Gen-AI: Artificial Intelligence and the Future of Work
By Mauro Cazzaniga ; Florence Jaumotte ; Longji Li ; Giovanni Melina ; Augustus J Panton ; Carlo Pizzinelli ; Emma J Rockall ; Marina Mendes Tavares
On behalf of The International Monetary Fund
An executive summary
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 percent 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 percent 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
percent in emerging market economies and 26 percent 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 highcomplementarity 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 market 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.
