New Harvard's study (62M workers, 285k firms) shows firms adopting generative AI cut junior hiring sharply while continuing to grow senior roles — eroding the bottom rungs of career ladders and reshaping how careers start.
If entry-level roles are shrinking, how should companies rethink talent development?
Without the traditional “bottom rungs,” how do we grow future seniors if fewer juniors ever get the chance to start?
The question is... is this based on existing capability of LLMs to do these jobs? Or are companies doing this on the expectation that AI is advanced enough to pick up the slack?
I have observed a disconnect in which management is typically far more optimistic about AI being capable of performing a specific task than are the workers who currently perform that task.
And to what extent is AI-related job cutting just an excuse for what management would want to do anyway?
Interesting. However just because this is true right now doesn't mean it will be true going forward. Unique to the current moment is that there are simultaneously (1) high interest rates and a challenging economy (2) a narrative that AI adoption should enable cutting junior roles. This could lead to companies that would anyway be doing layoffs choosing to lay off or not hire juniors, and replace with AI adoption.
To really test the implied theory that using AI enables cutting junior hiring, we need to see it in a better economy, in otherwise growing companies, or with some kind of control (though not sure how this would really be possible).
What happens when companies refuse to hire, even though there is an obvious need? It has to lead to reduced growth. If the majority of companies do this, I would think it would lead to a severe deflationary cycle.
Generative AI may automate some entry-level tasks, but young professionals are not just “replaceable labor.” They bring growth potential, adaptation, and social learning. Without frameworks to manage AI’s role, we risk undermining the very training grounds that prepare the next generation of experts.
The tragedy of the commons: companies acting in their self interest at the expense of the industry by drying up the workforce pipeline. The next generation will pay, like when America stopped producing hardware.
In the future, there will be two kinds of companies:
1. Those that encourage people to use AI agents aggressively to increase productivity.
2. Those that encourage people to use AI agents aggressively to be more productive while still hiring young people.
Which type of company will be more innovative, productive, and successful in the long run?
We had some marketing folks give us a company-wide demo of Chat GPT and some other Gen AI tools and showed us how cool it is and how quick they can make stylish and sophisticated pitch decks and marketing materials now.
And the entire time I'm watching this I'm just thinking that they don't realize that they are only demonstrating the tools that are going to replace their own jobs. Kinda sad, really. Demand for soft skills and creatives is going to continue to decline.
The economic turmoil in the US is hollowing out the entry level jobs, AI is just the cover companies are using. The constant tariff changing means that companies have to be very pessimistic in their long term planning, as any assumptions they make can be turned on their head with no notice.
Another way to look at it is that legacy jobs have no future therefore there is no point bringing in the next generation into a dying system.
Another way to look at it is that hiring is fine, and that the vain entitled generation we all suspected was going to emerge feels that a job should absolutely be available to them, and immediately.
Another way to look at it is that journalism has been dead for quite a while, and writing about the same fear-based topics like “omg hiring apocalypse” is what makes these people predictable money (along with other topics).
Another way to look at it is that we raised a generation of narcissistic parents and children that have been going “omg grades”, “omg good college”, “omg internship”, “omg job” for so long that that these lamentations feel normalized. A healthy dose of stfu was never given to them. Neurotic motherfuckers.
The pessimistic reading is well-represented, so here's another: AI changes the definition of "entry-level", but it doesn't eliminate the class of professional labor that experienced workers would rather not do.
Until AI can do literally everything we can, that class of work will continue to exist, and it'll continue to be handed to the least experienced workers as a way for them to learn, get oriented, and earn access to more interesting problems and/or higher pay while experienced folks rest on their laurels or push the state of the art.
Today they're admitting AI is hollowing out entry-level jobs. The reality is that it can and will replace mid-level and eventually even quite senior jobs.
Why?
