AI-Driven Disruptions to Hit Labour Markets and Lending
Central bankers are scrambling to grasp the full extent of artificial intelligence’s impact on the global economy, as this technology seeps into almost every conversation. At a recent meeting of the world’s top central bankers, they discussed the looming question: will AI displace jobs or boost productivity?
The International Monetary Fund’s Chief Economist, Pierre-Olivier Gourinchas, warned that AI could disrupt labour markets on a massive scale.
Avoiding a Job Crisis, One Algorithm at a Time
AI has already started replacing low-paying, repetitive jobs, and its reach is expanding to higher-skilled positions. According to recent research, nearly 60% of all occupations have at least 30% of the elements that are programmable by a computer. This poses a significant threat to the future of work.
Meanwhile, some experts predict that AI-driven automation could lead to a surplus of skilled workers, pushing wages down and sparking a job crisis. But others argue that AI will create new jobs that we can’t yet anticipate, and that its impact will be a double-edged sword.
Lending to the Rescue, or a New Risk?
AI is also transforming the lending landscape, making it easier for companies and individuals to access credit. By leveraging vast amounts of data, AI can assess creditworthiness more accurately and quickly than human lenders, potentially expanding access to credit for underserved communities.
However, this could also create new risks, such as AI-generated credit applications being exploited by scammers. Central bankers are grappling with the potential consequences of relying on AI-driven credit decisions, and whether regulators will be able to keep pace with the technology.
What This Means
The impact of AI on the global economy will be far-reaching, with potential consequences for labour markets, lending, and beyond. While its effects are still uncertain, one thing is clear: central bankers will need to adapt to a world where AI is increasingly intertwined with economic decision-making.
