerical and design work here and there, but where are all the industrial productivity boosts? If AI were so good, large industries and factories should be adopting them as a never-before-seen scale. Where are they?
[0] https://news.ycombinator.com/item?id=49735506
But go and talk to small companies. What they are able to pull off is just incredible. More features in shorter time. Improved UX and client satisfaction.
On a society level 6 months is nothing. This will take about 10 years to penetrate all organizations I assume.
Since Fedora moves old releases to some mirror it's a nightmare to update old installs.
Now I did it very conveniently. Did I build a space ship with the help of ChatGPT? No. Is it useful to me? Yes.
I'm doing many much cooler things that I haven't released yet but I am launching projects I never dreamed I could do as a solo dev in 2-3 months.
I'm pretty confident I can release it in October, after some 500 hours of work.
Usually in these discussions I get "so it has zero users then".
One time someone on here told me that for AI to prove its worth for software engineering, my application would need to be in use already for at least ten years.
Wouldn't have been possible.
But hey, you can now close yourself off even more, not interact with anyone or develop a skill to get a dumb bash script for a menial task you wouldn’t miss that much anyway if you didn’t have it. Woopie, totally worth it!
Warehouse and factory labor is the next largest market for AI/robotics, at about $7T/year globally.
The bubble question is really about the target year. Will these companies start on a trajectory where AI begins eating these massive markets before investors lose faith?
To me it looks like one of these is true:
(1) this is indeed a bubble, and AI will turn into a useful tool integrated into everything but fall short of expectations. We'll see some significant multiple compression in the share prices of these core AI companies, but they'll remain good investments in the long term.
(2) this is a real transformation, the investment was worth it, and these companies will earn massive revenue while causing Depression-era levels of unemployment (24% if half of knowledge workers and factory/warehouse workers can get jobs).
Basically, the revenue required to justify the infra spend requires that they start eating existing industries, because that's certainly not going to come from ChatGPT/Claude subscriptions.
For example, the article suggests $1T from enterprise productivity tooling. A quick Google suggests the global enterprise productivity tooling market is only worth about $0.1T right now.
Do we really expect all the world’s corporations to suddenly up their annual spend by 1,000% on average? Why?
This of course hinges on the big if: does AI create wealth? I think yes, but maybe not $6 trillion of it in five years.
There is also the question of time scale. Growing a market takes time. Assuming the numbers above are the right order of magnitude, we are not going from 0.1 to 1 in a year. So even if the number would make sense over longer time frames, it can still be unsustainable for a significant amount of time before that.
Like the Internet at the end if the 1990s, basically.
At a time when corporate CEOs are largely saying that they can't see that AI has improved office productivity at all, why should we believe that a killer productivity application of genai that's amazing enough to justify an order of magnitude increase in enterprise spending on productivity tools is just around the corner?
I think CEOs could honestly say it a year ago, but by now the numbers of those who say so should be dwindling.
Recent surveys by BCG and others suggest things have changed.
Personally, I know many people in different fields who’ve seen crazy speed ups in many of their tasks.
I'm using claude to make gaming mod apps I never would have bothered to code before, but they have zero monetizable value. There is demand for sure, but somewhat ironically, copyright/IP/TOS law stands in the way. The thing which committed the biggest copyright infringement in human history lets me make another thing which I can't release because of copyright law. I'd get cease-and-desisted instantly if I did so.
And employees self-reporting that they saved time doesn't necessarily mean they actually save time. Humans are famously crap at estimating that sort of thing.
Anecdotally, I've seen management using AI to produce more and more flashy looking dashboards and interactive displays of various metrics. Will this help our bottom line?
But also the car business is far larger than the horse business ever was. It is not zero-sum; every time Henry Ford's factory spit out a new model T, real wealth was being created.
Money is just a standin for wealth. If we suddenly doubled the amount of wealth in the world, we could just print more dollars to match - or the existing dollars would just become worth twice as much.
For example, if I'm a landlord that uses AI to more intelligently price rental increases to maximize profit without attrition, I have created more revenue but not more wealth.
Play positive sum games.