It's already doing a lot of the loadbearing work in those mid-level roles too now, it's just a bit awkward for management to admit it. One common current mode of work is people using AI to accomplish their work tasks very quickly, and then loafing a bit more with the extra time. So leaders refrain from hiring, pocket the savings, and keep a tight lid on compensation for those who remain.
At some point they'll probably try to squeeze the workforce for some additional productivity, and cut those who don't deliver it. Note that the "ease" of using AI for work tasks will be a rationale for why additional compensation is not warranted for those who remain.
> the largest effects in wholesale and retail trade
Hard for me to believe that AI in its current state is hollowing out junior shop assistant and salesperson roles. Either those jobs were already vulnerable to "dumb" touchscreen kiosks or they require emotional intelligence and embodied presence that LLMs lack.
It’s really hard to adjust for economic factors here. I am in agreement with skepticism in this thread as job numbers got revised downward heavily in both 2024 and 2025 (too negatives in some months) indicating a poor economic situation.
I am confused about how to feel about the data the paper is based on. If you look at the paper, the data description is:
"Our primary data source is a detailed LinkedIn-based resume dataset provided by Revelio Labs ...
We complement the worker resume data with Revelio’s database of job postings, which tracks recruitment activity by the firms since 2021 ...
The final sample consists of 284,974 U.S. firms that were successfully matched to both employee position data and job postings and that were actively hiring between January 2021 and March 2025.3 For these firms, we observe 156,765,776 positions dating back to 2015 and 245,838,118 job postings since 2021, of which 198,773,384 successfully matched with their raw text description."
They identified 245 million job postings from 2021 forward in the United States? I mean the U.S. population is like 236 million for the 18-65 age group (based on wikipedia, 64.9% of 342 total population).
And they find a very small percentage of firms using generative AI:
"Our approach allows us to capture firms that have actively begun
integrating generative AI into their operations. By this measure, 10,599 firms, about 3.7 percent of our sample, adopted generative AI during the study period."
Maybe I am wildly underestimating just how much LinkedIn is used worldwide for recruiting? As a tech person, I'm also very used to seeing the same job listing re-listed by what seems to be a large number of low-effort "recruiting" firms on LinkedIn.
I think for trying to figure out how generative AI is affecting entry-level jobs, I would have been much more interested in some case studies. Something like find three to five companies (larger than startups? 100+ employees? 500+?) that have decided to hire fewer entry-level employees by adding generative AI into their work as a matter of policy. Then maybe circling back from the case studies to this larger LinkedIn dataset and tied the case study information into the LinkedIn data somehow.
I heard an argument that the valuation of AI/ AI-adjacent firms only makes sense if 1) companies grow their aggregate top-line revenues by multiple trillion dollars of 2) this amounts to the potential savings from gutting knowledge-based employment across an economy.
Of course in the long run a chronically underemployed economy will have little demand for products and services, but that is beyond the scope of companies who, in general, are focused on winning short term and zero-sum market capture. However I believe that while a billion dollar valuation is a market and strategy problem, a trillion dollar valuation is a political problem - and I would hope that a mandate of broad gainful employment translates to political action - although this remains to be seen.
39 comments
[ 3.3 ms ] story [ 48.6 ms ] threadThe question is... is this based on existing capability of LLMs to do these jobs? Or are companies doing this on the expectation that AI is advanced enough to pick up the slack?
I have observed a disconnect in which management is typically far more optimistic about AI being capable of performing a specific task than are the workers who currently perform that task.
And to what extent is AI-related job cutting just an excuse for what management would want to do anyway?
To really test the implied theory that using AI enables cutting junior hiring, we need to see it in a better economy, in otherwise growing companies, or with some kind of control (though not sure how this would really be possible).
This is cause for government intervention.
Is this a case of "correlation does not imply causation?"
And the entire time I'm watching this I'm just thinking that they don't realize that they are only demonstrating the tools that are going to replace their own jobs. Kinda sad, really. Demand for soft skills and creatives is going to continue to decline.
Dev jobs too.
