Bosses betting on AI to slash headcount and boost margins are discovering an uncomfortable truth: the strategy isn’t working.
New research from Gartner lays out the problem in stark terms. The analyst firm surveyed 350 global businesses - all with annual revenues above $1 billion, all piloting or deploying intelligent automation - and found that around 80 percent had cut staff as a result.
The returns? Elusive. Companies that reduced their workforces were just as likely to see negative outcomes or marginal gains as they were to generate any meaningful return on investment (ROI).
The conclusion? Layoffs don’t create returns, they just create vacancies.
“Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced,” said distinguished VP analyst Helen Poitevin and lead researcher on the study. “Workforce reductions may create budget room, but they do not create return. Organizations that improve ROI are not those that eliminate the need for people, but those that amplify them,” she added.
LLM prices will continue to rise and they’ll be stuck holding the bag
This is the part I’m waiting to see. My prediction; once AI providers have other companies by the nuts watch them hike prices and then we’ll hear CEO’s squealing about the unfairness of it even though they were the ones calling the shots.
It’s going to be bad, too. These companies are repportedly selling tokens for 1/10 - 1/15 the actual processing costs. Companies are already spending significantly more than they would junior developers (to generate an un-revewable amount of code). Raising peices by a factor of 20 will kill the whole project dead. They’ll need to hold out until there’s no one left who knows how to write anymore to survive that kind of price hike.
Except that it’ll never work out that way. Open models are almost as good and cost a tiny fraction of the cost of the proprietary models. There are no moats to protect their business model. Anyone can come along and eat their lunch.
AI has no path to profitability since it’s going to be commoditized. There isn’t a big enough difference between individual models to justify the price premium of paying $100/million tokens when open models cost 10¢/million tokens.
And it gets even worse when you consider specialized models; the real future is likely going to be custom training models for specific use cases, trained on the company’s data (and other data too, of course). A much smaller model can be much more successful on tasks it has been trained on. It’ll cost a tiny fraction of the compute of a mega model to train and likely beat mega models on tasks within its training domain. And it can run entirely on the company intranet, so there are no real privacy/security concerns.
Right now, the big players are giving away their compute at cents on the dollar, so there’s not much incentive to run local models. As soon as they start to push pricing to try to become profitable, companies will switch to in-house models.
OpenAI is doomed. I doubt they’ll be relevant in a decade.
Yup. And costs right now are rising while they’re still in the “get everybody hooked” stage of things, in no small part because they can’t survive at current prices. Anthropic is desperate to get to their IPO so they can have the warchest they need to actually become an established integral part of development pipelines and not just a fad.
This isn’t new. Even before AI, failing companies would use layoffs as a sort of loan on their quarterly numbers. If you lay off your employees, you’re really profitable for as long as you can continue collecting money for the work the employees had already done.
I don’t think it is just failing companies that are doing this.
COVID fundamentally broke the relationship of cost of living to the salary of certain jobs. You don’t need to pay salaries for people to live in Silicon Valley or Seattle if everyone in the department is full remote. So, if you are going to keep the job as full remote, you can base the salary on a more average cost of living and cut wages. You can use AI as an excuse for senior staff layoffs for investors, then quietly hire workers in more parts of the world with lower salaries.
Those of us around for the days when off-shoring was some kind of magic pill will remember how it wasn’t. Outsourcing to some guy in Delhi, Ohio, doesn’t seem so different; apart from time zone, maybe.
Ai isn’t the cause for this but it certainly was the enabler.
Part of the issue with off-shoring was that a lot of the work was contracted to different companies. Nowadays, large companies own the satellite offices so they have better control over the work.
Exactly what’s happening. Job postings specifically exclude larger cities now and low ball the shit out of the offer
Yep. Place I’m at is in some sort of “hiring freeze”. They’re not replacing people who left. They also told the many (probably not strictly legal) contractors that they won’t be renewing them. It’s absurd.
Same at my place. They expect AI to pick up the slack but all that’s accelerating is incidents
le gasp
