Editor’s Note: Whether AI will bring about a “job apocalypse” has become one of the most pressing concerns in the business world. In an article for The New York Times, David M. Solomon, Chairman and CEO of Goldman Sachs, argues that these fears are exaggerated. While AI will indeed disrupt the labor market—particularly repetitive tasks in white-collar roles such as accounting, banking, law, software engineering, and customer service—it is more likely to transform job content than simply eliminate large numbers of positions.
Solomon’s core insight is that AI automates not 25% of jobs, but 25% of work hours. In other words, machines will take over parts of tasks that are inefficient or repetitive, while humans are shifted toward more complex roles requiring judgment and customer interaction. Meanwhile, new demands such as data center construction, AI workflow management, and compliance verification are creating fresh employment opportunities.
What this article truly aims to address is an old question in technological change: every new technology brings disruption, but historically, economies have often recreated jobs after such shocks. The risk of AI is not that it will inevitably cause job losses, but whether society, businesses, and education systems can promptly help workers transition.
The following is the original text:
Over the past few months, I’ve spoken with hundreds of business leaders and noticed a sharp divide in their views on artificial intelligence. One side believes that a “job apocalypse” and widespread unemployment are imminent; the other side believes AI will propel society toward a tremendous leap forward.
I fall into the latter category—though I do have some reservations. Will AI disrupt the labor market? Undoubtedly. This transition, like other major historical shifts, will bring new challenges, particularly as AI separates labor from productivity on an unprecedented scale. But the United States has long demonstrated the ability to create new jobs following technological disruptions—from electrification in the early 20th century to the digital revolution in the 1990s. I see no reason why this dynamic would stop today.
There is no doubt that AI will reshape our daily lives. Goldman Sachs economists estimate that over the next decade, AI could automate 25% of current work hours. For occupations requiring hands-on, on-site work—such as food preparation, construction, and services—the impact of AI remains difficult to assess; however, in white-collar roles including accounting, banking, and law, many tasks are likely to be automated. A Stanford University study found that in occupations most vulnerable to automation, such as software engineering and customer service, entry-level employment has already declined by 16% compared to the least affected roles.
However, the picture changes when looking at jobs or industries with weaker ties to automation. Our economists estimate that the growth in demand for data centers since 2022 has created over 200,000 construction jobs. While AI may eliminate roles in certain industries, it can also drive job growth in others. For example, Goldman Sachs may no longer need as many staff dedicated to regulatory reporting or customer onboarding processes, but this frees up capacity to hire more bankers, traders, and asset managers who engage continuously with clients.
Of course, we cannot ignore the very real human costs behind this disruption. The Industrial Revolution did raise living standards, but only after society endured grueling labor in factories and mines, as well as the squalid slums brought on by rapid urbanization. In recent decades, manufacturing jobs have declined sharply due to automation and global outsourcing, causing significant hardship for many families and communities across the United States, such as Gary, Indiana, and Greenville, South Carolina.
But despite these challenges, I keep returning to one reality: the standard of living for the vast majority of Americans has significantly improved over time. I was born in 1962, when most American adults did not have air conditioning; later, as air conditioning became cheaper, nearly everyone enjoyed its cooling benefits. In the 1950s, only large companies like IBM had computers; today, about 90% of American adults carry a supercomputer in their pocket. In 1900, global life expectancy at birth was 32 years; today, it exceeds 70 years.
Perhaps more importantly, job growth has outpaced population growth. Since 1962, U.S. civilian employment has increased by approximately 145%, while the civilian population aged 16 and over has grown by about 128%. During this period, some new industries emerged, while others expanded or declined. Manufacturing employment fell from 15.5 million to 12.5 million, with nearly 2 million jobs lost in the textile and apparel manufacturing sector; meanwhile, the healthcare industry now employs over 18 million people. The U.S. economy remains the most innovative, dynamic, and entrepreneurial in the world.
Indeed, even the most reliable historical patterns can be broken. However, I believe the U.S. economy will continue to demonstrate resilience and vitality for three reasons.
First, if our estimates are correct, AI will not eliminate 25% of jobs. More likely, people will find more efficient ways to allocate their time. When I first started as a first-year investment banking analyst, simply creating a chart of stock performance took six hours, as I had to look up prices in microfilm archives of The Wall Street Journal. Today, a first-year analyst can accomplish the same task in seconds, and in recent years, we’ve hired more people than ever before. The more advanced the tools, the more naturally the complexity of work increases. Despite the convenience brought by Excel, email, and Zoom, does anyone among us really feel like we have less to do now?
Second, even if a job can be replaced, that doesn’t mean it will be replaced. Television did not eliminate the demand for live entertainment, and the internet has not put real estate agents or fitness trainers out of work. On the contrary, these technologies have highlighted and enhanced the value of these professions. Technological change and cultural change do not progress in sync. After all, despite decades of ATMs, digital banking, and banking consolidation, employment in the commercial banking sector today remains roughly at the levels seen in the mid-1990s.
Third, the U.S. labor market itself is highly dynamic. Although net job creation each year amounts to only a few million, the overall volume of job turnover is much larger: U.S. businesses eliminate and create between 25 and 35 million jobs annually. As AI drives further innovation, this pace is likely to accelerate, and we are already seeing the economy adapt to these changes. Companies are now seeking talent capable of managing so-called "agent-based AI" and applying it across a wide range of use cases—from implementation and workflow automation to compliance and validation—all of which still require human judgment.
If AI indeed eliminates jobs—and does so potentially faster than ever before—public policy must respond: either fund large-scale retraining programs or promote the development of AI that supports workers rather than replaces them.
This must be a joint effort between the public and private sectors. The public sector should provide incentives and resources when necessary, including increased investment in vocational schools and community colleges; the private sector should help employees upskill and redesign on-the-job training systems.
Historical patterns are clear: the U.S. economy can and will adapt to major technological advancements. It is equally clear that even the most insightful predictions often prove inaccurate. In 1930, John Maynard Keynes famously predicted that by 2030, people would work only 15 hours per week. Although the leisure-filled future he envisioned has not materialized, it serves as a valuable reminder: fears of “job apocalypse” likely underestimate AI’s potential to drive economic and productivity resurgence.
David M. Solomon, in addition to leading Goldman Sachs, is also an electronic dance music producer under the alias DJ D-Sol.