Generative AI and the future of New York

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At a glance

  • The labor market in the New York region faces several critical challenges. These include too few workers to meet overall demand, stagnating productivity, and yawning inequities across geographic areas and demographic groups. Generative AI (gen AI) provides an opportunity to address aspects of these challenges, while creating some new obstacles.
  • Overall net employment in the New York region is expected to continue to grow, increasing by about 1.8 percent through the end of the decade. While positive, that is lower than the 4.2 percent net employment growth estimated for the nation during the same period.
  • The evolving nature of work means the mix of jobs in the New York region will likely change substantially in the next few years. By 2030, as many as 1.1 million occupational shifts may be required in the New York region, and one-third—or approximately 380,000 of these shifts are directly attributable to the impact of gen AI. The technology affects a far broader range of occupations than existing automation technologies do and primarily augments work rather than replacing it.
  • When factoring in other structural and technological shifts alongside gen AI, the New York region stands to gain up to 700,000 jobs. This gain will be fueled by heightened demand for healthcare and engineering professionals, construction workers, and transportation service personnel. This growth will be partially offset by 600,000 positions that could be affected in office support, customer service, and food service and production, precipitated by accelerated automation and deliberate cost-shifting strategies beyond the region’s boundaries.
  • Gen AI could help ease the region’s worker shortage, revive productivity growth, push people toward higher-value roles, and unleash creativity. Yet doing so while minimizing the potential negative impact on workers requires the committed and coordinated engagement of public, education, and private sector leaders across America’s most important economic region.

The greater New York region has a long history of evolving its economy to meet the demands of new markets, technologies, and trends. Hundreds of thousands of New Yorkers change jobs every year to increase their earnings, reach their potential, or adjust to shifting demands for labor1 as neighborhoods like Manhattan’s Far West Side have evolved from oyster reefs to shipbuilding and warehouses to becoming the home of Google and the High Line. For centuries, automation has been a driving force for much of that churn, and today, the latest force for change—broadly described as gen AI—will drive further and faster evolution in the ways of working and the demand for labor.

Gen AI is shifting the New York region’s work landscape and job market. The evolving technology’s advanced natural language capabilities have extended the possibility of increased productivity to a much wider set of job activities, including writing code, designing products, creating marketing content and strategies, streamlining operations, analyzing legal documents, providing customer service via chatbots, and even accelerating scientific discovery.

Our analysis of McKinsey Global Institute research found that even without gen AI, by 2030, ongoing technological advancements could automate as many as 20 percent of total hours worked in the dynamic economic market of the New York region (defined for this article as the New York combined statistical area [CSA] with more than 12 million workers). A comprehensive analysis indicates that the unparalleled capabilities of gen AI have the potential to elevate this figure by an additional nine percentage points, reaching up to 29 percent of total hours worked (Exhibit 1). This transformative influence of gen AI is expected to reshape the fundamental nature of numerous occupations, instigating a shift toward novel roles that will emerge concurrently with the phasing out of traditional positions.

This change—like so many before it—does not mean the region will lose jobs overall, just as the lost jobs of clothing manufacturers in the Garment Center were replaced by media and tech jobs generations later. But gen AI will accelerate a shift in ways of working for hundreds of thousands of workers in different ways and to different degrees. Because the technology’s distinctive capabilities—such as enhanced natural language processing and understanding—can expedite basic, manual, and higher-level cognitive tasks, it will affect the workforce at both ends of the income and skills spectrums.

Activities anchored by decision-making and collaboration, of financial analysts in Wall Street banks to programmers in Union Square tech start-ups, which were barely affected by previous cycles of technological advancement, could see the biggest changes caused by gen AI. We estimate that for workers in these roles, the potential share of hours affected by automation will increase by 27 to 38 percentage points.2 For example, gen AI could automate 56 percent of work hours spent on activities that involve applying expertise, such as planning and designing facilities or conducting audits, compared with 18 percent without.

