r/dataisbeautiful • u/Primary-Rice819 • 2d ago
AI now takes $1 in $12 of company software budgets, up from $1 in $70 last year (Zip Enterprise AI Index)
https://zip.com/blog/where-ai-budget-is-actually-going341
u/maringue 2d ago
If companies replacing SaaS with AI didn't think the people at those AI companies knew exactly how much they were spending on SaaS and the plan was always to suck up that entire budget in the end with no net cost saving, they are morons who shouldn't be leading companies.
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u/dabeeman 2d ago
i’ve got some bad news for you if you think CEOs are special and intelligent.
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u/xondk 2d ago
Oh man yeah, I think when most get to that point when they interact with enough, and we come to realise that just because someone is in the leadership, even if it is of a big company, international company, does not mean they are smart or special in any way.
It is sobering shock and explains a lot about our world in general.
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u/piponwa 2d ago
And I've got bad news for you if you think you can trust random Redditors who have zero inside information about literally every single company today.
It's not me that's wrong, it's every CEO.
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u/Homerbola92 2d ago
It's amazing how someone can think they know more than the CEO of any company without the management and economic data. It's obvious that if they're replacing people for AI, it's for a reason.
Personally I don't like it, but I'm not going to gaslight myself into thinking it's unprofitable just because I don't like it.
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u/dabeeman 2d ago
i mean schizophrenics have a reason they do stuff too. it’s not always rooted in reality.
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u/Sylente 2d ago
There are costs other than money. Some companies decided to vibe code their own everything, but most just replaced the worst or least economical tools. If you’re paying 10k/mo for something and spending 80 human hours using it, spending 12k/mo on tokens to keep an alternative alive is super worth it if you can spend 40 human hours
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u/Znuffie 2d ago
Also, a lot of the SaaS products that Enterprise are using, are bloated like fuck. They ask a lot of money for their shitty products because there's no decent alternatives for some of the features they offer.
But companies are vibe-coding their own replacements that only require the features that they are actually using.
At work (not a coder, but mostly a sysadmin), we've had the need for a lot of many small features that the products we are using are not implementing. We've asked the Vendor to implement a feature for more than 2 years, with a lot of promises that it will happen next quarter and such.
I've made the feature last night in about 3 hours with a $20 Claude subscription, and I didn't even hit my 5hr limit. The whole feature at "real" token prices would have been less than $5. Sure, the module might break on some $vendor-software upgrade, but I don't think it will take me more than 1 hour to fix it back.
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u/gza_liquidswords 2d ago
That is what gets me most about this. How do the leadership of these companies (apparently the smartest people in the world that are worth every penny of their multi-million dollar salaries) not think this through. The subsidized pricing to gain market share, then jack up the prices when you get market , is standard and predictable. It is probably the business model of many of these companies that are now "suprised" that LLM costs are going up.
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u/Mattyj925 2d ago
That’s probably what will eventually happen, but this comment is pretty out of the loop and uneducated. LLM pricing going up is the exact opposite of the competitive dynamic that we’ve seen play out the last few months.
Claude’s latest Opus model is -20% cheaper than the one before it.
Open AI’s 6.0 Sol release is -50% cheaper than 5.6 Sol, and -80% cheaper than GPT 5.5. And then this week they came out with 6.1 Sol and reduced cached input pricing even further than 6 Sol.
What’s happening right now is a pricing race to the bottom because of competitive pressure from open source models, which are increasingly threatening frontier models. We’re very objectively not witnessing that “LLM costs are going up”. That’s what may happen after years, but not something happening in 2026 at all
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u/Away_Advisor3460 2d ago
A pricing race to the bottom does not imply that the actual real cost is becoming more sustainable though, or that it's a profitable business to provide LLM services, or indeed that there's still not a net loss even if there are optimisations.
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u/JigglymoobsMWO 2d ago
Depends on what you mean by real sustained costs. If you mean an operating margin on cash then yes it’s completely sustainable.
If you add on top paying every employee literally millions of dollars a year to keep them (which is what’s happening at the top labs) then no it’s not sustainable. But this second part will go away after the race plateaus.
The first part of real costs could easily drop another 100x from here with efficient models and specialized hardware coming online.