That said, this came too late for investors in the dot-com boom. AI investors may find themselves in a similar situation.
However, customers coming up with the money is the easy half of the problem. The hard part is having them pay you.
Wikipedia's valuation is on the small side of {number of people on the internet worldwide} * {peak price of Encyclopaedia Britannica} † despite containing a lot more content.
LLMs can only chase high margins while they're ahead of their competitors; the moment the investment stalls, open weighs catch up, they loose their edge. Cloud compute providers still win on supplying inference, but there too competition will likely lower margins, not justify huge valuations.
NVIDIA may remain as valuable as today, but their P/E ratio will likely shrink a lot even while keeping up the price.
Model makers still have a problem here even if the tech is so useful it rapidly grows the economy: "free" is right behind them almost immediately after they stop.
* under the assumption the tech is real; there's plenty of people here on Hacker News who still dismiss it as a "scam"
† that would be about 13 trillion USD, from what I read
If they keep replacing employees with AI, that is indeed the direction.
Eventually this merry-go-round runs into some issues if we don’t figure out a way to make this huge productivity boom work.
1) This would make stocks worth a lot more and produce more dividends so everyone owning stock would get money to spend.
2) Governments effectively indirectly own ~40% of all business profits via corporate taxes, capital gains taxes, dividend taxes, sales taxes. So governments would also have more revenues to spend/redistribute (this depends on governments not wasting it, spending it on wars etc.)
That doesn't mean the wheels won't fall off, they fall off pretty regularly as is.
The difference between this loop and the previous loops, is that people making the tech used to be pretty straightforward ("invest in me, your money will let me make a machine that lets me fire 90% of my peasants and we can share in the savings"), while today they're all "invest in me, either this will kill everyone or just make the concept of money irrelevant, either way rotflmao".
If this does or doesn't happen with AI kinda depends how fast it makes multiple different sections of the population unemployed, rather than just one group like "software developer" or "vehicle driver".
It took maybe a century and a half for the modern consumer economy to appear. And it didn't happen until money started being shared into the wider economy for political reasons, not technological ones.
Meanwhile the enclosure of common land was catastrophic for rural populations. Sources of food and pasture disappeared as the Big Houses took them over and turned them into huge single family estates.
Heh, got fired from my old company for reasons not connected to AI. Then couldn't find job. AI suggested one that is perfect for me, helped me put up webpage (I can do everything from electronics/firmware/backend/iot/cad, but nice webpage is not something I can do easily), then helps me every day to learn new things and make useful products I always wanted to make. And I found something safe for now from AI and big companies - making old equipment work with new systems. No one will touch it, because you have only small projects here and can't extract a lot of value at once, but a single person who can do anything with some help from AI can carve out a whole niche.
I think such solution - thousands of small niches by small entrepreneurs (1 person companies) who can use AI for some small skill they are lacking - are our future and they will absolutely extract a lot of money from people, who hope to make some more money with small optimisations of already working businesses. One example of such small optimisation - making a slightly better wood drying controller for small woodmill owner. He already put up small cabinet with cheap tuya controllers and needs to control them though atrocious app. Now I can make a small module that will add several more sensors, give him some simple dedicated control panel on webpage. Not even medium company would make such small product, because planning phase alone would cost more than what I can charge for whole system and do it in a week.
And it all started with one prompt - "Given my CV, what single person job would you recommend?"
Because spend on "enterprise productivity tooling" (or whatever category they want to place AI spend in) can now increasingly offset human labor cost.
Still though, the thesis seems based on an assumption that the companies would experience either major growth or major efficiency gain, neither of which really pass the smell test to me. Option 1 growth - money has to come from somewhere ultimately? Option 2 efficiency - put into profit rather than simple offset to AI provider?
Or the AI providers get companies hooked with subsidized pricing that unwinds later and you end up with the Uber/AirBNB situation of market capture and good product reverting to mean level of price/quality over time. Tinfoil hat thinks it ultimately gets squeezed out of retail investors in index funds.
A ~40% reduction in employee compensation to source 6T, globally, seems a little more plausible.
