Goldman Sachs CEO Solomon wrote in The New York Times: AI doomsday panic is being exaggerated; white-collar employment will be hit the hardest, but entirely new jobs will be created

Goldman Sachs CEO David Solomon publicly commented on Tuesday in The New York Times, bluntly stating that the panic over AI causing "job apocalyptic scenarios and mass unemployment" is greatly exaggerated. Solomon believes AI will not eliminate jobs on a catastrophic scale but will instead boost worker productivity, shift employees toward higher value-added tasks, and create entirely new roles centered around AI system management, implementation, verification, and regulation. However, he also admits that white-collar industries such as banking, law, accounting, software development, and customer service will face the greatest impact.
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Table of Contents

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• From Panic to Productivity: How AI Replicates the Path of Technological Change
• $700 Billion Capital Expenditure: AI Benefits on Construction Sites
• Structural Challenges in White-Collar Industries
• Blueprint for New Roles: From AI System Management to Regulatory Verification

Will artificial intelligence trigger widespread unemployment? This core question troubling the global labor market has recently received one of Wall Street’s most influential voices. On May 26, David Solomon, CEO of Goldman Sachs, published an opinion piece titled "I’m the C.E.O. of Goldman Sachs. The A.I. Job Apocalypse Is Overblown." in The New York Times, systematically refuting the pessimistic narrative that AI will eliminate human jobs.

In the article, Solomon explicitly states that while AI will indeed impact certain industries, historical experience repeatedly shows that technological progress ultimately creates more jobs than it destroys. His argument is built on three core pillars: the historical trajectory of productivity gains, the chain reaction of massive capital expenditures, and the natural emergence of new job categories.

From Panic to Productivity: How AI Replicates the Path of Technological Change

Solomon acknowledges that the rapid development of AI has indeed sparked widespread labor market anxiety. Goldman’s economists forecast that within the next decade, AI could automate about 25% of current work hours, with white-collar industries such as banking, law, accounting, software development, and customer service being most affected. These industries involve extensive data processing, document review, coding, and standardized communication—areas where current AI systems excel.

But he also emphasizes that the U.S. economy has experienced similar scenarios multiple times in the past, from large-scale shifts of agricultural labor during the Industrial Revolution to structural unemployment caused by manufacturing automation in the information age. Each wave of technological disruption has been successfully absorbed by the economy, with overall employment rates and living standards continuing to rise. AI is likely to follow this same path: eliminating some jobs while expanding others on a larger scale.

$700 Billion Capital Expenditure: AI Benefits on Construction Sites

Solomon points to a concrete and quantifiable piece of evidence: this year alone, hyperscale cloud service providers plan to invest approximately $700 billion in capital expenditures. This enormous investment has already driven a surge in employment within the U.S. construction industry. Building data centers, semiconductor fabs, fiber optic networks, and other AI infrastructure requires a large workforce—from rebar workers to electrical technicians—that cannot be replaced by AI but is created in large numbers due to AI development.

This phenomenon reveals a key aspect overlooked by "job apocalypse" theories: AI is not only a technology that replaces jobs but also a driver of physical economic investment. Every new data center or high-performance computing line represents thousands of construction and operational jobs.

Structural Challenges in White-Collar Industries

Although the overall outlook remains optimistic, Solomon does not shy away from the real impacts AI will have on the labor market. He highlights that white-collar industries will be the "epicenter" of this wave of technological change:

In banking, AI can already handle loan approvals, risk assessments, and regulatory compliance traditionally managed by analysts; in law, AI document review systems can complete in seconds what previously took dozens of lawyers and weeks; in accounting and auditing, automation is accelerating.

However, Solomon believes these industries will not disappear but will undergo a fundamental shift in job structure. low-value repetitive tasks will be replaced by AI, but the building, management, verification, and regulation of AI systems will generate a large number of new specialized roles. These new roles require higher judgment, more complex problem-solving skills, and the ability to critically evaluate AI outputs.

Blueprint for New Roles: From AI System Management to Regulatory Verification

Solomon mentions that AI will give rise to at least four emerging job categories: AI system administrators responsible for daily operations and handling anomalies; AI implementation consultants helping companies integrate AI into existing processes; AI verification engineers ensuring the accuracy and fairness of AI outputs; and AI compliance officers managing regulatory and ethical issues. These roles are not science fiction but are already gradually forming within Goldman Sachs and other Wall Street institutions.

It’s worth noting that Solomon is not speaking from an ivory tower. Goldman Sachs itself has heavily deployed AI tools internally, from trading strategy support analysis to intelligent customer response systems. The experiences he shares are firsthand observations from this Wall Street giant’s AI transformation process.