In contrast, for jobs involving physical activity, whether maintaining vehicles or delivering items, the incremental increase in potentially automated hours of work due to gen AI may be only one to three percentage points (Exhibit 2). Unlike with prior technology shifts, workers with higher levels of education are the most likely to be affected: gen AI may increase the automation potential of tasks by 14 percentage points for people with master’s degrees or higher by 2030, compared with a five-percentage-point increase for those who did not graduate from high school.

Yet while gen AI presents significant challenges, it offers even greater opportunity. Although the technology may accelerate the automation of certain elements of jobs, it could also free workers to undertake tasks that involve applying expertise to decision making and planning or managing and developing people. For example, new associates in Midtown firms could be freed to focus on complex matters of law instead of spending hours repetitively reviewing nearly identical documents. This could create entirely new roles to accommodate an expansion in creative work and encourage workers to harness new skills. And with the committed and coordinated engagement of all stakeholders, the net effect of gen AI could be to ease the New York region’s worker shortage, reverse years of slowing productivity, and unleash worker creativity.

Reinvigorating productivity

Across the United States, gen AI alone may increase labor productivity by up to one percentage point annually.3Generative AI and the future of work in America,” McKinsey Global Institute, July 26, 2023. This reflects the technology’s degree of sophistication; for instance, McKinsey Global Institute analysis and interviews with industry experts suggest gen AI could accelerate the ability of machines to perform in the top quartile of human performance in natural language understanding and social and emotional reasoning by 20 years. The combined effect of gen AI and all other automation technologies could boost labor productivity by up to 4 percent annually by 2030, with as much as a quarter attributable to gen AI. Realizing the full potential of the technology’s benefits will require supporting workers in learning new skills and through any job transitions.

In the New York region, gen AI’s impact may help combat the overall trend of decelerating productivity: while New York City’s labor productivity grew by an average of 2.1 percent a year from 1947 to 2018, it increased by just 1.3 percent annually from 2005 to 2018 and by 0.8 percent from 2010 to 2018.4 Gen AI can increase the number of tasks automated in the region by as much as 2.4 billion hours by 2030, contributing to the productivity growth critical for sustaining the region’s GDP growth in the face of the region’s flattening employment and population growth.

In this way, gen AI may also be an important lever to counter the impact of the region’s aging labor force and the lingering effects of the pandemic, such as outward migration, the increase in remote and hybrid work, and higher job churn rates.5

Changing the work landscape

Gen AI’s impact on how jobs are performed depends on the susceptibility of particular tasks to automation. For example, gen AI can quickly automate job activities requiring relatively basic cognitive skills. This could make more time available for job activities using technological, analytical, or social and emotional skills, which could in turn improve productivity and worker satisfaction.

While the combination of gen AI and a series of other structural and technological changes may affect as many as 4.1 million people by 2030 in the New York region, we find that gen AI will not lead to a net loss of jobs, despite its ability to accelerate adoption of, and use cases for, automation. This is because automation does not occur in a vacuum. It has an important impact, but automation is just one factor in New York’s evolving economy. Many other trends affect overall workforce demand, creating pull and push across sectors and occupations today as it has for centuries in this global center of innovation.

When we modeled 11 major trends affecting the labor force—including the accelerated pace of automation adoption from gen AI, the ongoing effects of the pandemic, federal investment in infrastructure, increasing demand for healthcare, and shifts to e-commerce and remote work—we found that the New York CSA could see net employment growth of 1.8 percent through 2030. Although lower than the national growth rate of 4.2 percent, that is a net increase of more than 200,000 jobs in the region.

This net growth manifests in a variety of ways. For example, demand for healthcare and science-technology-engineering professionals, construction workers, and transportation service staff could add up to 700,000 jobs in the New York region by the end of the decade. Multiple factors are driving this. The Federal CHIPS and Science Act is putting additional funding into semiconductor manufacturing as well as R&D and scientific research just as some companies are adjusting their supply chains, leading to an uptick in domestic manufacturing. While manufacturing is likely to boost employment demand overall in the years ahead, the sector is also becoming more high-tech and will involve fewer traditional production jobs but more workers with technical and STEM skills.