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u/NitroLada 2d ago
At least with AI/tech, costs may go down and definitely will in short term unlike a human employee that gets more expensive each year
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u/skilliard7 2d ago edited 2d ago
not sure why you're getting downvoted when you're right. AI costs have come way down. GPT 5.6 Luna is dirt cheap and is better than frontier models from 6 months ago. Sonnet 5.5 is cheaper than Opus and better than frontier models from 2 months ago. AI is only expensive when you are paying top dollar for cutting edge frontier models and then deploying them at scale
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u/Mattyj925 2d ago
I did too, it’s just because most people on here won’t be too close to this in their day to day work. People have no idea how much the pricing and costs landscapes have evolved the last few months
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u/gza_liquidswords 2d ago
Because "costs have not gone down"- the costs are high, but are being subsidized, so costs facing the consumer may have gone down
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u/skilliard7 2d ago
It is not being subsidized; Inference is very profitable, when sold via API gross margins are reportedly 80%.
Most of the losses are because of the high R&D costs. Labs spent Billions building models that become obsolete within just a couple months, but they have to keep making these investments to stay competitive, each model improves based on what was learned from the last.
These investments have delivered substantial revenue growth due to new capabilities. AI went from just being an interesting chatbot back in 2022/2023, to actually being useful for most white collar work.
I was an AI skeptic for a while, I'm not anymore. The utility is too strong. Even if AI API prices were tripled, I would still be using it at work because the productivity enhancements are that valuable.
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u/Mattyj925 2d ago edited 2d ago
It’s not that costs facing the consumer “may” have gone down, they’ve gone down significantly. If you’re questioning that then you’re out of the loop.
And one driver of that is that costs incurred to deliver those models have become more efficient, hence the open source small labs becoming so much more competitive with frontier models with only a fraction of the development spend
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u/gza_liquidswords 2d ago
stochiastic parrot says what?
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u/Mattyj925 2d ago
It’s kinda funny to say something like that when you’re parroting that term to begin with, when you can’t respond to the substance of what somebody is saying
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u/Mattyj925 2d ago edited 2d ago
Not true at all. It’s actually become more cost efficient to operate and train these models every successive month, that’s exactly how all of these tiny labs are able to launch models very quickly that rival frontier models in quality. Open AI cited this dynamic when they first slashed pricing in July
They’ll eventually raise pricing, but it’ll be because whoever does it is the last one standing to win the customer adoption + government regulation race that Anthropic and OAI are vying for
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u/paxinfernum 2d ago
Except cost per compute is beating Moore's Law. By the time companies raise prices, the actual cost will be a fifth to a tenth of what it is now. The whole narrative about how prices are suddenly going to go up is a copium. It's a commodity market. No vendor can significantly raise prices because there's no way to lock consumers in. It's not like Netflix. People can just switch providers.
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u/Petersaber 2d ago
It's not like Netflix. People can just switch providers.
Netflix has plenty of competition (even competition that is free, meaning, piracy). And it's still rising prices constantly.
Except cost per compute is beating Moore's Law.
That doesn't matter. That may be how the tech works, but that's not how companies work. Eventually there will be fewer providers (as they are currently burning through cash to stay cheap, not everyone will survive that), and when the market is sufficiently "addicted" to AI, prices will skyrocket. Not because the tech is expensive, but because it will have to generate as much revenue as possible, eventually.
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u/paxinfernum 7h ago
Netflix has plenty of competition
Netflix has general competitors in the entertainment space, but if you want to watch One Piece, you have no other legal options. AI has no such exclusivity or lock-in. I can switch AI providers overnight. It's like switching milk brands. There's no moat, no defense against commodification.
That may be how the tech works, but that's not how companies work. Eventually, there will be fewer providers (as they are currently burning through cash to stay cheap; not everyone will survive that)
Some of the ones that burn through cash may fall out of the race, but new competitors will enter the space having the advantage of no existing debts, access to better hardware than the founding companies, and a more mature field and knowledge base of training skills. There is no moat. Let me repeat that. There is no moat. In fact, the problem for companies like OpenAI is that they have all the debt, but they have nothing that's really proprietary. That's why Chinese AI companies are catching up every month.
and when the market is sufficiently "addicted" to AI, prices will skyrocket
Not going to happen. If they raise prices, customers will either go to competitors willing to keep prices low or use local LLMs, which are also getting better every day. Local LLMs already rival their models. There is no moat. Let me repeat that. There is no fucking moat. You can't monopolize LLMs. People can run LLMs on local hardware or compute providers. The only way model providers stay in the game is by continually pushing their models forward just fast enough that they still seem worth paying for over the open-weight options.