Entry-level jobs get "hollowed out" in a stagnant economy regardless of "AI".
AI = not hiring because no new work but spin as a "AI" . Markets are hungry of any utterance of the the word AI from the CEO.
so ridiculous. but we've collectively decided to ignore BS as long as we can scam each other and pray you are not the last one holding the bag.
Another way to look at it is that hiring is fine, and that the vain entitled generation we all suspected was going to emerge feels that a job should absolutely be available to them, and immediately.
Another way to look at it is that journalism has been dead for quite a while, and writing about the same fear-based topics like “omg hiring apocalypse” is what makes these people predictable money (along with other topics).
Another way to look at it is that we raised a generation of narcissistic parents and children that have been going “omg grades”, “omg good college”, “omg internship”, “omg job” for so long that that these lamentations feel normalized. A healthy dose of stfu was never given to them. Neurotic motherfuckers.
Until AI can do literally everything we can, that class of work will continue to exist, and it'll continue to be handed to the least experienced workers as a way for them to learn, get oriented, and earn access to more interesting problems and/or higher pay while experienced folks rest on their laurels or push the state of the art.
they rather pay people to sit in a room pressing a button every hour than have them loitering around on UBI
either that or in the pod
Why?
It's already doing a lot of the loadbearing work in those mid-level roles too now, it's just a bit awkward for management to admit it. One common current mode of work is people using AI to accomplish their work tasks very quickly, and then loafing a bit more with the extra time. So leaders refrain from hiring, pocket the savings, and keep a tight lid on compensation for those who remain.
At some point they'll probably try to squeeze the workforce for some additional productivity, and cut those who don't deliver it. Note that the "ease" of using AI for work tasks will be a rationale for why additional compensation is not warranted for those who remain.
Hard for me to believe that AI in its current state is hollowing out junior shop assistant and salesperson roles. Either those jobs were already vulnerable to "dumb" touchscreen kiosks or they require emotional intelligence and embodied presence that LLMs lack.
The US is going through a lot of upheaval, which whether you think is positive or negative, is unique, and a confounding factor for any such research.
"Our primary data source is a detailed LinkedIn-based resume dataset provided by Revelio Labs ...
We complement the worker resume data with Revelio’s database of job postings, which tracks recruitment activity by the firms since 2021 ...
The final sample consists of 284,974 U.S. firms that were successfully matched to both employee position data and job postings and that were actively hiring between January 2021 and March 2025.3 For these firms, we observe 156,765,776 positions dating back to 2015 and 245,838,118 job postings since 2021, of which 198,773,384 successfully matched with their raw text description."
They identified 245 million job postings from 2021 forward in the United States? I mean the U.S. population is like 236 million for the 18-65 age group (based on wikipedia, 64.9% of 342 total population).
And they find a very small percentage of firms using generative AI:
"Our approach allows us to capture firms that have actively begun integrating generative AI into their operations. By this measure, 10,599 firms, about 3.7 percent of our sample, adopted generative AI during the study period."
Maybe I am wildly underestimating just how much LinkedIn is used worldwide for recruiting? As a tech person, I'm also very used to seeing the same job listing re-listed by what seems to be a large number of low-effort "recruiting" firms on LinkedIn.
I think for trying to figure out how generative AI is affecting entry-level jobs, I would have been much more interested in some case studies. Something like find three to five companies (larger than startups? 100+ employees? 500+?) that have decided to hire fewer entry-level employees by adding generative AI into their work as a matter of policy. Then maybe circling back from the case studies to this larger LinkedIn dataset and tied the case study information into the LinkedIn data somehow.
Of course in the long run a chronically underemployed economy will have little demand for products and services, but that is beyond the scope of companies who, in general, are focused on winning short term and zero-sum market capture. However I believe that while a billion dollar valuation is a market and strategy problem, a trillion dollar valuation is a political problem - and I would hope that a mandate of broad gainful employment translates to political action - although this remains to be seen.