workers may be pushed into lower-paid, simpler tasks, while the lowest-skilled workers risk unemployment altogether (Acemoglu and D. Autor 2011). In a scenario where generative AI amplifies inequality and triggers social unrest, sustaining economic growth becomes increasingly challenging (Aghion, Caroli, and Garcia-Penalosa 1999).

Additionally, generative AI will affect individuals’ incentives for acquiring education and skills. Traditionally, high-skill, well-paid jobs have demanded specialized expertise, with the promise of higher income and more fulfilling careers motivating individuals to invest in college degrees and advanced training. However, technological advancements continuously reshape the landscape of valuable skills, rendering some expertise obsolete while creating demand for new competencies.

The current competition for scarce generative AI talent exemplifies this shift, with annual compensation packages reaching a million dollars for top professionals<sup>1</sup> . Simultaneously, expertise in other fields is being devalued. If AI leads to a decline in the proportion of high-skill, well-paid jobs in the long term, individuals may be discouraged from investing in higher education due to diminished prospects of securing rewarding employment (Capraro et al. 2024).

Evidence suggests this trend is already underway. In the United States, the percentage of high school graduates immediately enrolling in college has decreased from 69% in 2018 to 62% in 2022<sup>2</sup> . Moreover, parents and students are increasingly questioning the value of a college degree, with approximately half of U.S. adults believing that a four-year degree is less important for obtaining a well-paying job today than it was two decades ago.<sup>3</sup> This paper underscores risk of ”premature de-professionalization” - the potential contraction of opportunities for well-paid jobs in high-skill services within developing countries. This could potentially lead to widespread underemployment, reduced social mobility, and disillusionment among younger generations. While economists have historically argued that technological advancements create more jobs than they eliminate, this optimism may not hold in the AI era. Acemoglu and Restrepo 2019 has documented an acceleration in automation coupled with a deceleration in the creation of new tasks. Digital technologies and AI have eliminated millions of middle-skill, middle-income routine jobs while generating low-barrier, poorly-paid, precarious positions in low-skill services and the gig economy. In developing countries, the current high employment shares in agriculture and low-skill services mask underemployment on a grand scale, as these sectors often serve as last resorts for those unable to secure more promising opportunities.

> 1The Fight for AI Talent: Pay Million-Dollar Packages and Buy Whole Teams. https://www.wsj.com/tech/ai/the-fightfor-ai-talent-pay-million-dollar-packages-and-buy-whole-teams-c370de2b

> 2Immediate College Enrollment Rate, https://nces.ed.gov/programs/coe/indicator/cpa

> 3Roughly half US adults say it’s less important to have a four-year college degree today in order to get a well-paying job than it was 20 years ago. https://www.pewresearch.org/social-trends/2024/05/23/is-college-worth-it-2/

41