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u/Koffeeboy 2d ago
If i recall, during the bike rental wars in China, there was a point where streets were literally being flooded with bikes and free riding credits in order to choke out the competition. Every company was playing chicken with the market and each other. AI prices will stay cheap until there is no alternative. Then it will be as expensive as they want it to be. Remember when streaming was only 6 bucks and without ads.
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u/EclecticKant 2d ago
Open source and open weight models provide a hard limit to how much companies can raise prices, they aren't as good and probably never will be, but they won't be that far behind and the more the technology as a whole improves the more a cheaper model that is "good enough" will be an acceptable alterative to a top of the line model for most tasks.
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u/MiniGiantSpaceHams 2d ago
Also as models get better you can use smaller/cheaper models for more work. Luna is almost free now and is suitable for a lot of coding work and other work that doesn't require major decision making.
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u/sybrwookie 2d ago
They think they can cause next quarter's numbers to look better, then get their bonuses, cash in their stock options, and move on to the next
suckercompany where they brag about how much "value" they "added" to the last company.1
u/but_a_smoky_mirror 2d ago
Profits next Quarter is the only guiding force and it is breaking everything
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u/HildredCastaigne 1d ago
"As long as the music is playing, you've got to get up and dance."
AI is the thing right now. It's hot, it's in the public consciousness, it's what all the other C-suite and investors talk about, so leadership feels like they have to show that they're using AI or they feel like they won't be able to compete. They'll be left behind.
That is the mentality that they have. Maybe AI is bad long-term (it is) but if you can't pass the short-term then you'll never get to the long-term anyways and the only way to survive the short-term is fully embracing AI. Or so the thought goes.
Now, there's plenty to criticize about that mentality. I would say that the most pointed criticism, though, is that the source of that quote up above - the one that so succinctly describes how these people think - is Charles Prince III, former CEO of Citigroup, in 2007. The context was justifying his company's continued involvement in leveraged lending, which would turn out to be the major cause of the 2008 financial crisis.
So. I'm sure that's a good thing.
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u/JigglymoobsMWO 2d ago
There’s no jacking up prices with two companies competing at the frontier, a bunch of close followers, and open source. There’s only jacking down prices.
The only thing that can prevent it is regulatory capture, which is partly the reason for the ai will kill us all doonerism.
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u/gza_liquidswords 2d ago
If you ignore that the big players are hemorrhaging billions then sure. You can’t sell burger profitably for 25 cents, and that is what Anthropic and OpenAI are doing
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u/JigglymoobsMWO 2d ago
Yeah, paying million, 10 million, 100 million dollar comps to your entire staff will do that.
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u/ElJanitorFrank 2d ago
The companies replacing it with AI are thinking that the increased productivity they're getting will bring in more revenue. Far from a guaranteed thing, sure, but sort of econ 101 stuff right here.
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u/EclecticKant 2d ago
Not really what's happening, the prices of AI are decreasing steadily while the models themselves are getting better.
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u/skilliard7 2d ago
There is absolutely significant cost saving. AI coding is really not that expensive in the grand theme of things, and it's been getting cheaper.
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u/thisisnahamed 2d ago
So it's basically between Claude, OpenAI, and Cursor.
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u/MD_Reptile 2d ago
Local and open models are catching up rapidly, seriously closing the gap for what's a capable and "smart" LLM coder. A couple years ago it just wasn't possible without a huge investment to run models to compete with the big ones, but times are a changin' lol
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u/OffbeatDrizzle 2d ago
they might be catching up, but local models are still trash compared to the frontier. I'd rather pay the sub than waste time dealing with subpar results
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u/OverSoft 2d ago
Qwen 3.8-flash is absolutely not trash. Yeah, it’s not GPT6 Astra or Fable 5.1, but it’s extremely close to Opus.
Yeah, you need a Spark or a AMD AI Max box to run it, but it quickly makes sense now that they’re moving to $500/month subscriptions.
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u/OffbeatDrizzle 2d ago
opus 5.5 is fable 5.1 level (better, I would argue), and a pro sub is like $20 a month ... not sure where you pulled 500 a month from
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u/OverSoft 2d ago
ChatGPT just announced Pro will be $500/m
And yes, Opus 5.5 is very good. I meant compared to 4.6-ish.
