this post was submitted on 16 Feb 2026

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107

Majority of CEOs Alarmed as AI Delivers No Financial Returns (futurism.com)

submitted 22 hours ago by yogthos@lemmygrad.ml to c/technology@hexbear.net

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[–] SootySootySoot@hexbear.net 1 points 6 minutes ago* (last edited 5 minutes ago)

Also, "seeing a financial return" is not equivalent to "using AI was a good idea". There are multiple companies I've interacted with that e.g. use AI as their support tool and cut their 'real' support team hugely. And it's so furiously useless that I quickly hate the company because it can't support shit.

A lot of these companies who are seeing a financial return today, will quickly see that go away as their business stagnates/shrinks from offering a shittier service. And a lot of those that don't will be companies that can just get away with infinite enshittification and externalising their costs (eg natural monopolies, stuff people need to live, etc), thus making all of life worse even if their line goes up.

[–] Ghostie@lemmy.zip 7 points 8 hours ago

Mmmm schadenfreude

[–] BarneyPiccolo@lemmy.today 5 points 8 hours ago

These ghouls are practically giddy at the prospect of firing as many workers as possible. Sorry to disappoint them.

[–] BodyBySisyphus@hexbear.net 69 points 19 hours ago (4 children)

Pretty sure there are returns, they're just negative:

[–] SuperZutsuki@hexbear.net 1 points 31 minutes ago* (last edited 31 minutes ago)

It's very telling that they just implemented the AI without even giving its answers any sanity checks near the beginning. Could have caught it day one but no, it's magic and checking would be a waste of time brainworms

[–] jackmaoist@hexbear.net 61 points 19 hours ago (2 children)

This is like a perfect setup to commit fraud. Just blame AI for cooking your sheets and be done with it.

[–] Fossifoo@hexbear.net 12 points 12 hours ago

astronaut-1

[–] Tabitha@hexbear.net 39 points 18 hours ago (1 children)

Is AI a valid defense, or is it a confession to negligence?

[–] Le_Wokisme@hexbear.net 40 points 18 hours ago

depends how good your lawyer is

[–] Johnny_Arson@hexbear.net 25 points 17 hours ago

There are more guardrails but the company I work for relies heavily on salesforce and I wonder if this is applicable. I don't care I missed my bus and said fuck it and called in sick.

[–] miz@hexbear.net 22 points 18 hours ago

what-the-hell

[–] Goblinmancer@hexbear.net 31 points 17 hours ago (1 children)

Dont worry its all "speculated ROI" now and when shit goes up in flames give the ceos 10 billion dollars while firing everyone else.

[–] THEPH0NECOMPANY@hexbear.net 19 points 16 hours ago

That was supposed to be what AI was for in the first place, an excuse to cut staff, smh damn capitalists don't even know their own scams anymore

[–] EveningCicada@hexbear.net 50 points 20 hours ago (1 children)

you just haven't invested enough bro come on the singularity is right around the corner do another venture capital surge i promise it will be worth it

[–] LaGG_3@hexbear.net 5 points 10 hours ago

Yeah, the singularity of the economic black hole lmao

[–] Lussy@hexbear.net 18 points 18 hours ago

And we’re going to pay for it, either ways

[–] Infamousblt@hexbear.net 24 points 19 hours ago* (last edited 19 hours ago) (2 children)

This sounds damning but also doesn't mean a lot. Many companies go many many years building things before seeing a "return" on it. They make money but they are making less than they're burning in VC funds, and as they start approaching the break even point, they use that to go get more VC funds to burn to keep expanding. This is largely how the tech industry works. Very very few companies are cash flow positive during their growth phases.

It does mean that there is a risk in this investment because from a business perspective AI hasn't been proven as a valuable investment yet but it still might for at least some of these companies and unless we really do run into the physics issues with AI with regards to data center capacity and build rate it could take a decade or more for this "we aren't seeing a return yet" thing to matter

[–] yogthos@lemmygrad.ml 16 points 17 hours ago (1 children)

I agree, it's basically a completely new tool looking for a market fit. It's also worth noting that these companies are basically looking for one stellar application. If they hit on something that works really well, that's gonna be the business model. So, they're perfectly fine with most of the pilots failing if they can find one that works well.

That said, I do think there is a bubble where a lot of companies are implementing these tools without having a good fit for them, and there's a ton of money being wasted in the process. It's kind of the same thing we saw with the dotCom bubble. When it popped, there was an extinction event where most companies went belly up, but we got a ton of useful tech out of it that underpins the internet today.

I expect we'll see a similar thing happen with AI. Except, this time around there's another factor which is that there's direct competition from China. My prediction is that Chinese models will win in the end because Chinese companies aren't looking for direct monetization, they're treating models as infrastructure, sort of what we see with Linux. Most companies don't try to monetize it directly, they build stuff like AWS on top of it and that becomes the product.

I expect American companies are just going to run out of runway in the near future, and they're also getting squeezed by cheap Chinese models that are also open source. Big companies prefer running stuff on prem because they can keep their data private that way, and they can tune the models any way they want. Meanwhile, stuff like DeepSeek is orders of magnitude cheaper than Claude for individual use. So I just don't see a long term business model for models as a service, especially not at pricing like Anthropic or even Google. Vast majority of people aren't gonna pay 20 bucks a month for this stuff, let alone a 100.

