According to the International Monetary Fund (IMF)'s Gen-AI: Artificial Intelligence and the Future of Work report, AI will impact as much as 40% of all jobs globally.
Artificial intelligence (AI) is set to profoundly change the global economy, with some commentators seeing it as akin to a new industrial revolution. Its consequences for economies and societies remain hard to foresee. This is especially evident in the context of labor markets, where AI promises to increase productivity while threatening to replace humans in some jobs and to complement them in others.
Almost 40% of global employment is exposed to AI, with advanced economies at greater risk but also better poised to exploit AI benefits than emerging market and developing economies. In advanced economies, about 60% of jobs are exposed to AI, due to prevalence of cognitive-task-oriented jobs. A new measure of potential AI complementarity suggests that, of these, about half may be negatively affected by AI, while the rest could benefit from enhanced productivity through AI integration. Overall exposure is 40% in emerging market economies and 26% in low-income countries. Although many emerging market and developing economies may experience less immediate AI-related disruptions, they are also less ready to seize AI’s advantages. This could exacerbate the digital divide and cross-country income disparity.
AI will affect income and wealth inequality
Unlike previous waves of automation, which had the strongest effect on middle-skilled workers, AI displacement risks extend to higher-wage earners. However, potential AI complementarity is positively correlated with income. Hence, the effect on labor income inequality depends largely on the extent to which AI displaces or complements high-income workers. Model simulations suggest that, with high complementarity, higher-wage earners can expect a more-than-proportional increase in their labor income, leading to an increase in labor income inequality. This would amplify the increase in income and wealth inequality that results from enhanced capital returns that accrue to high earners. Countries’ choices regarding the definition of AI property rights, as well as redistributive and other fiscal policies, will ultimately shape its impact on income and wealth distribution.
The gains in productivity, if strong, could result in higher growth and higher incomes for most workers. Owing to capital deepening and a productivity surge, AI adoption is expected to boost total income. If AI strongly complements human labor in certain occupations and the productivity gains are sufficiently large, higher growth and labor demand could more than compensate for the partial replacement of labor tasks by AI, and incomes could increase along most of the income distribution.
College-educated workers are better prepared to move from jobs at risk of displacement to high complementarity jobs; older workers may be more vulnerable to the AI-driven transformation. In the UK and Brazil, for instance, college-educated individuals historically moved more easily from jobs now assessed to have high displacement potential to those with high complementarity. In contrast, workers without postsecondary education show reduced mobility. Younger workers who are adaptable and familiar with new technologies may also be better able to leverage the new opportunities. In contrast, older workers may struggle with reemployment, adapting to technology, mobility, and training for new job skills.
To harness AI's potential fully, priorities depend on countries’ development levels. A novel AI preparedness index shows that advanced and more developed emerging market economies should invest in AI innovation and integration while advancing adequate regulatory frameworks to optimize benefits from increased AI use. For less prepared emerging markets and developing economies, foundational infrastructural development and building a digitally skilled labor force are paramount. For all economies, social safety nets and retraining for AI-susceptible workers are crucial to ensure inclusivity.
Info source: IMF