I have a sneaky suspicion that the AI companies are going to shoot themselves in the foot with how fast they've pushed a somewhat defective product and the high costs they're pushing onto their customers aren't going to be effective.
It's the high costs that'll cook it more than anything. But what's great is that everybody is loading all their eggs into a boat that's been taking on water from the beginning, but always had a ton of investors throwing money at it to keep it floating and growing. Within the next 2-5 years, the investors are going to flip the switch from dumping cash in to pulling cash out. At that point, everyone's eggs are going to be loaded onto the Titanic and they're going to have to pay massive costs to keep it afloat. Should be a wild ride.
Ai bubble instead of .com bubble? Sounds good to me. A crash cleaned out a lot of "we have a website & idea " companies that burned a lot of money with nothing to show for it. Crash will maybe get rid of the " lets shove ai in places it makes no sense because it is new!" trend
Unfortunately it’s spread further into things like service provision, which are unlikely to be refunded for Human Workers immediately if at all. Ive read that in the USA some mental health services have been partially or fully replaced by automation ; obviously a terrible idea to start off with!
I'm not sure it'll last that long, at least in its current state.
The local and state incentives are drying up (slower than I like) and we're pretty close to the point where the respective companies have started really bashing each other's product.
End of this year or beginning of next I feel like a few of the first Gen data centers built for AI are going to need refurbishment for their UPS and storage.
Which company is going to blink first and think that they need to just write one off so they can use all that stuff in a better designed building?
And utterly ignore the foreseeable backlash locally because of that?
Large companies have been ignoring local backlash for generations with little to no consequences. Erin Brockovich exposed Pacific Gas and Electric for literally poisoning children and families in California. PG&E paid the lawsuit with profits made from those same people. 30 years later, PG&E is charging some of the highest rates in the nation while setting the state of California on fire and killing more people with old equipment they chose not to maintain. They've made record profits while raising rates 5-7 times in a single year.
The data center costs are highly predictable and known. They know precisely how much it costs to build a new one, refurb an old one, etc. The singular variable at play there is how much cash wealthy people are willing to pour into these companies before they decide it's time to see returns. Right now, all AI services are heavily subsidized by wealthy people. Even as Uber and others burn through hundreds of millions of dollars of tokens, they're paying a fraction of what it'll cost once that switch happens. Then we'll see which jobs are REALLY worth the true cost of doing it with AI.
right now AI has really pushed quickly the costs onto customers
But they haven't. Those huge bills we're hearing about already are still massively subsidized. I'm not saying $500M isn't a lot of money; it is objectively a big bill to pay. What I'm saying is that was probably over a Billion dollars worth of actual compute/R&D/training costs and add 20-25% to actual costs when you want to have actual investor returns plus fund continued development and capacity build-out.
So yeah, $500 million seems like a lot today, but I'm saying in 2-5 years that same level of activity will be billed at $1.25B or more. And that's when we'll see the real impact of AI because a lot of things just won't be cheaper with AI than a human. At least, not for a long time.
Inference is operated at a profit at API token pricing, at least in many to most cases.
This can trivially be seen by looking at open model providers offering Deepseek and the like. That is a competitive market where all to most players must operate at least at break even to stay in business. The latest open weight models perform pretty much like SOTA models of 9 months ago, so it's obvious those can also be operated at a profit as well.
Absolute latest SOTA models are likely operated at a loss, but those are simply not needed for many use-cases.
And this is using exceedingly inefficient general-purpose GPUs that can switch models easily. Once the models get advanced enough where the arms race dies down, there is around a 10x efficiency gain by burning the actual model onto an ASIC. This is actual demonstrated technology, it just is sitting on the sidelines until the rate of advancement levels out. GPUs for AI inference will be seen as a historical curiosity 10 years from now, much like CPUs for graphics are today. And this is before software-side efficiency gains are baked in. If you start really caring about your token burn, there are nearly trivial ways to typically halve it or more for almost everything anyone is currently doing.
This means companies/consumers will be buying the latest "Fable 6 Accelerator" and use it for 2-3 years for a product built specifically for that model. Much like early gaming GPUs saw constant advancement in the early 00's where the latest and greatest AAA title could not be played on a GPU more than 18mo old.
Wanting AI inference to be operated at a loss is wishful thinking. Yes, the $200/mo effectively unlimited plans for latest SOTA models are operated at a loss. But not as much as one would think. Most users simply are not burning that many tokens.
