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IMF Warns That Nearly 40% of Global Jobs at Risk Due to AI

-Editorial

The rapid evolution of artificial intelligence (AI) has sparked global fascination and concern, and has started a crucial examination of its potential consequences for the world economy. 

As AI permeates economies in intricate ways, forecasting its net effect remains challenging. However, it is evident that the world must establish a set of policies to harness AI’s vast potential responsibly for the benefit of humanity.

An analysis by IMF staff delves into the potential influence of AI on the global labor market. While predictions of job displacement by AI have been prevalent, the analysis acknowledges that AI is likely to complement human work in many cases. The study reveals that almost 40 percent of global employment is exposed to AI, with both advanced and emerging economies facing distinct challenges and opportunities.

Advanced economies, facing a higher risk from AI, may see approximately 60 percent of jobs impacted. Despite the risks, about half of these exposed jobs could benefit from AI integration, boosting productivity. However, the other half may witness tasks currently performed by humans being executed by AI, potentially reducing labor demand, lowering wages, and, in extreme cases, leading to job loss.

In contrast, emerging markets and low-income countries face a lower immediate disruption, with AI exposure expected to be 40 percent and 26 percent, respectively. However, the lack of infrastructure and skilled workforces in these countries raises concerns about long-term inequality as they may struggle to harness AI benefits effectively.

AI’s impact on income and wealth inequality within countries is a critical concern. The potential for polarization within income brackets may favor workers who can harness AI, exacerbating inequality. Policymakers must proactively establish comprehensive social safety nets and retraining programs to ensure an inclusive AI transition, protecting livelihoods and curbing inequality.

Recognizing the urgency for appropriate policies, the IMF has developed an AI Preparedness Index. This index measures readiness in areas such as digital infrastructure, human-capital and labor-market policies, innovation, economic integration, regulation, and ethics. The findings indicate that wealthier economies, including Singapore, the United States, and Denmark, are generally better equipped for AI adoption, emphasizing the need for global collaboration to address the challenges posed by AI.

Acceptability may vary depending on job roles. Some professions may seamlessly integrate Al tools, while others could face resistance because of cultural, ethical, or operational concerns. This uncertainty becomes especially pronounced in labor markets.

Although Al holds the potential for production-oriented applications, its effect will likely be mixed. In some sectors where human oversight of Al is necessary, it could amplify worker productivity and labor demand.

In other sectors, Al might pave the way for significant job displacements. A rise in aggregate productivity of the economy could however strengthen overall economic demand, potentially creating more job opportunities for most workers in a ripple effect. Moreover, this evolution could also lead to the emergence of new sectors and job roles—and the disappearance of others—transcending mere intersectoral reallocation.

Advanced economies, with their mature industries and service-driven economies, typically have a higher concentration of jobs in sectors that require complex cognitive tasks. These economies are therefore both more susceptible to, yet better positioned to benefit from, Al innovations.

Conversely, emerging markets and developing economies, often still reliant on manual labor and traditional industries, may initially face fewer Al-induced disruptions. However, these economies may also miss out on early Al-driven productivity gains, given their lack of infrastructure and a skilled workforce. Over time, the Al divide could exacerbate existing economic disparities, with advanced economies harnessing Al for competitive advantage while emerging market and developing economies grapple with integrating Al into their growth models.

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