Clearly, I'm eliding a ton of complexity/nuance.
They already figured they would need trillions revenue. So they paint an economic where such amount is plausible.
AI is not a replacement for powerpoint and excel. You can't substitute those.
White collar worker salaries is ~$30T+ global.
LLMs can use PowerPoint, but also LLMs can write the raw document file directly without the software. One time I asked for a letter and what came out was it doing that.
What really matters with this though is reading other people's documents, whatever format they happen to be in. PowerPoint isn't the only game in town for creating slide decks, but if you want to be sure you can read all the ones sent to you, it used to be the case you'd need a copy.
Used to be. Now the AI can read and summarise the slides for you.
("AI, expand these bullet points into a slide deck" -> "AI, condense this slide deck into bullet points", as the meme goes).
I very much can.
That applies to most software.
This doesn't solve the problem of "Who gets paid now, and for what?" at all. If anything it makes it worse.
My point was that AI isn't some productivity software thing. The addressable market is white collar work that can be done on a computer.
You think its implausible for AI to replace some fraction of white collar workers? To me this is directionally exactly where this is heading?
productivity tooling replaces employees
Hard to see how Google or Facebook keeps their advertising models in that environment. There aren't enough construction workers and data scientists to buy everything.
which yes, will completely destroy the consumer economy and social structures and current forms of governance
Who re these people?
because AI is gonna make them so much more productive of course. /s
Currently, hyperscalers are growing revenues at an impressive annual rate (~20%), which comfortably covers current annual CapEx. While traditional cloud services still drive a large share of this growth, AI services are becoming an increasingly material contributor. So far, so good.
However, the real question is whether a market actually exists to sustain this CapEx spending at scale relative to revenue growth. The current CapEx growth rate (~50%+ year-over-year) has already outstripped revenue growth, and no one truly knows where the trillions in required future revenue will come from.
If this projected revenue growth fails to materialize, tech equities face severe re-rating risk, given that current stock valuations have already priced in these best-case expectations. A market crash unless a real market is discovered.
In summary, nothing new—perhaps just another red flag.
> Bain forecasts that annual spending on AI infrastructure might hit $1.5 trillion by 2031.
So maybe in 5yrs it will need enough revenue to cover $1.5T in capex spend globally in a year, investments which as the article mentions is also being supported by governments in "the UAE, Saudi Arabia, the EU, South Korea and the US". ... Or spending growth could lower over the next couple years to be more realistic.
I think their claim they can make, assuming their evidence is true, is
"AI needs $6T in annual revenue for every investment in AI to be profitable"
I think some people will make a lot of money and more people will lose a lot of money.
Most of those investing know this, they are taking the risk of losing a lot to attempt to be one of the ones that make a lot.
A lot of early internet tech companies went bust, a few became extremely successful. At the time I would see high valuations and ask "Yes, but how do they make money". Most of those with an unclear answer to that question are not around now. The ones who had a tangible plan to make money, even if they were making a loss at the time, tended to survive.
There is a lot of Dumb money going into AI, when that is the dumb money of wealthy individuals, I am more than happy to let them receive no return while paying for infrastructure. There's a problem when the dumb money comes from dumb individuals who are routing money from others who do not have a say in how it gets invested.
That is not an AI specific problem, that is a problem where people can make decisions where others carry the risk without their consent. That is the problem that needs to be met head on.
Consumer-focused services, which includes subscriptions and advertising revenue, is seen to contribute $200 billion to $400 billion
So not $6T of ARR subscription sales, but $6T of "economic enablement". By 2031, the global economy is estimated to add another $40T of economic activity to GDP. So AI needs to account for 15% of that.
What happens when the adoption of AI destroys the middle 60% of the bell curve of programmers and technologists? How will the middle class of people spend money on products/services if they don’t have a job?
We can’t both create wealth and destroy jobs with nothing to replace them.
America has little to no manufacturing base.
Technology and finance has been its differentiator economically speaking for job creation. Both are at risk from AI adoption. Businesses have to sell to someone, and at the moment it’s not clear — if the stated goals of revenue are to be believed, how that can happen.