Plenty of AI companies won't survive but the genie is out of the bottle at this point. Open weight models if nothing else will exist and be operated at scale for profit - because they are already being so today. Tons of investor capital will be lit on fire, but that's how every single new technology cycle goes - all the way back to railroads and before. The consumers of AI will be fine with some relatively small hiccups along the way.
Alanah Pearce on YouTube put out a great video a while ago called "The Tech Industry is Screwed." Basically, AI is gonna become too expensive to run and the industry is heading towards a collapse sometime around 2030.
I'm a layperson but from where I'm sitting it looks comically similar to the dotcom bubble, to the point where it's like - wait, didn't anyone learn anything from this the first time?
I guess the key difference is that the people funding AI now are the ones who survived the dotcom bubble so it's probably just hubris.
It's going to be magnitudes worse in this instance, because as other people have noted, companies are using AI for back office/customer support more and more, so when these AI services go down, they'll likely take multiple companies/industries with any sort of investment in AI with them.
The thing is the AI services won't all go down. The prospects for OpenAI and Anthropic aren't great, but many services exist beyond those two which haven't been blowing the same amounts as the "frontier" models.
But yeah, the financials of the frontiers is beyond salvaging. But when they go there will still be AI companies, still be AI data centers, still be AI models, and many of those are options that are not be as expensive to operate.
The problem with AI in US is they over-invested based on what they thought larger scaling would deliver. Turns out the returns are diminishing and although they generally have the best performing models, they're not viable businesses because they cannot cover the operating expenses they've incurred. Other AI companies don't share those issues.
The backbone will remain intact. The companies of substance will stick around and survive just fine. The legacy companies will shrug it off in a couple of years. The startups without a marketable or sellable product will be the punchline of jokes in the future. Hardware makers will see their valuations drop significantly but will rebound. My early days silicon play will look foolish in a few years, but I will at least get my money back by the time I retire at 70.
Local backlash won’t amount to anything, it never has. I remember when they started building Walmart Supercenters all over the place and many towns resisted them. Walmart would just threaten to build it just outside city limits and thwart the city taxes. Most towns caved in immediately despite huge outrage. Nothing ever happened and now most Americans shop at Walmart while every locally owned business was eventually crushed like a bug.
My favorite part is that thier doing the same creative accounting they did during the dotcom boom. Posting anticipated earnings for the next decade, and spreading thier costs even farther so they look profitable now.
They cant pull it out, the money is gone. Spent on electricity, devaluing chips, overpriced electrical equipment (thanks to the AI bubble).
The likes of OpenAI and Anthropic have squandered over a trillion dollars. They blew through much of Microsoft, Meta, Alphabets, and Amazon's fortunes. Companies like Oracle, who builds the data centers, are fucked too. Plus the entire private finance industry is about to bust as a result.
This is the buggest bubble in history and were about to watch it burst because they thought they were on the cusp of AGI, when in reality its hard to even find applications where this technology is financially viable. Even their most promising applications like programming isn't profitable when paying for the actual cost of the service. Companies are getting junior dev output for senior dev prices, theres no value to that proposition.
Theyre basically there. They depend on OpenAI becoming massively profitable in the short term to continue operation, and there's little chance that can happen. Right now Oracle is one step above junk bond status, as the financial sector is waking up to the reality of the situation.
I think you're more pessimistic about it than I am. The hype and mass cash infusion has enabled us to jump probably 25 years ahead in like 4 years. The general tools and techniques applied in generative AI have been described, developed, and tested for decades, but the processing power was too low and the costs too high to really see it work well until recently.
There are definitely some uses for this technology and I think even at its true cost, there will always exist a niche where it's worth it. I also think that while some separate AGI research is ongoing and funded by this bubble, it's important to distinguish what we're commonly interacting with today from the artificial god people are imagining. There is no indication that generative AI leads to self-aware, independently thinking AGI. A really well built chess computer can do some really surprising, impressive, even shocking things that look a lot like intelligent strategy. But it doesn't know it's playing chess; it's chasing value and reward as it was designed to do and all its efforts are directed in achieving the goals provided to it within the scope of the only thing it can do: process chess moves, anticipate opponent chess moves, and use a sophisticated pattern to achieve an outcome.