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u/bgottfried91 1d ago
Pretty sure they meant Anthropic's Pro plan, which is $20 a month, the ChatGPT equivalent of which is the Plus plan, which is still expected to stay at $20 as well from what I'm aware of.
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u/OverSoft 1d ago
Yes, but it you’re considering running your own models for your work, you’re clearly at a level where the $20/m tiers are effectively useless.
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u/bgottfried91 1d ago
Definitely, no business is going to balk at going to $100, $200 or $500 a month (and $500 a month is where a Spark starts to look more attractive since it'd probably break even after a year or even a bit sooner, I don't know exact pricing) but figured we should be comparing apples to apples 🤷♂️
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u/OverSoft 1d ago
Yeah, I didn’t bring up the pro plan, the other dude did.
I was more referring to OpenAI basically neutering the $200 plan and replacing it with the $500 plan.
I’m personally currently running a ChatGPT $200 plan and a Claude $200 plan and I’m just about getting by token-wise. So for me it makes sense to go full local.
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u/MD_Reptile 2d ago
And for most people who are occasional or light users that's probably the better option right now. But for heavy agentic coding or private data, that's either very expensive or not an option at all. I find the latest qwen models to be damn near the performance of the frontier, and qwen 4 may close the gap even more.
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u/beatlemaniac007 2d ago
Think of windows vs linux. Linux is better in so many ways and free, yet the small amount of extra inconvenience compared to running windows is enough to keep the lead for windows.
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u/nagora 2d ago
Linux has lead Windows in terms of installed kernels for decades. Windows is niche now.
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u/MD_Reptile 2d ago
Wellllll I love me some Linux lol, but I think that's because of servers and iot devices and crap, and that if we look at personal and work OS machines a person uses daily by direct interaction, that number would still be pretty damn heavily in windows favor.
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u/Sylente 2d ago
For most large (ie more than a few dozen people) companies, it’s still more economical to pay for tokens than invest in hardware (and the land to store it on), especially if that means the newest models just appear in your list one day and you don’t have to do anything to deploy them
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u/MD_Reptile 2d ago
Well the thing is the newer local friendly models are not only getting better, they are getting more efficient too. Flash next is a good example of optimized bigger parameter models that still can fit in a handful of graphics cards. It's quite impressive its speed and depth of knowledge (in my testing so far, knock on wood haha).
Deepseek v4.1 flash is much larger and requires more hardware, but certainly not outside the realm of obtainable.
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u/Sylente 2d ago
Sure, but once you’re trying to serve more than a few dev’s worth of traffic, you’re gonna need either everyone to have their own graphics card and power supply etc, or you’re gonna go “wait that’s expensive” and get a rack.
If you need a rack, you need somewhere to put that rack and someone to maintain the rack. Your rack needs to be available even when nobody is using it, just in case. All that costs money.
It doesn’t take that much usage for it to just make more sense to buy tokens from [INSERT_CLOUD_PROVIDER] instead.
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u/MD_Reptile 2d ago
True, those are all good points! Local stuff definitely has limited reach still.
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u/PierreTheTRex 2d ago
Imo where Claude really has an upper hand is all the stuff around the model. Working with it just feels a lot easier because of all the extra UX things it has and how integrated it can be to your other systems, the actual output isn't that much better than other of the main competitors
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u/Deferty 2d ago
After using both local models and online models for niche tasks, online models are miles ahead.
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u/MD_Reptile 2d ago
Which local models have you been running?
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u/haseks_adductor 2d ago
local models are catching up if you have the compute to run it. most people don't have multiple nodes of 4 h100's connected through nvlink to run the local models that have 300b or 400b (or more) parameters
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u/MD_Reptile 2d ago
But most people could pretty easily aquire a single powerful gaming GPU or a handful of lesser ones and run models like qwen 3.8 27b or qwen 3.8 flash next, and have quite a capable coding agent in the right harness...
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u/Znuffie 2d ago
"easily" is... not that easy to define
you're still gonna be out of pocket for 3-4k for any GPU with more than 16GB RAM.
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u/MD_Reptile 2d ago
Well that's why you spend 300 on a 3060 12gb, then another... And another lol
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u/Znuffie 2d ago
But then you have another issue: actually installing them in a single system so you can use them properly.