At the same time, rising incomes and education levels will sustain jobs. An aging population will need more healthcare workers everywhere from our world-class teaching hospitals to community health clinics and home care workers, while the ongoing process of digitalizing the economy will require additional tech workers in every sector, despite some recent headlines around layoffs. Conversely, this growth could be partially offset by as many as 600,000 jobs lost in fields such as office support, customer service, and food service and production. Contributing factors there include automation, which will be further propelled by gen AI, the strategic outsourcing of costs, and the enduring impact of the pandemic prompting shifts in business models—such as the widespread adoption of e-commerce and rise in remote work that has affected commutes to downtown, retail shopping in Midtown, and dining across New York’s famous food sector.

We found that the New York CSA may require about 1.1 million occupational shifts by 2030 (Exhibit 3), and one-third of those shifts—or approximately 380,000—are directly attributable to the impact of gen AI. In fact, the technology primarily augments work rather than replaces it, and occupational categories most exposed to the technology could continue to add jobs through 2030 (although the rate of growth may slow).

Demographic differences

These labor market changes are expected to affect populations differently. The advent of gen AI will likely lead to greater adoption of automation in higher-wage roles, such as those in managerial and professional services occupations, compared with lower-wage roles, including those in production work and maintenance. This shift is influenced by the fact that activities within higher-wage roles, once considered less susceptible to automation, have experienced significant advancements in automation.

In the New York region, automation adoption in jobs within the top two wage quintiles is projected to be between 1.9 and 2.0 times higher with gen AI, compared with no gen AI. On the other hand, jobs in the bottom two wage quintiles are expected to see a more moderate increase, with automation adoption up to 1.3 times higher with gen AI than without it (Exhibit 4).

Nevertheless, a look at structural trends and past technological shifts that include gen AI as well as broader changes in the nature of work that were already underway shows that lower-wage jobs are more susceptible to more complete displacement. Our analysis finds the jobs of low-wage workers in the New York region are 4.2 times more likely to be displaced than those of the highest-wage earners (compared with 14.0 times more likely across the United States). Non-college-educated workers could be 1.6 times more affected than those with bachelor’s degrees or higher (compared with 1.7 times nationally). Women, Latinos, and young workers are expected to be more adversely affected by job transitions precipitated by automation and other factors.

As gen AI reshapes work activities for many occupations, the region’s economy may end up with a larger share of high-wage, higher-productivity jobs. Our analysis shows that the share of low-wage jobs in the New York CSA may decrease from 43.1 percent in 2022 to 41.6 percent in 2030, similar to the US average. And the share of high-wage jobs in the New York region could increase from 31.4 percent in 2022 to 33.5 percent in 2030, again mirroring the national trend (Exhibit 5).

Seizing the moment

Change is rarely easy for individuals, families, communities, or even nations. Shifts in the nature of work affect not only companies but also, more critically, workers and the families they support. The speed of gen AI’s appearance, adoption, and effect on labor markets will likely be unprecedented by historical standards of technological change, this time affecting programmers in Bushwick almost as much as factory workers from the Bronx. Yet there remains a window of opportunity to address its impact.

Mitigating the potentially negative effects of gen AI and harnessing its potential upside will require the committed and coordinated engagement of all stakeholders, including individuals and the private, education, and public sectors. Companies and government organization leaders may consider clearly assessing gen AI’s risks, challenges, and opportunities to avoid fragmented responses and exacerbating challenges in worker transitions. A unified approach is necessary to fully realize the positive impact of gen AI, navigate its complexities, and ensure that its integration aligns with broader societal goals for economic growth and sustainability.

Leaders might consider the following questions to help the New York region capitalize on this moment’s positive potential and minimize its negative effects:

It is far too early to tell how history judges the way that the New York region addresses the gen AI revolution. In conjunction with many other forces driving change from Suffolk to Bergen County, gen AI has the potential to shift the nature of occupations for bankers on Wall Street and creatives in Williamsburg, creating new jobs we cannot even imagine yet, and altering the mix of jobs in the country’s biggest labor market. Managing this disruption by harnessing this technology’s opportunities and mitigating its challenges requires all stakeholders to come together, something they have not always done in previous revolutions. If we get it right, the New York region can not only set an example for the nation but also address many of its deepest and most long-standing challenges.

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