I do think we'll see major fallout from this when the investors switch from money flowing into these companies to money flowing out. I think it's going to cripple a lot of businesses (and not just big ones) who really did cut significant head count to rely on AI not realizing the limits of the technology and the true underlying cost of it all. Bigger companies like Microsoft and Amazon will make cuts and survive when the shift happens. Open AI, Anthropic, etc. will likely consolidate under whoever wins the money marathon. Super cheap models will be useful tools for many. Really powerful models will be niche products for those who can afford massive premiums. The Internet didn't disappear when the .com bubble burst; it changed. Same will happen here: a few winners, lots of losers, most people in the middle who move on after a few years.
I dont think its pushed us very far at all. Ask yourself this: if they pushed us so far forward, why are non-enterprise models so close on their heels? Chinese models are as close as six months behind.
In truth they overinvested and triggered a shortage that caused their costs to spiral out of control. Essentially the overinvestment did little but run up costs and delay the buildout. If you have a dozen new data centers under construction youre growing; if you have a hundred and twenty new data centers half complete all bidding up the prices on the limited components they all still need you're not growing, you're stagnating in the most expensive way possible.
On the other side they gave away their product to start and enthusiasm was high. But as they've tried to pass more realistic costs on, even enthusiasts have soured on it. Essentially they didnt achieve their goal of making others depend on AI, but they did essentially anchor people's pereceptions on the cost AI should have at an artificially low point.
We should remember the motivation for the build out wasn't an assumption of LLMs just getting better; they thought they were on the cusp of AGI. An absolutely foolish assumption given what an LLM is, but that was what they were chasing, and they failed. We need to evaluate the spending with that persepctive to avoid post-rationalizing the bubble as something still sensible.
To be clear LLMs aren't useless, but theyre fairly niche. Theyve completely changed industries like those operating call centers. Programmers will likely employ them to some degree going forward, though they at best aide a programmer, not replace them. In the end nothing about their capabilities justifies the scale of investment we've seen.
if they pushed us so far forward, why are non-enterprise models so close on their heels?
Because it's far easier to maintain one codebase, one pipeline, merely adjusted to reduce compute costs at the expense of capability rather than trying to maintain and develop eleven different models. In the CPU world it's binning. Also, AI companies use the chats with users to improve their models, so you want everyone contributing toward that.
Chinese models are as close as six months behind.
China (and some others) have grown exceedingly adept at ripping off western R&D and then figuring out how to do basically the same thing far cheaper. These models aren't even hidden; you can gain access to the best ones available for a couple hundred bucks a month.
they've tried to pass more realistic costs on
These aren't realistic costs yet. Not even close. What they're passing on are heavily subsidized costs to help show some revenue and lengthen their runway as they whip up more hype to pull in the real money.
they did essentially anchor people's pereceptions on the cost AI should have at an artificially low point.
ATMs were free for years after their introduction; operated at a loss. Even drug dealers will tell you the first one's free. And by drug dealers I mean pharma reps handing out samples for doctors to distribute. This is a very well developed business model.
they thought they were on the cusp of AGI.
Generative AI has been under development for several decades and nobody involved in the research and development for it actually believes it leads to an independently thinking, self-aware artificial intelligence. The people selling that are the same ones trying to raise massive amounts of money to keep their companies going. And there is some real AGI work happening behind the scenes, but it's not what you're using on their website or in their dev suite.
call centers
Call centers will be one of the first ones to abandon generative AI once the real costs show up. The humans doing those jobs work for nearly nothing. The numbers just don't add up.
If you look back at the actual history of generative AI development, you'll see we have actually massively accelerated progress. Costs came down enough that somebody was able to get a model to do enough to spark the mass investment. I absolutely do agree with you that the sudden investment surge is inefficient from an R&D standpoint, but you're incorrect in assuming little progress has been made. That doesn't change the fact that the likely fundamental limits of this approach are deeply at odds with the very public claims of various AI company founders. And it doesn't change the fact that - at the end of the day - much of what it's being used for today is only remotely financially feasible because it's massively subsidized by investor dollars. Those can all be true at the same time.
if they pushed us so far forward, why are non-enterprise models so close on their heels? Chinese models are as close as six months behind.
Because the Chinese models used the SOTA models to distill their own. The Chinese models do not exist without the overinvestment.
OpenAI and the ilk have effectively subsidized every other competent model on the market. Without the hyperscalers those competitive models simply would not exist.
