AI Needs to Help Young Workers

Editor's note: This piece was authored by Ryan Khurana.

AI is finally showing up in the labor data, but in an unexpected way. 

Stanford researchers studying U.S. payroll records found a growing divide between young workers based on their exposure to AI. Since ChatGPT’s release in November 2022, employment among 22- to 25-year-olds in highly AI-exposed occupations has fallen 19 percent relative to less-exposed occupations. 

Young workers in AI-exposed fields like software development, customer service, and accounting are competing for fewer roles than their unexposed peers in nursing, construction, and food services. However, the same AI-exposed occupations have seen no comparable decline in new roles for experienced workers. Layoffs also remain stable.

The clearest AI-associated labor market effect has simply been fewer job opportunities for young Americans.

My own experience with enterprise AI adoption reflects this data. AI demand has focused on automating “intern-level” tasks: the routine, low-stakes, time-consuming work that gets young workers onto the job ladder. Existing workers do more entry level work with AI and new positions do not get created.

These current applications of AI fail to utilize the technology’s potential, which should help create more opportunities for young workers. 

AI democratizes the expertise workers learn from years on the job. A study of customer support workers found that AI productivity gains were concentrated among novice and lower-skilled workers. 

The ideal users of AI are the ones that companies have the least incentive to hire. A broken first run for hiring new employees trades investment in their future productivity for smaller realized gains today.

This discrepancy may explain a paradox about the current economy. There is little evidence of the broad productivity boom many expected from AI. At the same time, we have entered a low-hire, low-fire environment where young workers struggle to find work. Labor share of GDP has fallen to its lowest level since recording began in 1947, while profit margins are rising faster than revenue. AI may be allowing firms to extract value from their existing workforce without expanding real wages or employment. 

For young Americans, that means losing income and experience today and shrinking opportunities tomorrow. This is an unsustainable situation.

In Gerontocracy in America, historian Samuel Moyn argues that as Americans live longer and hold a growing share of the country's wealth, senior leaders have become more reluctant to retire and pass the torch to the next generation. 

While younger Americans face reduced opportunity, Congress has on average become 10 years older than in 1981, and the average American CEO is now 61 — a decade older than in 2000. 

AI may exacerbate this problem.

Organizations naturally protect incumbents. By choosing to deploy AI in a way that keeps existing employees on longer and reduces additional hiring, a company creates little disruption. Realizing AI's full potential requires ambition and dynamism that would disrupt the status quo. 

Previous technological revolutions created new ladders for ambitious young people to climb: they required new skills and benefited from outside-the-box thinking. AI’s ease of use allows experienced workers to adopt it and be satisfied as is. As a result, this is becoming a rare moment when younger Americans are more skeptical of a major new technology than their elders.

Pew found that 48 percent of adults ages 18 to 29 think AI will have a negative effect on society over the next 20 years, compared with 37 percent of Americans over 50. Young adults are also the most likely age group to believe AI will negatively affect them personally. Anti-AI and anti-data centre sentiment is growing across party lines among young Americans. 

American firms and policymakers need a new deal for young workers to ensure they gain from innovation. 

AI should be a rising tide that lifts all boats, supercharging productivity, accelerating scientific discovery, and compensating for the declining ratio of workers to retirees. 

The current situation risks creating what economist Daron Acemoglu calls ‘so-so automation’: technology that is good enough to replace workers, but not transformative enough to drive substantial productivity growth.

It does not have to be this way.

Business leaders need to acknowledge that the presence of young, technically literate employees in their organizations will drive dynamism. 

States need to incentivize the hiring of young workers so they can get onto the job ladder and begin accumulating the experience that makes them harder to displace. They need to move taxation away from consumption and labor that falls on the young. They need to create early-retirement incentives so that passing the torch feels like less of a burden.

AI has already delivered frontier advancement in software, science, and medicine. There is no reason it should not be accelerating the economy as a whole. 

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