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By Wilson Wong
March 21, 2025
Many scholars and international organizations underestimate the impact of artificial intelligence (AI) on employment because they make a common error: viewing AI as an isolated force rather than recognizing its powerful synergy with existing technologies. This combined force will likely surpass current expectations, generating unprecedented impacts across labor markets and societies. Representatives of the conventional view that AI’s impact remains limited include Daron Acemoglu, one of this year’s Nobel Prize winners in Economics. In contrast, prominent leaders and entities seeking to integrate AI with robotics to fundamentally transform society include Elon Musk—CEO of Tesla and SpaceX—and China, an AI superpower and the United States’ primary competitor in the global AI race.
While Acemoglu is undeniably at the cutting edge of AI research, his assessment of AI’s disruptive potential remains relatively conservative. He argues that current market enthusiasm for AI is largely irrational, creating an economic bubble at risk of bursting and potentially triggering an economic downturn. Conversely, the International Monetary Fund (IMF), in its 2024 report Gen-AI: Artificial Intelligence and the Future of Work, estimates AI could disrupt or replace approximately 40 percent of global jobs, with the figure reaching around 30 percent in the United States. Interestingly, the proportion of workers facing significant disruption is lower in developing countries—less than 20 percent in Brazil and India.
The rise of generative AI (GAI) has emerged as a primary factor contributing to this disruption and underscores the disparity between developed and developing economies. Unlike earlier generations of AI, GAI—including large language models such as ChatGPT—can potentially replace knowledge workers, including professionals like lawyers, accountants and consultants. Given that professionals constitute a significant segment of developed countries’ workforces, these economies face disproportionately higher vulnerability to AI-driven disruptions.
Acemoglu’s latest MIT paper, The Simple Macroeconomics of AI, however, suggests that only about 5 percent of jobs are truly at risk. His analysis relies on a “task-based model,” breaking down job functions to determine human versus AI advantages and assessing realistic threats of AI replacing human labor. Yet, his approach rests on two key assumptions: first, jobs will not be reorganized or redesigned in response to AI; second, the analysis primarily examines AI in isolation, neglecting significant synergies between AI and other technologies, especially robotics, which could threaten many physical-labor jobs.
In reality, advances in AI are accelerating robotics development considerably. Autonomous vehicles and sophisticated robots are rapidly acquiring enhanced learning and adaptability capabilities, soon matching or surpassing human performance in a variety of tasks. Thus, the impacts of AI on labor markets extend beyond knowledge workers, profoundly affecting physical laborers through wage reductions and potential layoffs.
Tech leaders like Elon Musk represent the other extreme compared to Acemoglu’s cautious approach. Many technology giants aim to push boundaries by rapidly advancing innovations, often without fully considering their societal implications. These innovations typically disrupt existing orders through “creative destruction.” At a recent Tesla event, Musk introduced three groundbreaking inventions: the Optimus robot, capable of conversing and conducting general tasks alongside humans; the driverless taxi Cybercab; and the autonomous minibus Cybervan. Each of these technologies, when widely adopted, will significantly impact labor markets and transform human society, creating both opportunities and threats.
Consider the potential societal shock when professional drivers, numbering approximately 3.6 million in the United States alone, are displaced by autonomous vehicles. Similarly, what will be the economic consequences for countries such as the Philippines and Indonesia, whose economies depend significantly on remittances from overseas domestic workers, once home robots become commonplace and dramatically reduce demand for human labor abroad? Such disruptions could lead to large-scale unemployment, increased internal inequalities, political instability and even reshape the global political and economic order.
Most experts agree that substantial changes from AI and robotics are inevitable, though they differ on the exact timing and magnitude. Unfortunately, many governments remain inadequately prepared for these revolutionary transformations. According to my research, although most advanced economies have issued national AI strategies, these plans often prioritize retraining and upskilling highly educated workers, largely overlooking the needs of more vulnerable, less-educated populations at risk of displacement.
Governments must urgently adopt a more proactive and comprehensive approach to AI preparedness. First, policymakers should expand workforce development strategies to include targeted programs for lower-skilled and vulnerable populations, offering robust retraining opportunities and job-transition assistance. Second, governments should actively engage in scenario planning to identify sectors most vulnerable to AI and robotic disruption and preemptively design economic and social policies to mitigate adverse impacts, such as unemployment insurance reform, universal basic income experiments, and economic diversification initiatives.
Finally, international collaboration is critical. Countries need coordinated strategies to address global labor-market shifts, protect vulnerable workers and prevent destabilizing economic disparities between nations. Failing to act proactively risks marginalizing significant segments of society, exacerbating inequality and destabilizing nations. On the other hand, thoughtful planning and policy adaptation can harness AI’s immense potential for economic growth, productivity gains, enhanced quality of life and shared prosperity.
The choice governments make today, whether to adopt an informed, proactive approach or remain unprepared, will profoundly shape their societies’ trajectory. The stakes could not be higher.
Author: Wilson Wong is the Founding Director and an Associate Professor of Data Science and Policy Studies (DSPS), School of Governance and Policy Science, at The Chinese University of Hong Kong (CUHK). He is also a Senior Research Fellow at the School of Management, UCL, and a Fellow at the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford University. His major research areas include AI and Big Data, digital governance, ICT and comparative public administration.