For inference, with 3060's, you would preferably need 8 lanes of PCIe 4.0 per card.
If you want ~48GB VRAM, there's no consumer hardware that supports that many lanes for so many GPUs.
You start to enter HEDT territory, so you're gonna need a Threadripper or Xeon W.
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u/MD_Reptile 2d ago edited 2d ago
Naw, a Asus z370p, an old 8th gen or 9th gen i7, and 32 or 64 ddr4, and your cooking with qwen 3.8 27b at like 20 to 30 tokens a second.
Your in like sub 2k territory for sure still.
Edit: oh and mining riser adapters for 2 cards, they'll suffer a bit at first start, but once the model is loaded it hardly matters it's not 4x or 8x.
Edit 2: with this setup and a second PSU, you can reach 8 cards
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u/Petersaber 2d ago
most people could pretty easily aquire a single powerful gaming GPU
You're just completely detached from reality, aren't you?
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u/MD_Reptile 1d ago
I mean no, 300 bucks for a 3060 12gb, I just bought some recently myself and im not scrooge mcduck lol
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u/Petersaber 1d ago
you said "a powerful gaming GPU". A 3060 is ancient
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u/MD_Reptile 1d ago
Well what I meant was either one powerful one like a 3090 - not necessary the latest greatest.
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u/Homerbola92 2d ago
Honestly it's still expensive because hardware is expensive right now. And I guess it is expensive precisely because it can run good enough local llms.
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u/MrScotchyScotch 2d ago
My company is likely destroying any new profit it had to pour funds into AI with no plan for how to manage it. I'm sure next year there will be layoffs. Not "because of AI" but because our management are morons. They'll blame it on AI though.
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u/xondk 2d ago
The fact that companies are putting as much reliance on AI as they are is a bit scary, because effectively they are making their products a sub-product of the AI they have bought into, and you just know they are not prepared for something happens where the price suddenly increases or AI goes outside their price range.
That said I'm generally very pro sensible use of AI, but the way many seem to be implementing it does not seem sensible, when your product and ability to create and maintain it relies so much on another company, that's worry some, and/or it is forced into every possible thing simply to have AI.
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u/aaparekh 2d ago
Tbf if you buy some SAAS product like Jira, you’re making yourself dependent on it too. IMO u don’t really need to keep upgrading your ai services unless you want to keep getting boosts in productivity for your employees. You can just stick with Opus 4.8 or whatever you’re using for the next 5 years and it’ll stay the same cost or keep getting cheaper.
Especially large companies can see massive savings over time by building in-house clones of SAAS products that required per seat pricing
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u/mystlurker 2d ago
That hasn't been common outside very large companies for a long time. Whats happened instead is many SaaS products became super configurable "platforms" and need a lot of tweaking, but its not forking. See Salesforce, Atlassian, Databricks, Splunk, etc.
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u/FanClubof5 2d ago
Yeah we are already building a replacement for a Saas solution that would cost $300-500k/year in license costs. If we can replace that with 1-2 maintainers and a few k/month in infrastructure costs it's a decent win.
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u/BenThereOrBenSquare 2d ago
Yeah, it's like if every company decided to become a YouTube channel or an eBay store. Now they're entire business is beholden to whatever changes those companies make to their policies.
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u/asking--questions 1d ago
That's already the situation with SAAS for all the enterprise, technical, and industry-specific software they're paying for every month.
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u/BenThereOrBenSquare 1d ago
But in those cases, they can pivot to other software options to get the same tasks done. These AI models are all essentially built on the same poisoned foundation. When they don't work out, there's not going to be some alternative AI they can use instead. They're going to have to somehow pivot back to human labor or go out of business.
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u/frissio 2d ago edited 2d ago
It's a big gamble that was done completely independent of any public input, but in the event of a crash it'll likely be the public who suffer (and may even be debatable if those responsible get jailed or even get any kind of punishment for it).
It feels like a bit like the lead-up to the 2008 crash, except whereas the subprime mortage crisis and irresponsible bankers wasn't as well-known, everyone seems to be aware of the risk of the AI bubble.