[–] darkmode@hexbear.net 9 points 16 hours ago* (last edited 16 hours ago) (1 children)

Most companies don't try to monetize it directly, they build stuff like AWS on top of it and that becomes the product.

My company has an idea like this going rn but still charges per token bc it uses the vc funded companies services instead of having their own models

[–] yogthos@lemmygrad.ml 5 points 9 hours ago (1 children)

For business customers per token costs might not be a deal breaker, but for anything consumer facing it's a really tough sell in my opinion. I do expect that the cost of running models is going to come down significantly in the near future though. There is a whole bunch of recent research that identify some key optimizations that can be made. Some of the ones I've found particularly interesting here:

Deepseek-mhc https://arxiv.org/abs/2512.24880
a graph-guided code generation framework that could solve the problem of keeping a repo’s structure in context https://arxiv.org/abs/2509.16198
Hierarchical Reasoning Model https://arxiv.org/abs/2506.21734
MemOS https://arxiv.org/abs/2507.03724 (https://github.com/MemTensor/MemOS)
https://github.com/BICLab/SpikingBrain-7B
German researchers achieved 71.6% on ARC-AGI using a regular GPU for 2 cents per task https://arxiv.org/abs/2505.07859
Affordable AI assistants with knowledge graph https://arxiv.org/abs/2504.02670 (https://github.com/spcl/knowledge-graph-of-thoughts)
Nested Learning: A new ML paradigm for continual learning https://abehrouz.github.io/files/NL.pdf
Continual Low-Rank Adaptation for Pre-trained Models https://arxiv.org/abs/2502.17920
Recursive language models https://arxiv.org/pdf/2512.24601
embeddings and context https://pub.sakana.ai/DroPE/
DeepSeek Engram paper https://github.com/deepseek-ai/Engram/blob/main/Engram_paper.pdf
a 32M parameter multi vector model outperforms 600M parameter models https://arxiv.org/abs/2601.08620

Once these ideas start getting integrated, I expect that we'll see much more capable models that can run on fairly cheap hardware. Even local models will likely be quite capable for a lot of tasks. And at that point running a model as a service and charging per token is going to be a dead end.

[–] darkmode@hexbear.net 2 points 4 hours ago (1 children)

this is an incredible list of research. TYSM! In spare work time i have a small tool that tries to accomplish what #2 describes i have not clicked the link and read yet but now i will read everything

[–] yogthos@lemmygrad.ml 2 points 3 hours ago

I played around with implementing the recursive language model paper, and that actually turned out pretty well https://git.sr.ht/~yogthos/matryoshka

Basically, I spin up a js repl in a sandbox, and the agent can feed files into it, and then run commands against them. What normally happens is that the agent has to ingest the whole file into its context, but now it can just shove files into the repl, and then do operations on them akin to a db. And it can create variables. For example, if it searches for something in a file, it can bind the result to a variable and keep track of it. If it needs to filter the search later, it can just reference the variable it already made. This saves a huge amount of token use, and also helps the model stay more focused.

[–] GoodGuyWithACat@hexbear.net 11 points 17 hours ago

But it isn't a niche area, it's the major focus of corporate investment for the last year or two.

[–] plinky@hexbear.net 13 points 17 hours ago (1 children)

there were some pictures floating on twitter (in tooze circles, can't find it quickly), that there were some increases in total factor productivity for tech workers and some text adjacent fields, around 3%, with some negative correlations for teaching and i think doctors/nurses? which seems kinda less than i expected

[–] Speaker@hexbear.net 4 points 9 hours ago

How are they measuring productivity? If one of your KPIs is "Accelerate Business Objectives By Leveraging Theft Machine Synergy", the results may be a bit skewed. 😄

[–] aanes_appreciator@hexbear.net 14 points 17 hours ago

Lol for real. im soending today undoing work my ai slop loving colleague wrote on Friday. so effectively zeroed out.

[–] jack@hexbear.net 21 points 19 hours ago* (last edited 19 hours ago)

wowee who could've seen this coming

[–] ClathrateG@hexbear.net 30 points 20 hours ago* (last edited 20 hours ago)

Just a few more trillion and all the water in Tennessee and Minnesota and half the juice in the grid I swear bro

[–] WafflesTasteGood@hexbear.net 34 points 20 hours ago (2 children)

A mere 12 percent of CEOs reported that it’d accomplished both goals.

That 12 percent is either full of shit, they were running things like garbage to begin with, or the shitstorm just hasn't hit them yet.

[–] Tabitha@hexbear.net 20 points 18 hours ago

I'd say it's more likely that 95% were greedily chasing hype, went a little too all-in, and 7% of them got lucky it didn't burn them.

[–] yogthos@lemmygrad.ml 36 points 20 hours ago

I actually think around 10% success rate sounds about right here. There are niches where this tech works well, but it's being applied everywhere indiscriminately. So it makes sense that most deployments fail, but a small percentage actually finds the right niche.

[–] PaulSmackage@hexbear.net 12 points 18 hours ago

HUH, WHO WOULDA THOUGHT

[–] DasRav@hexbear.net 27 points 21 hours ago

CEO: "Wow, this could replace me, because all I really do is send an email once a day and try to say nice things about business business while trying to profit off of insider trading. And this thing won't do the last bit, so it's better then me! Everyone use the theft machine!"

Workers: "Healthcare?"

CEO: "No. Only use theft machine!"

[–] LaGG_3@hexbear.net 20 points 21 hours ago

surprised-pika