Goldman Sachs CEO Solomon: The AI "Jobs Apocalypse" Is an Overblown Panic

Goldman Sachs CEO Solomon published a commentary in The New York Times, offering a different perspective on market fears that AI will trigger a "job apocalypse." Solomon noted that AI automation is more likely to repeat the pattern of past technological transformations—eliminating some positions while expanding others. Goldman Sachs economists predict that over the next decade AI could automate 25% of current working hours, while hyperscale cloud providers' $700 billion in capital expenditure has already driven emerging employment in industries such as construction. (Background: Bitcoin consolidates at $76K, ETFs see 6 consecutive days of outflows totaling $1.26 billion, market watches for first FOMC on 6/17) (Background supplement: Major news! Foreign media reveals US-Iran ceasefire agreement extended by 60 days! Iran pledges to "clear mines" within 30 days and reopen the Strait of Hormuz) In a commentary article, addressing market fears about AI triggering a "job apocalypse and mass unemployment," Solomon presented a different view. He believes the impact of AI on the job market is not as severe as market panic imagines—AI is more likely to repeat the path of past technological transformations, eliminating some positions while expanding others. Goldman Sachs CEO Solomon, writing in The New York Times, pointed out that technological transformations over the past centuries have all followed similar trajectories. During the Industrial Revolution, horses were replaced by automobiles, but driver and mechanic positions emerged. During the Computer Revolution, typists were replaced by word processing software, but programmer and data analyst positions increased. During the Internet Revolution, brick-and-mortar retailers were replaced by e-commerce, but logistics and digital marketing positions expanded. "AI is likely to repeat the path of previous technological transformations, eliminating some positions while expanding others." According to Goldman Sachs economists' latest forecast, AI could automate 25% of current working hours over the next decade. This figure is not as alarming as imagined. White-collar industries will bear the brunt: banking, law, accounting, software development, and customer service will face the greatest impact. Blue-collar work is relatively stable: automation in construction, manufacturing, and services is slower. New positions emerge: new roles in AI system management, implementation, verification, and regulation will continue to grow. Solomon provided a concrete example to support his view. In just this year alone, hyperscale cloud companies plan to invest $700 billion in capital expenditure, which has already driven a surge in construction industry positions. This $700 billion in capital expenditure includes: data center construction, chip factory expansion, infrastructure upgrades, and energy supply systems. Solomon emphasized that the US economy has successfully absorbed multiple rounds of technological shocks. During the Agricultural Revolution, agriculture went from 70% of the workforce in 1800 to less than 3% today. During the Manufacturing Revolution, manufacturing fell from a peak of 33% to the current 8%. During the Services Expansion, services grew from 30% to the current 80%. "Overall employment and living standards have continued to improve." Taiwan, as a global semiconductor and technology manufacturing hub, will see significant impact on its AI job market. In the semiconductor industry, leading enterprises such as TSMC are actively integrating AI for process optimization, with AI chip demand driving global investment. In tech startups, Taiwanese startups are rapidly adopting AI tools to boost productivity, with software development and data science becoming popular professions. In manufacturing automation, Taiwan is transforming from a "manufacturing powerhouse" to "smart manufacturing," with widespread application of robotic processes and machine learning. Based on this analysis, Solomon proposed the following policy recommendations: educational reform, strengthening STEM (Science, Technology, Engineering, Mathematics) education. Vocational training, establishing a "lifelong learning" system. Social safety net, expanding unemployment protection and health insurance. Infrastructure investment, leveraging AI to improve public service efficiency. Solomon's view offers an optimistic perspective: AI will not be the "apocalypse" of employment, but rather the key to new "opportunities." The crux lies in how to invest in human capital, enabling workers to smoothly transition to new positions. As AI technology continues to develop, the labor market will continue to evolve, but history shows that humans possess remarkable adaptability.