Does technological change increase employment, or decrease employment? The answer depends on what you believe about the technological change. If the technological change primarily automates tasks that were previously done by human workers, then it may decrease the demand for labour and reduce employment [*]. On the other hand, if the technological change primarily makes workers more productive, so that they generate more value for their employers, then it may increase the demand for labour and increase employment [**].
Which of those two situations is AI creating? In reality, it's probably a bit of both. However, which effect is stronger? We can get a sense of where things are at from this recent working paper by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen (all Stanford University). They use data from ADP, the largest payroll processing firm in America, which contains records on between 3.5 and 5 million workers each month between January 2021 and July 2025. Using this data, Brynjolfsson et al. demonstrate six key facts about the labour market over that time:
- First, we find substantial declines in employment for early-career workers in occupations most exposed to AI, such as software development and customer support.
- Second, we show that economy-wide employment continues to grow, but employment growth for young workers has been stagnant.
- Third, entry-level employment has declined in applications of AI that automate work, with muted effects for those that augment it.
- Fourth, these employment declines remain after conditioning on firm-time effects, with a 13% relative employment decline for young workers in the most exposed occupations.
- Fifth, these labor market adjustments are more visible in employment than in compensation.
- Sixth, we find that these patterns hold in occupations unaffected by remote work and across various alternative sample constructions.
The first key fact is demonstrated by looking across all occupations. However, it is most clearly seen in Figure 1 from the paper, which shows how the number of workers (by age group) employed as software developers or customer service representatives (two of the occupations most cited in the media as being affected by AI) have changed compared with October 2022:
Notice how the blue line (employment of early career workers aged 22 to 25 years) trends downwards, starting from 2022, while employment of the most senior workers (especially those aged 35 years and over) continue to trend upwards.
The second key fact builds on this, to show the trend is apparent when you pool all workers together, as demonstrated in Figure 4 from the paper:
Note that the trends are not as wildly different as they are for software developers or customer service representatives, but remember that figure shows the trends across all workers, including those in jobs like nurses, welders, or baristas, whose employment is unlikely to be very impacted by AI (yet!).
Their third key fact relates most closely to the point I raised at the beginning of this post. On this, Brynjolfsson et al. find that:
...occupations with the highest estimated automation shares have experienced declining employment for the youngest workers...
...occupations with the highest estimated augmentation shares have not experienced a similar pattern...
The relevant figures are Figures 7 and 8 from the paper (which are too large for me to reproduce sensibly here). For their fourth key fact, Brynjolfsson et al. use a Poisson regression model within each age group, which allows them to control for firm-time-specific and firm-quintile-specific effects (where the quintiles are quintiles of exposure to AI, drawn from the paper that I discussed in this 2023 post). The firm-time effects will control for firm-specific shocks that affect all of the firm's workers, while the firm-quintile effects will control for different trends affecting a firm's workers that have similar exposure to AI. The analysis won't control for all of the relevant differences, and the analysis remains correlational rather than causal. Nevertheless, Brynjolfsson et al. find that:
For workers aged 22-25, estimates for higher quintiles are large and statistically significant, with a 12 log point decline in relative employment... Estimates for other age groups are generally much smaller in magnitude and not statistically significant.
A 12-log point change is about 11.3 percent, so relative to older workers working in the same firm and with the same exposure to AI, the youngest workers have suffered an 11.3 percent decrease in employment.
Brynjolfsson et al.'s fifth point is simply that the effects show up for employment, but not for wages. And their sixth point is that the effect is robust to various alternatives, including: excluding tech occupations; looking separately at jobs that are, or are not, amenable to remote work; extending the pre-period back to 2018; looking separately by gender; and using the Current Population Survey instead of the payroll data. Interestingly, looking differently at occupations depending on the education level of workers, the results show that:
Occupations with a high share of college graduates have declining employment overall, with muted differences between more-exposed and less-exposed occupations compared to our main results. In contrast, occupations with a low share of college graduates have rising overall employment, with the least AI-exposed occupations growing and the most exposed occupations declining in employment.
All of this is not great news for current university students. Think about all of the results taken together. Firms have been employing fewer entry-level workers, which are your typical graduates. Occupations that have a high share of college graduates are experiencing declining employment overall, in both occupations that are more exposed to AI and occupations that are less exposed to AI. And employment in AI-exposed occupations with a low share of college graduates has also been declining. It seems that the only groups of entry-level workers who aren't experiencing negative trends are non-college-educated workers in occupations that are not exposed to AI.
Brynjolfsson et al. try to finish on a positive note though, noting that:
The adoption of new technologies typically leads to heterogeneous effects across workers, resulting in an adjustment period as workers reallocate from displaced forms of work to new forms with growing labor demand... Past transitions such as the IT revolution ultimately led to robust growth in employment and real wages following physical and human capital adjustments, with some workers benefiting more than others...
Here's hoping that we don't have to wait too long for those adjustments.
[HT: Marginal Revolution]
*****
[*] However, decreasing employment (and wages) in the automating industry may increase the supply of workers into other industries, increasing employment (but decreasing wages) in those other industries. The general equilibrium effect is not straightforward.
[**] Arguments that increasing productivity will reduce the demand for labour, since fewer workers are needed to complete the same amount of work, run into the 'lump of labour' fallacy. They forget that firms can expand production if they have more productive workers, and will want more workers if their workers are more productive and therefore more profitable to employ.
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