> The incentive structure for managers (and literally everyone up the chain) is to maximize headcount. More people you managed, the more power you have within the organization
Ding ding ding!
AI can absolutely reduce headcount. It already could 2 years ago, when we were just getting started. At the time I worked at a company that did just that, succesfully automating away thousands of jobs which couldn't pre-LLMs. The reason it ""worked"" was because it was outsourced headcount, so there was very limited political incentive to keep them if they were replaceable.
The bigger and older the company, the more ossified the structures are that have a want to keep headcount equal, and ideally grow it. This is by far the biggest cause of all these "failed" AI projects. It's super obvious when you start noticing that for jobs that were being outsourced, or done by temp/contracted workers, those are much more rapidly being replaced. As well as the fact that tech startups are hiring much less than before. Not talking about YC-and-co startups here, those are global exceptions indeed affected a lot by ZIRP and what not. I'm talking about the 99.9% of startups that don't get big VC funds.
A lot of the narrative on HN that it isn't happening and AI is all a scam is IMO out of reasonable fear.
If you're still not convinced, think about it this way. Before LLMs were a thing, if I asked you what the success rate of software projects at non-tech companies was, what would you have said? 90% failure rate? To my knowledge, the numbers are indeed close. And what's the biggest reason? Almost never "this problem cannot be technically solved". You'd probably name other, more common reasons.
Why would this be any different for AI? Why would those same reasons suddenly disappear? They don't. All the politics, all the enterprise salesmen, the lack of understanding of actual needs, the personal KPIs to hit - they're all still there. And the politics are even worse than with trad. enterprise software now that the premise of headcount reduction looms larger than ever.
Yes, and it’s instructive to see how automation has reduced head count in oil and gas majors. The reduction comes when there’s a shock financially or economically and layoffs are needed for survival. Until then, head count will be stable.
Trucks in the oil sands can already operate autonomously in controlled mining sites, but wide adoption is happening slowly, waiting for driver turnover and equipment replacement cycles.
> The bigger and older the company, the more ossified the structures are that have a want to keep headcount equal, and ideally grow it.
I don't know, most of the companies doing regular layoffs wheneveer they can get away with it are pretty big and old. Be it in tech - IBM/Meta/Google/Microsoft, or in physical things - car manufacturers, shipyards, etc.
Through top-down, hard mandates directly by the exec level, absolutely! They're an unstoppable force, beating those incentives.
The execs aren't the ones directly choosing, overseeing and implementing these AI efforts - or in the preceding decades, the software efforts. 9 out of 10 times, they know very little about the details. They may ""spearhead"" it in so far that's possible, but there's tonnes of layers inbetween with their own incentives which are required to cooperate to actually make it work.
If the execs say "Whole office full-time RTO from next month 5 days a week", they really don't depend on those layers at all, as it's suicide for anyone to just ignore it or even fake it.
> At the time I worked at a company that did just that, succesfully automating away thousands of jobs which couldn't pre-LLMs.
which company is this? surely they wouldve made a big splash for doing something no one else has been able to do.
Did you not see the backlash the Duolingo CEO got and how hard he backtracked? Coming out and saying "We're replacing a big bunch of people with LLMs" is about the worst PR you can get in 2025, it's really an wful idea for anyone but maybe pure B2B companies that are barely hanging on and super desperate for investor cash.
This was a big, traditional non-tech company.
Also as implied, these were cheap offshore contracting jobs being replaced. Still magnitudes more expensive than LLMs, making it very "worth it" from a company perspective. But not prime earnings call material.
Everyone in the industry also knows that it's not particularly unique, far away from something no one has been able to do. Go look at the job markets for translation, data entry, customer support compared to 2 years ago. And as mentioned, even junior web devs.