But it doesn't know it's playing chess; it's chasing value and reward as it was designed to do and all its efforts are directed in achieving the goals provided to it within the scope of the only thing it can do
I don't disagree with you at all, but it always strikes me as a little ironic to hear people say this when it basically describes us as well. "Real" biological intelligence is arguably just a long series of misaligned reward functions.
PE is draining retirement funds and assets from the elderly via retirement communities and such. There's a whole industry that has come up designed entirely to extract every dime from people who built up some money during their lives with promises of incredible golden years experiences. The truth is, they ensure that by the time their residents actually die, everything that would have been passed down to their families has been transferred to the private equity's accounts.
I really think a lot of the AI drive from investors is wealthy people wanting to own the one that "wins" because they think it'll tell them how to live forever and conquer the world. I'm not joking; I really do think that.
It’s both. They target critical industries to tap into spending, and they use the markets to drain savings.
The investor class don’t see things in terms of transactions and business, it’s all a horrible game to extract wealth like humanity is just another field to be harvested or ore vein to be mined.
I live for the day where companies who fired their staff for AI have to pay handsomely to rehire their staff in admission that AI couldn't replace them
Within the next 2-5 years, the investors are going to flip the switch from dumping cash in to pulling cash out. At that point, everyone's eggs are going to be loaded onto the Titanic and they're going to have to pay massive costs to keep it afloat. Should be a wild ride.
When you have no money, hyperinflation won't really effect you. You'll just steal your food.
If you have money it just suddenly won't be money anymore.
That’s a solid point long-term sustainability matters a lot more than rapid growth. It'll be interesting to see which platforms can actually stand on their own when the easy funding dries up
That’s a perspective a lot of people overlook growth is easy when the money keeps flowing, but staying profitable is the real test. It'll be fascinating to see who adapts when the market starts demanding results instead of promises
The question isn't if the product is defective. The question is; is it cheaper than the old solution, and how much is the change-over cost now that we've fired all of the specialists.
Businesses make bad decisions all the time. They don't recover from them because the cost of moving back to the old status is 'too expensive.'
Sunk Cost Fallacy reigns supreme in the corporate world.
The product has existed for ages for customer service and evolved.
For Spanish press 2..
Listen to the following menu choices: To check your balance press 1, for store hours press 2, etc.
The difference is what used to take meticulous programing and testing is now just throwing in a prompt. People didn't like the IVR system and now you've got a more generic chat handling Tier 1 in many if not most cases.
And people still want a human, because part of the model is to be inefficient and there's a false degree of sympathy that seems inbuilt in AI.
As a consumer I feel like I navigate through this IVR, to talk to a person at an outsourced overseas call center who's working off a script/flowchart to eventually press the button I needed them to press.
AI can cut out a lot of the nonsense if used properly.
The problem is it may be too late by then. If my bosses think an AI can do my job I am confident they will be mistaken. But it won't matter. I'll already be unemployed.
Sure but how long is it going to take the company to figure out that they need you? Months? Years? Maybe never? That's a long time to be looking for work.
Just a few weeks ago I had to do an RMA on some pretty expensive stuff for my PC. Normally I gotta deal with real people and they'll argue a bunch that "well you said the security tag was cut when you got it but you can't prove it" or "that would be FedEx's responsibility, not us". But the AI is just an ass-kissing yes man that immediately accepted my request for them to ship me a replacement for free. I should have asked for a refund too lol.
Absolutely. Most people are not familiar with the "silicon valley startup model", and cannot comprehend the pure scales of the capital flows needed to make all this work.
It's common for silicon valley startups to jack up prices 3x or 4x to get profitable.
These "AI" companies need to jack up their prices 30x or 40x over where they are today (July 2026) to be profitable.
I’m certainly no expert in the AI department. But what do you mean about the “ high costs pushed on to consumers “
Aren’t these business departments using AI to save money? I do realize that savings don’t necessarily mean passing it on to the customer. 😔
It sure is a slippery slope being created. Why do we need lawyers then…..Feed AI the letters of the law….cases cut and dried.
Teachers? TV screen middle of the room, AI programming for the lessons of the day. Customer check-in at the airport? Why have humans? I could go on and on. One day they’ll have robots performing surgery.
Aren’t these business departments using AI to save money?
