r/ValueInvesting • u/EnvironmentalFeed246 • 1d ago
Discussion Gartner Report : AI Spends, and impact on Alphabet, Microsoft, Amazon and Meta + neoclouds
Hey Everyone!
I was reading up on the Gartner report that caused the neoclouds to selloff. I think it has ramifications on some of the companies with broader appeal like Alphabet, Microsoft, Amazon and Meta
Gartner estimates AI providers will spend about $7 trillion on AI infrastructure between 2026 and 2030, and AI revenue over that period will only be about $3.6 trillion
I had a couple of questions:
- A big chunk of this spend sits with Alphabet, Microsoft, Amazon and Meta. Do they actually have the capital to fund their share, probably $3.5 trillion or more, over the next few years? They are already at about $760bn this year, and I am not sure they have the cashflow to accelerate the buildout
- Gartner’s numbers assume spending accelerate. If business and consumer AI revenue doesn’t scale, won’t companies just slow down rather than overinvest by a few more trillion?
Overall, I understand the buildout isn’t yet generating a return, which is a fair callout, and we’ve known this for a while. I don’t think the Gartner report told us much that’s new. What do you guys think?
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u/itswheaties 1d ago
Since when has investment needed to have an immediate payoff? Infrastructure spending on data centers have leases of 15+ years. I agree with you that the investment will slow a bit, but I think its a bit naive to expect the return to exceed the investment immediately.
The technology develops so rapidly that I still think its safe to assume that returns in 3 years will continuously accelerate as adoption broadens and technology becomes more intrgrated.
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u/Far-East-locker 1d ago
Didn't read the whole report, but from another news, the period mean for the hardware's life cycle, not the period of build
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u/itswheaties 1d ago
5 y.o. gpus are at peak price per hr again this month. I think this is all a reaction to LLMs not having as much revenue as anticipated.
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u/EnvironmentalFeed246 1d ago
I agree with you. I felt that the Gartner report was non-material, and wanted to double check if I missed anything. Tens of billions have been wiped out in the past few days
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u/Ehh_littlecomment 21h ago
What does the 15 year lease cover though? VR for example requires a complete overhaul lf electrical systems. Ex GPU and RAM, the infra is a very tiny part of the total bill.
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u/itswheaties 10h ago
My point is that hyperscalers are anticipating growth over decades. You're right that equipment will have to be swapped out and so forth, but I wouldn't be surprised if hyperscalers are surpassing 1tn cloud revenue per quarter by the end of the decade
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u/Ehh_littlecomment 10h ago
If we’re just throwing random numbers why stop at a trillion, why not 5 tn?
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u/itswheaties 10h ago
No you're right. Annually would be more realistic not quarterly. My bad.
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u/Ehh_littlecomment 9h ago
It needs to be a tn incremental annual revenue by 28 to justify current capex let alone a growing capex scenario. If they get to a trillion total in a decade, it would lead to broad based crash in valuations of all AI stocks.
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u/NoSet3132 1d ago
https://reddit.com/link/ph77bee/video/e89k46hxnwvh1/player
To say that Gartner was off in this forecast is an understatement
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u/EnvironmentalFeed246 1d ago
I know what you mean. They had forecasted we'd be spending an hour in metaverse everyday by now
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u/throwaway9gk0k4k569 19h ago
Gartner Predicts Neocloud Providers Will Capture 20% of the $267 Billion AI Cloud Market by 2030 https://www.gartner.com/en/newsroom/press-releases/2026-06-23-gartner-predicts-neocloud-providers-will-capture-20-percent-of-the-267-billion-dollar-ai-cloud-market-by-2030
Gartner Says Over $3.5 Trillion of AI Infrastructure Spending Could Be Exposed to Impairment by the End of 2030 https://www.gartner.com/en/newsroom/press-releases/2026-10-14-gartner-says-over-us-dollars-three-and-a-half-trillion-of-artificial-intelligence-infrastructure-spending-could-be-exposed-to-impairment-by-the-end-of-2030
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u/Kingcanute99 1d ago
AI revenue over that period will be less than $3.6T
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u/ApoxieDK 1d ago
Exactly. My company is already moving to open weight models run locally. Its cheaper and more secure.
Why would companies choose to pay millions of dollars for AI from providers when they for 100k's can setup their own AI that is both more secure and sufficiently good for the work they need. You dont need frontier models for 99% of the work in a typical company.
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u/legno2 1d ago
People thought the same back in the days. Eventually AWS took over because it provides less headaches
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u/Tim_Apple_938 1d ago
Ya that guy is overestimating how much ppl wanna do DIY
Dell shouldn’t be a centi-billionaire cuz companies can just assemble their own desktop computers for cheaper right??
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u/ApoxieDK 16h ago
The different is price. What we would be paying 1-2M dollars for in tokens we can do with a one time investment of 1-200k dollars in a local machine with open weight AI. You cant make your own dell computer for 10% of what a dell costs in retail. You could probably save 10-20% doing it yourself but thats not so attractive as 80-90% savings.
