I agree that the former is a strong signal. However the latter doesn't tell you anything without further context: did interest rates go up, because the economy was strong, or did rising interest rates dampen the economy?
(It's similar to how you can't tell how hot it is in my apartment, purely from looking at my heating bills: does a low heating bill mean that it's cold in my flat, because I'm too cheap too heat? Or does a low heating bill mean it's summer and really hot anyway?)
Stupendous loads of money have been allocated to a solution looking for a problem to solve.
https://www.gartner.com/en/newsroom/press-releases/2025-06-2...
It doesnt matter. Whether it went from strong -> weak or weak -> weaker is beside the point, the question is if genAI is the main reason for entry level job loss and raising interest rates are another possible answer.
Yeah it can correlate with the end of a post pandemic hiring boom, and it can correlate with the bank rate. But no matter what it also correlates with the rise of AI.
All are true and causation cannot be established for any of the 3 through just an observational study.
But specifically entry level is down significantly since Nov 2022.
All of your points - interest rates, post pandemic hiring boom would apply to market as a whole.
Not saying it’s causation like the article claims, but there’s at least some correlation trend.
Growth was weak to unremarkable although the hiring market was good for job seekers at the time shortly before the interest rises were introduced.
These categories have seen broad application of AI tools:
- CS, you’ll most likely talk to an LLM for first tier support these days.
- Account management comprises pressing the flesh (human required) and responding to emails - the latter, AMs have seen their workload slashed, so it stands to reason that fewer are required.
- Paralegal - the category has been demolished. Drafting and discovery are now largely automated processes.
- Data analysis - why have a monkey in a suit write you barely useful nonsense when a machine can do the same?
So - yeah, it’s purely correlative right now, but I can see how it being causative is perfectly plausible.
Given that AI tools are only really used for white collar work, but white collar professions have not been declining faster than entry level jobs in hospitality, vocational jobs, nursing or transportation (all of which are down), this gives you a pretty decent natural control group.
The whole debate about bifurcation of the labour market, that entry level coders are having a harder time than they used to, precedes even the pandemic or recent economic woes.
If you've ever tried to use AI to help with this kind of analysis, you might find this to be more inevitable than it is funny.
It's really, really, really good at confidently jumping to hasty conclusions and confirmation bias. Which perhaps shouldn't be surprising when you consider that it was largely trained on the Internet's proverbial global comments section.
Kind of like entry level software engineers.
I am kidding, I believe the market has more to do with tax changes than AI. I just couldn't pass up the joke.
But the original comment I first replied to seemed to suggest that high interest rates should lead us to deduce a weak economy.
If I am running a factory that use to create carriages and now creates cars, I need people who can create cars now. If I want to expand the number of customers I serve, I need to hire more people.
If I am a software company, I don’t need to scale the number of software engineers I hire to serve more customers.
Since gen AI has been a thing, I mostly pivoted to more strategy based cloud consulting than hands on keyboard software development. But before Gen AI, I would have needed a couple of junior developers to do the grunt work of implementing well defined implementations. Now I can do both the strategy and implementations in the same amount of time.
Even before Gen AI the entire reason that software engineers get paid so much because software development has high fixed costs but near zero marginal costs. No other industry has been like that historically.
We don’t know if 2 causal events will stack. It may be that one causal event does so much damage that the second causal event can’t do much.
It’s like firing a bullet and throwing a stone at a window. Whichever came first will mask the causative nature of the second. The window can't break twice.
I have never once said “it sure would be nice to have a few more junior devs. That would really increase our velocity”.
As someone who is responsible for getting projects done on time, within budget and meets requiremenga, why would I push for hiring fresh entry level devs instead of hiring a mid level dev with experience for only 20-30% more? The spread isn’t that great for enterprise developers.
It’s even more true now that I can push for hiring a mid level devs working remotely in East BumbleFuck South Dakota for peanuts.
For what’s its worth, I am classifying seniority by the ability to work at certain “scope” and “deal with ambiguity”, not someone who “codez real gud” and can reverse a b tree on the whiteboard
https://www.levels.fyi/blog/swe-level-framework.html
And there is a diminishing return on new features. If Google fired every developer not involved in search and ads, they could survive another decade or so and probably end up being more profitable since they can’t produce new good profitable products to save their lives
But also, "AI" is polysemous. There's "AI" the academic field, and machine learning is a subset of that field. But there's also "AI" the marketing term, which is much more well-known nowadays. And for that meaning of the term, it's the other way around -- it's a subset of machine learning.
Under either definition, though, I agree it doesn't make much sense to talk about them as if they are two different things, because either way one is just a particular kind of the other.