One open question here is whether we’re seeing youth employment decrease because AI is effectively replacing entry level workers in these fields, or because executives wrongly *think* AI can or will soon be able to do so?
I’ve played around with AI in my job, which I’m pretty sure Anthropic would classify as highly exposed to AI (think something similar to accounting). It’s really helpful for a small number of tasks that comprise maybe 10% of my job, but pretty much useless at the rest. If it’s impacting entry level jobs in my field at all, I really think it’s more that those jobs will change a bit than be totally replaced. I suspect that at some point once the AI hype fever breaks, companies will simply reconfigure entry level jobs a bit to incorporate AI and begin hiring again. I could be wrong, but that’s what I’d bet on right now.
I’m not sure why 10% of junior sales and marketing was laid off at a stroke and rehired a year later, or why junior software engineers have a hard inflection at October 2022, but those seem much likelier to be executive decisions — they just don’t fit any reasonable S-shaped adoption curve.
And something I worry about, how are we going to get capable workers without their having first done these entry level jobs. There is the perpetual catch-22 of companies who want to hire people with 3 years experience to do an entry level job (Or any job really). But what I think is more crucial is that you can't doo the next job up if you haven't learned the lessons before. You need to be an intern to be a resident, a resident to be an attending etc. How will they know how to do anything? A lot of the frustration with the current generation is the expectation they should just know it. Nobody wants to teach. Teaching isn't a brief walk through of procedures either.
It is logical to me that AI would impact some entry level jobs first. The effectiveness of AI bs humans is still to be determined. If AI does replace many “entry level” jobs, where do the humans receive the training necessary to take over the more experienced roles that AI does not seem (at least yet) to be capable of replacing?
Anyone who has tried to use the "new customer service experience" is in for a huge surprise. If AI is being implemented here, it is a huge failure. I tried filing a long-term healthcare claim online with a major US insurer. I could not do it as the website did not include the name of the person the claim was being filed for. I called customer service and went through two or three different menus and was asked at the end of each unsuccessful try if I would like to complete a customer service survey. I finally get a real person with a heavy foreign accent who after five minutes of collecting information said she could not help me and gave me another phone number. I called that number and got through to a person who took the same information again and said I would be contacted within five workdays by a claims manager!!!
This one experience is not unique as I've had other unpleasant experiences in the past couple of years with "customer service" at other major US companies. Sometimes real people cannot be replaced by machines.
Insightful, thoughtful, and well-researched as always. Thank you, Derek! This article along with your recent one on the social implications of AI as a therapist/counselor were so interesting and thought-provoking.
As a CS professor at a liberal arts college, I often feel like I'm teaching my students to fly the plane while I'm also learning how to fly it and the controls are constantly being rearranged.
The shape of the line for 22-25 year old software devs (Figure 1) is interesting. It shows the big drop starting in late 2022 and continuing for most of 2023, then a period of relative stability until the second part of 2024, followed by a second steep drop into 2025.
A possible story is that the first drop was primarily due to overall conditions and post-COVID hiring pullback. The early LLMs were not particularly effective at coding. The second drop, though, roughly lines up with the introduction of Claude Sonnet 3.6 in October 2024, which was a big step up in coding ability and kicked off the current wave of agentic programming tools. So the first wave of job losses may have been partially driven by AI hype, but the second is driven by agentic tools increasing the productivity of mid-career devs.
There's some evidence that CS enrollments are softening as students look to less risky majors. I'm still seeing good numbers in my intro course, but lower throughput to later courses. I think we're entering a period of reduced demand for CS as a standalone major, but much higher demand for programming across the curriculum. Using AI to solve problems with code is an emerging skill that's going to transform a lot of disciplines.
Indeed, before the TCJA’s enactment, businesses deducted the total amount of R&D expenditures as an expense in the taxable year. Beginning in 2022, all costs related to R&D must now be amortized over five years for US-based companies or 15 years for non-US companies.”
Software jobs are definitely often classified in R&D, and this new rule generated a massive headwind from
2022 until repeal in July 2025 (via the OBBB). Obviously the timing overlaps with end of Covid, so it’s tricky.
Two questions:
1. How does this interact with the age cohort of the software developers?
2. How will hiring into these jobs change now that the OBBB has passed?
Great write up, thanks. It would be useful to consider supply effects here. We are producing more CS grads each year, so at some point you’d expect labor market saturation even without AI. Also, the first group that AI will replace are college students — at least the ones who are willing to be replaced by letting AI do their coursework. Which raises the question about whether recent grads are comparable to past ones. Love to learn more.
yeah, i think any claims about AI affecting junior software developer jobs needs to address the fact that hiring in the tech industry peaked in mid-2022 and has not even come close to rebounding in the subsequent 3 years, so of course there will be a headcount bias towards older employees since then
I'm interested in learning about the potential long-term impact of entry-level workers not learning tasks that are easily automated, assuming the data continues to support this and becomes more robust. I suspect that certain tasks which can be automated are actually important. The question then becomes: which entry-level tasks? I have some ideas in mind, but they require more thought before I comment further.