Reason I ask is sure, you did this but since few people are paying true cost, if prices rises by 10x, is it still worth it?
His latest newsletter (from today) also talks about this: https://www.wheresyoured.at/dead-money/
“Being right at the wrong time is as good as being wrong” - Howard Marx
What you consider “losing money” I might consider “choosing not to participate in an ongoing global financial scam at the cost of my retirement growing slightly slower for a while”.
I don’t even disagree with some or even a lot of his takes, it’s just he is singularly a content generator with a track to run on. Look at his previous work, it’s much of the same kind of attempts at being relevant. To me he’s nothing more than a drive time radio host, shouting about something just to fill the air
Just for fun, I'll join in myself and make two bold half-hearted predictions that will surely be wrong:
- Zitron is wrong about the details, but right about the ultimate fate of the AI companies. Turns out AI is useful after all, it just isn't able to justify trillions of dollars in expenses. Shit falls through hard. Probably not an AI winter, but more like the dotcom bubble, as many have already predicted for years. Everything looks rosey right up until the first domino falls.
- The AI safety doomers are right, just not any time soon. Turns out our depth of understanding what intelligence really means was severely lacking; it's hard to quantify and we never had so many things testing it. Eventually, we really do discover why LLMs emergent capabilities really are inherently limited in ways that just make their ability to meaningfully "escape" less scary, and maybe architectures emerge without these limitations, just not yet. The fight with LLMs and malicious use winds up looking a lot more like a supercharged version of the current fights we have with dumber bots. Everyone winds up having to fight LLMs with LLMs, and this new world eventually pushes both good and bad new legislation in its wake, finally actually pushing responsibility for AI misfires, but probably in a way that is at least as bad as it is good, creating chilling effects and harming competition unnecessarily, because that's just how things go. Maybe we eventually do crack true super intelligence where it's a full superset of human mental facilities, and then geopolitics maybe gets as interesting as it ever has been in history. Probably not in a way that is fun for people living through it.
I can't blame Zitron. It's fun to pretend to be able to predict the future. I still broadly agree that the financials don't really seem to make that much sense even if he clearly keeps getting the details wrong.
I don't think that nobody seems to mind that. Pro-AI people make fun of doomers because of their failed predictions of apocalypse at least since GPT-2 days.
https://danluu.com/zitron/
I kinda hope corpos with a bunch of money and plenty of normies adopt AI so developers don't get bled (as) dry, esp. given the recent OpenAI changes which I feel like Anthropic is soon to follow.
Edit: explanation of the downvotes would be nice. Dan Luu made a fairly factual article there that explores some of Zitron's claims. And personally I don't see how it's bad to wish for wider adoption of AI so the big orgs get their fill of profit (since enough inference could help fund R&D better) and developers don't have to bear that burden.
OTOH, this price crash will increase demand for inference. Maybe some data centres will go bankrupt, but the scavengers won't be selling off used TPU's for cheap, they'll operate those data centers to sell you tokens for cheap.
I guess either we get human level AGI so it can do human like jobs, or they'll have to trim those plans a good bit?
I don't care how good AI is at something like software development or whatever task. If customers were paying real prices for usage would any of us be using it?
Any data out there on how far off enterprise API pricing is from actual compute COGS for these models right now?
2. Global GDP will be ~$165T by 2031
3. This is not $6T of ChatGPT subscription revenue. The article actually specifically says of the $6T, $200-$400B would be subscription and AI app revenue in 2031.
4. The $6T figure is AI "economic enablement". Drugs, robotics, research, coding, manufacturing, materials, etc...
*https://blogs.lse.ac.uk/businessreview/2026/09/22/how-americ...
Chatgptd emails are not adding value anywhere
Very few professions if any get anything remotely like the value coders get from LLMs right now Maybe lawyers or doctors but it's just way too risky error wise A comma off in a legal doc can end your career
Models are getting cheaper, and more efficient, but I don't see how they cross the threshold of full autonomous intelligence in the way that an employee needs to be fully accountable for their actions.
A perfect ouroboros.
https://existentialcomics.com/comic/540
like in the good old days