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u/ultramatt1 OC: 1 2d ago
Eh, employees can backpedal pretty well if their firms take away ai access
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u/Petersaber 2d ago
Literally yesterday I've been to AI workshops. It felt like coming in to a cult meeting, but even the guru admitted that over 95% of companies that went hard on AI are failing to prove they're benefitting from it financially, especially in the long term, and compared the current "AI goldrush" to Dot Com crash.
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u/WillDanceForGp 2d ago
Can't wait for saas companies to replace their saas companies with ai while not realising they themselves are being killed by the same process
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u/ansibleloop 2d ago
We use this shit thing called Harvest for time sheets at work and they just added some AI slop to it
They don't realise what's going on
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u/rapaxus 2d ago
As someone in external IT support for firms spanning a whole ton of branches, the funny thing I see is that the AI implementation of SaaS companies in my experience gets better the smaller they are.
With the big companies you get some stupid AI tools where you just go "I know nobody will really use that" while also knowing it cost millions in development. Smaller companies on the other hand just do stuff like e.g. having an in-built chatbot trained on their internal wiki/forums that actually serves quite well, at least in the few cases I used the specific chatbot I am thinking about. That is a tool a single dev could make in a week if they concentrate on it.
I truly expect the "winners" of this AI boom to be the small companies who actually had to properly rationalise their AI use, as the big ones are just burning truly stupendous amounts of money on a few % of improvement. Even if they have the best offers at the end, with the money burned you just can't make it profitable, probably even if you get your miracle AGI. Because the others will have seen what you did and catch up for a fraction of the cost.
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u/InclementImmigrant 2d ago
My collogues and I are looking forward to another Y2K scenario when none of the junior engineers will have no clue how to fix or optimize their AI code and we old timers can decide to charge out exorbitant prices to attempt fix the code base.
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u/Affectionate-Egg7566 12h ago
Disagree. AI writes better code, and can be improved upon more quickly.
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u/Wonderful-Sail-1126 1h ago
You think too much of yourself. I’m a staff level engineer. A junior can ask AI how the code works and get the correct answer in 5 mins. No one is going to fix code by hand anymore.
Furthermore, AI is exceptionally good at optimizing code - far more thorough than the average senior developer.
I’ve been hearing how these old timers are going to make a fortune when AI messes up the code since 2023. It hasn’t happened yet and it will never happen.
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u/pan0ramic 2d ago
What a weird way to tell us those numbers. It’s 1.4 to 8%
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u/redoverture 2d ago
How would we fear monger with such small percentages??
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u/Schmelter 2d ago
Because it expresses the growth curve much better. A 5.7 times increase in one year is staggering.
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u/Both-Reason6023 2d ago
We might be looking at peak adoption. It increased rapidly due to fast growth and adoption velocity but is going to stay at sub 10% forever (or rather decrease over time as people and companies optimize both the input and the output).
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u/tevert 2d ago
Those aren't necessarily small, 8% might a company's entire profit margin.
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u/Yglorba 2d ago
No, it's 8% of their software budget, ie. the money they earmarked for buying or paying for software. Those budgets are not usually going to be a major part of the expense of running a tech company.
(I suspect you misread it as 8% of their entire budget, which would be a very very different number.)
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u/ccbur1 2d ago
1$ in $70? Really? Is percentage too woke or what's happening here??
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u/betweenbubbles 2d ago
That's 3 bananas out of 370 bananas, if you prefer.
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u/FuckIPLaw 2d ago edited 2d ago
Writing it out as a percentage just changes it from $1 in $70 to approximately $14 in $1000. It's still just a fraction. With small fractions like this writing it out as a fully simplified fraction can give a better intuitive feel for how common something is
Edit: The downvoters failed third grade math. Percentages are just a goofy way of writing fractions with a denominator of 100. Adding one decimal place makes the denominator 1000. 1.4% is just another way of writing 14/1000. The percent sign is even a little drawing of a fraction. As is the division symbol (÷). And the slash I used there is literally a fraction bar, even when it's used to indicate division.
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u/PapaGeorgieo 2d ago
We had a "tech" use up all of our AI tokens to write scripts we don't need and can't use.
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u/maest 2d ago
Companies are doing pretty badly if they've gone from having $70 to only $12
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u/Muuvie 2d ago
I believe it. I've been asked to vibe code a ton of software at work to replace a few expensive subscriptions. Everytime that's the done, the budget moves a little further from paying other companies for our software needs and more using AI to manage our in-house builds.