Hiring trends bounce around a great deal at the occupational and sectoral levels, sometimes in tandem with the aggregate economy, but sometimes not. While I haven't read the underlying paper, what's presented in this article doesn't seem like a slam-dunk confirmation of AI effects. Basically, as with some of the other commenters, I'd be hesitant to declare the Hand of God at work in what could plausibly be secular changes in hiring rates. But maybe the article undersells the full breadth of evidence presented in the paper?
It’s no surprise to me that AI can take entry-level jobs but I think that’s also because the issue is further up in the pipeline. The education system has been a fossil and AI just exposed how machine-like the outputs students are being trained on are.
Would be important to look at how much energy these data centers are going to require. It is projected by 2030 the energy needs will equal the entire nation of Japan. The water demands for cooling are going to be excessive. This seems to be completely ignored.
This issue may be linked to another topic periodically debated just as fiercely -- college or not. It seems possible to me that AI is replacing new college grads in "vulnerable" positions but not those in health care, customer service, etc., because the latter category is made up of jobs that are often filled by non-college grads, but traditionally have had quality issues because of a combination of high turnover and ill-prepared high school grads. Is it possible that companies are pairing non-grads with AI and thereby elevating the quality of performance in these positions without a corresponding increase in payroll costs? If this strategy is widely used and successful, it may account for some of the increases in jobs where AI "complements" employees rather than replacing them.
One open question here is whether we’re seeing youth employment decrease because AI is effectively replacing entry level workers in these fields, or because executives wrongly *think* AI can or will soon be able to do so?
I’m not closed to the idea that AI is displacing some young workers, but I also see out of touch executives and investors buying into a lot of AI hype that I’m not seeing reflected on the ground. There was a recent study that showed the vast majority of AI initiatives fail: https://fortune.com/2025/08/21/an-mit-report-that-95-of-ai-pilots-fail-spooked-investors-but-the-reason-why-those-pilots-failed-is-what-should-make-the-c-suite-anxious/
I’ve played around with AI in my job, which I’m pretty sure Anthropic would classify as highly exposed to AI (think something similar to accounting). It’s really helpful for a small number of tasks that comprise maybe 10% of my job, but pretty much useless at the rest. If it’s impacting entry level jobs in my field at all, I really think it’s more that those jobs will change a bit than be totally replaced. I suspect that at some point once the AI hype fever breaks, companies will simply reconfigure entry level jobs a bit to incorporate AI and begin hiring again. I could be wrong, but that’s what I’d bet on right now.
I’m not sure why 10% of junior sales and marketing was laid off at a stroke and rehired a year later, or why junior software engineers have a hard inflection at October 2022, but those seem much likelier to be executive decisions — they just don’t fit any reasonable S-shaped adoption curve.
I think there is some emerging evidence you may be right. Companies were cautious about hiring for a time, but that may be picking back up.
Take a look at the JOLTS job openings for Information for the most recent month currently available (June 2025): https://fred.stlouisfed.org/series/JTU5100JOR
We're at the highest rate of job openings in this industry since 2022!
I am doing a more detailed writeup about how to interpret these numbers, should be published by mid-September.
That was my take as well. Not replaced, but not hired yet because of hype and an overly optimistic executive take on usefulness.
I suspect we will see reversals as with Klarna. See https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ for metrics - AI actually made programmers slower although they thought they were faster.
And something I worry about, how are we going to get capable workers without their having first done these entry level jobs. There is the perpetual catch-22 of companies who want to hire people with 3 years experience to do an entry level job (Or any job really). But what I think is more crucial is that you can't doo the next job up if you haven't learned the lessons before. You need to be an intern to be a resident, a resident to be an attending etc. How will they know how to do anything? A lot of the frustration with the current generation is the expectation they should just know it. Nobody wants to teach. Teaching isn't a brief walk through of procedures either.
It is logical to me that AI would impact some entry level jobs first. The effectiveness of AI bs humans is still to be determined. If AI does replace many “entry level” jobs, where do the humans receive the training necessary to take over the more experienced roles that AI does not seem (at least yet) to be capable of replacing?
Anyone who has tried to use the "new customer service experience" is in for a huge surprise. If AI is being implemented here, it is a huge failure. I tried filing a long-term healthcare claim online with a major US insurer. I could not do it as the website did not include the name of the person the claim was being filed for. I called customer service and went through two or three different menus and was asked at the end of each unsuccessful try if I would like to complete a customer service survey. I finally get a real person with a heavy foreign accent who after five minutes of collecting information said she could not help me and gave me another phone number. I called that number and got through to a person who took the same information again and said I would be contacted within five workdays by a claims manager!!!