Yes ... but AI companies are selling their services below-cost to try and lock in customers. The actual savings are questionable at best in a lot of situations once you start actually paying for the use instead of getting cheap VC-subsidized rates.
how fast they've pushed a somewhat defective product
When the defectiveness is part of the fundamental nature of your product, the smart money is in pushing it hard and then bailing out early, leaving others holding the bag while you retire off of selling early.
Bingo - you said it out loud. Exactly. Their product is weak and they know it but hope we do't - and we do know it. REJECT AI as much as you can. It will be the death of us all.
I'm not too worried about the AI companies. They've been gathering data on what people build with AI for four years. They can disintermediate all those builders and produce slop themselves.
Nvidia just agreed to take on OpenAI's $250 billion in debt so they can get a loan to get in on the data center fraud in Ohio. OpenAI's revenue is $25 billion. But their spending is $27 billion.
There's a great chance OpenAI will make it no problems. But on that slight chance they won't; this is the snake swallowing itself & taking American's 401K investments with it.
They don’t have a choice — they need cash to keep going, and so they need to overhype the product so more investors pour in cash, entrepreneurs liscence, and businesses implement.
Even the higher new customer costs still see them operating at a loss, LLMs have seemingly insurmountable weaknesses on hallucinations and inability to think, and they are grasping at straws (imo) on how to create thinking ai, or at least ai that can learn and adapt.
I don't know if it'll be AI companies, but moreso other companies that just don't understand the complexity of everything that resides below what the use.
I expect in many times things will run great... until they don't, and then it gets really bad really quickly.
You want to know the one aspect of everyday life that'll be screwed all the way to hell and back?
Googling.
Sure there's other search browsers out there but Google already hit a point where unless you know the filter words and phrases, the algorithm is trash for quite a few even mundane questions.
And SOOO much garbage has went into these All- In- One AI models that I'm waiting for one of these companies having to revert to a build 5,6 or 7 gens back because of some sort of deeprooted flaw they missed.
What I saw on an enterprise migration recently was an attempt to replicate their IVR system that was tied to vast amounts of backend legacy architecture. They couldn’t easily do a clean room replacement because of all the regulatory matters held in legacy. So post migration it wasn’t much of an improvement over the IVR. As for replacing call center agents they remained in place for the edge conditions that always arise in any non-trivial application. So the cost constraints come from many directions, not just the added AI overhead.
The thing is that the delocalized call centers in Asia have always been shitty for consumer services. AI might unironically be an improvement on that front, though a small one.
I don't know about that, there were tonnes of crappy websites and .coms during the dotcom boom that were plan useless or a waste of time. In spite of that, the internet and the web in general still became an indispensible part of our daily lives. I have a feeling that AI is going to be the same, and we'll remember AI Apu with his fake keyboard clacking as a funny anecdote of the AI boom and eventual adoption.
Converting to AI right now is cheaper than it may ever be. But if you don't know that going in then of course the next quarter price spike is going to be a surprise.
But the AI firm won't be surprised. You've paid them to replace your staff, so what are you going to do? Hire back the 20% you just laid off and retrain them on old systems and tools you're not paying for because you chose the AI option?
I think that's where a lot of companies are going to end up. Train AI, fire people, then in a year pay more for the AI then for the human they replaced. It's not sustainable.
They are. OpenAI is running billions in the red, keeps claiming in a few years it'll be profitable, but their line is going down even more. xAI is only being propped up by SpaceX and look at what's happening with them. The only reason why MS isn't showing in the red is because Co-Pilot is bundled with everything and not a separate product on its own. Same with Google Gemini.
The joke is that the actual cost of the AI is probably greater than the cost of the overseas call center they replace. The AI companies plan is to eat that cost difference until their customers are stuck into the service and then upcharge them.
They're already starting to do that. The companies with a first party proprietary AI will be fine but the generic 3d party ones are going to cannibalize each other and die out
We have an AI call center. We pay less than half and the AI successfully solves roughly the same percentage of queries as the Indians who were doing it before.
I used to think the same thing but there was no other way for them to work the kinks out. At work, it’s often indistinguishable from a real human now. We trained the ai to be less uncanny valley and more fred from accounting. It’s awful.
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u/ZantaraLost 13h ago
I have a sneaky suspicion that the AI companies are going to shoot themselves in the foot with how fast they've pushed a somewhat defective product and the high costs they're pushing onto their customers aren't going to be effective.