Companies discover AI is expensive when employees actually use it
Once again, AI is a money incinerator.
The artificial intelligence revolution has reached the point where management begs employees to stop feeding PDFs into the robot so it can burp out PowerPoint decks nobody wanted in the first place.
The entire AI bubble is built on the idea that someday, somehow, customers will pay for the insane costs of using AI. This shows the system collapse is already here. The customers want to cut back. Once again, AI is a money incinerator.
The news highlights a major shift in the tech industry and other companies that use AI: the wave of uninhibited AI growth is over. Some AI providers like GitHub are now charging customers per token rather than a flat subscription fee, leading some companies to burn through their tokens. Uber recently capped employees’ use of AI tools like Claude Code and Cursor; that came after Uber told employees to use AI as much as possible and Uber’s CTO said the company had blown its entire AI budget in four months. And Accenture itself reportedly started requiring senior staff to start using AI or risk losing out on promotions.
Faced with actually paying for it, corporations want to cut AI costs. When the investor capital is gone, so go the non-consensual deep fakes.
From a comment I posted to r/LocalLLM on reddit, about why I am using AI that I run on my own computer, rather than models in the cloud. Local AI is far less capable, and slower. But I think that's temporary:
I don't want to use the frontier models for a few reasons. 1) I am retired, and this is a hobby. I don't want to put a lot of money into token fees. 2) My understanding is that frontier models are heavily subsidized. I don't want to get addicted to crack. 3) I think the future is local LLMs. They have to get better, in absolute and in relative terms. Models are so ridiculously expensive and resource-intensive to train and use, and its still very early days. There will have to be vast improvements in this area, just based on multiple financial incentives. 4) I view this as an updated version of the mainframe/PC battle from the 80s and 90s. PC-based architectures dominate except in a few places. PC descendents (by which I mean Intel/ARM based Linux systems) are vastly more powerful than they used to be. I think the same will happen with local models relative to frontier models. 5) Due to intense competition in the AI space, and the differing interests of different players, someone is always going to undercut competition by releasing a newer, more capable open source model. It's a race to the bottom.
Wait... the unspoken 'money saving' aspect of "A.I." is not [southpark]"they took our jebs!"? That is, it was presumed *the* plan was c-suite replaces everyone down to janitor with "A.I." and oh so much is saved in health care, pensions, ...yellow sticky notes; that's not how they intend to "use it"? they just don't want the existing hires to use it? [:confused cuttlefish emoji:]