This one experience is not unique as I've had other unpleasant experiences in the past couple of years with "customer service" at other major US companies. Sometimes real people cannot be replaced by machines.
Insightful, thoughtful, and well-researched as always. Thank you, Derek! This article along with your recent one on the social implications of AI as a therapist/counselor were so interesting and thought-provoking.
It’s true - no ordinary technology has ever caused temporary job losses.
As a CS professor at a liberal arts college, I often feel like I'm teaching my students to fly the plane while I'm also learning how to fly it and the controls are constantly being rearranged.
The shape of the line for 22-25 year old software devs (Figure 1) is interesting. It shows the big drop starting in late 2022 and continuing for most of 2023, then a period of relative stability until the second part of 2024, followed by a second steep drop into 2025.
A possible story is that the first drop was primarily due to overall conditions and post-COVID hiring pullback. The early LLMs were not particularly effective at coding. The second drop, though, roughly lines up with the introduction of Claude Sonnet 3.6 in October 2024, which was a big step up in coding ability and kicked off the current wave of agentic programming tools. So the first wave of job losses may have been partially driven by AI hype, but the second is driven by agentic tools increasing the productivity of mid-career devs.
There's some evidence that CS enrollments are softening as students look to less risky majors. I'm still seeing good numbers in my intro course, but lower throughput to later courses. I think we're entering a period of reduced demand for CS as a standalone major, but much higher demand for programming across the curriculum. Using AI to solve problems with code is an emerging skill that's going to transform a lot of disciplines.
Did you guys look at Section 174 of the TCJA?
https://www.thomsonreuters.com/en-us/posts/tax-and-accounting/section-174-expenditures/
Indeed, before the TCJA’s enactment, businesses deducted the total amount of R&D expenditures as an expense in the taxable year. Beginning in 2022, all costs related to R&D must now be amortized over five years for US-based companies or 15 years for non-US companies.”
Software jobs are definitely often classified in R&D, and this new rule generated a massive headwind from
2022 until repeal in July 2025 (via the OBBB). Obviously the timing overlaps with end of Covid, so it’s tricky.
Two questions:
1. How does this interact with the age cohort of the software developers?
2. How will hiring into these jobs change now that the OBBB has passed?
I know a division of folks, writers, laid off and explicitly replaced with AI. Definitely it is taking jobs.
Great write up, thanks. It would be useful to consider supply effects here. We are producing more CS grads each year, so at some point you’d expect labor market saturation even without AI. Also, the first group that AI will replace are college students — at least the ones who are willing to be replaced by letting AI do their coursework. Which raises the question about whether recent grads are comparable to past ones. Love to learn more.
yeah, i think any claims about AI affecting junior software developer jobs needs to address the fact that hiring in the tech industry peaked in mid-2022 and has not even come close to rebounding in the subsequent 3 years, so of course there will be a headcount bias towards older employees since then
I'm interested in learning about the potential long-term impact of entry-level workers not learning tasks that are easily automated, assuming the data continues to support this and becomes more robust. I suspect that certain tasks which can be automated are actually important. The question then becomes: which entry-level tasks? I have some ideas in mind, but they require more thought before I comment further.
Yes. I too thought and what are they not learning that they need to have experienced in the future.
“(M)ost people live in the past, hanging onto stale narratives and outdated models”
Underrated, widely applicable point!
Hiring trends bounce around a great deal at the occupational and sectoral levels, sometimes in tandem with the aggregate economy, but sometimes not. While I haven't read the underlying paper, what's presented in this article doesn't seem like a slam-dunk confirmation of AI effects. Basically, as with some of the other commenters, I'd be hesitant to declare the Hand of God at work in what could plausibly be secular changes in hiring rates. But maybe the article undersells the full breadth of evidence presented in the paper?
It’s no surprise to me that AI can take entry-level jobs but I think that’s also because the issue is further up in the pipeline. The education system has been a fossil and AI just exposed how machine-like the outputs students are being trained on are.
Would be important to look at how much energy these data centers are going to require. It is projected by 2030 the energy needs will equal the entire nation of Japan. The water demands for cooling are going to be excessive. This seems to be completely ignored.
This issue may be linked to another topic periodically debated just as fiercely -- college or not. It seems possible to me that AI is replacing new college grads in "vulnerable" positions but not those in health care, customer service, etc., because the latter category is made up of jobs that are often filled by non-college grads, but traditionally have had quality issues because of a combination of high turnover and ill-prepared high school grads. Is it possible that companies are pairing non-grads with AI and thereby elevating the quality of performance in these positions without a corresponding increase in payroll costs? If this strategy is widely used and successful, it may account for some of the increases in jobs where AI "complements" employees rather than replacing them.