None of the AI companies will make a profit long term (except maybe on ads), that is my prediction.
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u/Tim_Apple_938 1d ago
Na this is dumb logic.
Agree on cheap models parts, but open has nothing to do with it
The core issue w running models isn’t the proprietary-ness ; it’s efficiently managing fleets of GPUs , handling inference software routing etc
Enterprise at large is gonna outsource that to AMZN GOOG MSFT, just like they do for all of their cloud stuff.
Within that, they’ll just choose the cheapest model that’s good enough. Whether it’s open or not is irrelevant, it will be from an API from one of those 3.
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u/ApoxieDK 16h ago
You cant really share sensitive information with outside providers. So that speaks for local machine with AI installed. But sure, some will sign up to pay 1-2M per year for AI as a service, while they could get the same results with a 1-200k investment in a server and an open weight model.
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u/zer00eyz 1d ago
Andrej Karpathy made a tweet about how AI is being used.
Inside the labs they dont use a single instance/agent they are using them concurrently. This is also show to us (the public) in the OAI/Hugging Face hack (1200 agents in the hack of some unknown number running).
The idea of one really good agent doing the job of a person is appearing to be flawed - you're not going to get a single agent AGI - the power curve is still the power curve. This means there are theoretical limits on what a. single model can do. Spending more tokens at inference on thinking can improve task performance but you still only get one result and you're not sure if is the best one, especially with testable (math, comp sci) style domains.
This is why "brute force" works so well. Delegate a task to 1000 agents and see what they come up with in the noise - and maybe you get an "optimal" solution. This means you now have trade offs to make. 1000 agents in one day for a solution that you need now. Or one agent for 1000 days, where you MIGHT get a good enough solution sooner and then make a choice on letting it continue to run. What happens when your competitor is half the price but can do the job with 1500 agents in a day?
That high margin chip, purchased with high interest debt was a gamble that tokens arent a race to the bottom volume commodity. Supply will always increase to meet demand and drive prices down, till we have over capacity....
That means the long tail is in infrastructure: the buildings (long term assets), Power and Bandwidth (substrate and operations), and cooling. The chips (and the tokens they produce) are an over valued commodity.
GPU's are looking like tulips.
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u/Nearing_retirement 1d ago
I often wonder if demand for intelligence is limited. Even before AI PhDs in various fields had trouble finding jobs.
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u/Tim_Apple_938 1d ago
Ya isn’t it a meme on Reddit of all places that high iq ppl aren’t successful and rather dumb extroverts rule the world (and bang all the “Becky”s)?
I say Reddit of all places cuz now it’s one of the most religiously pro ai on that sentiment “demand for intelligence is infinite”
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u/Nearing_retirement 1d ago
Well I will tell you my story. I’m smart introvert that has worked for successful hedge fund for 25 years. They have paid me well. At this point I can see how AI will degrade my value to the company. But at the same time I’m thinking that personally I can use AI myself better than my company can. So I’m thinking of just quitting and trading on my own using AI. I can use it smarter than the chads can as an amplifier to my own ability. So I’m thinking why not. It is really just a matter of being disciplined. If I’m disciplined I can make more on my own. That’s my feeling anyhow.
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u/Tim_Apple_938 1d ago
NGL sounds like ai psychosis
be careful with that it is especially bad for smart introverts
But ya the other part of the Reddit meme is that redditors at large aren’t smart, they just have bad social skills and that’s why they’re not successful. Of course high IQ ppl are usually very successful esp in tech and finance.
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u/Turnvalves 1d ago
Problem is by using it you are helping them teach it to eventually completely replace you. This is no different than when they would come into the factory with a camcorder and film us doing work so they could train the people in the factory in Mexico to take our jobs. Eventually they couldn’t make it work in Mexico like they wanted to so they went to china. Same thing different century.
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u/Nearing_retirement 1d ago
Yeah I hear you. For me I’m not looking to make huge returns. Like if I could make 5 pct above inflation I would be happy. To be honest you would not believe the stupidity of the management at these hedge funds. It is 90 pct political skill to get into the higher positions. These guys have no clue whatsoever. I can’t even explain it, you have to be there to see it.
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u/Environmental_Park_6 1d ago
There's a lot of assumptions in this but that's the problem with forecasting. I don't know the difference between a cumulus and neocloud but I do think Google, Amazon, Microsoft, and Meta are entrenched.
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u/csgosteve 1d ago edited 22h ago
the hyperscalers have other revenues to cover most of their AI build out costs, sure their shareholders have to be patient through a period of lower free cash flow, but the business risk is minimal. worst case AI just becomes another cloud service no different to storage or compute.
neoclouds need everything to go right to remain solvent, they need to differentiate enough to steal locked in enterprise and win on cost, while retaining margins to pay back their debt almost exclusively from AI revenue.
*AND neoclouds will likely need their competitors (like the hyperscalers) to ALSO be their customers, for them to work.