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By James Manyika, Susan Lund, Michael Chui, Jacques Bughin, Jonathan Woetzel, Parul Batra, Ryan Ko, and SauraBH Sanghvi
In an era marked by rapid advances in automation & artificial intelligence, new retìm kiếm assesses the jobs lost and jobs gained under different scenarquả táo through 2030.

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The technology-driven world in which we live is a world filled with promise but also challenges. Cars that drive themselves, machines that read X-rays, & algorithms that respond lớn customer-service inquiries are all manifestations of powerful new forms of automation. Yet even as these technologies increase productivity và improve sầu our lives, their use will substitute for some work activities humans currently perform—a development that has sparked much public concern.


Powerful new technologies are increasing productivity, improving lives, & reshaping our world. But what happens lớn our jobs?
Briefing Note"https://sathachlaixe cộ.vn/future-1/imager_4_82617_700.jpg> Briefing cảnh báo (PDF-2MB) Executive Summary"https://sathachlaixe pháo.vn/future-1/imager_4_82617_700.jpg> Executive Summary (PDF-2MB) Full Report"https://sathachlaixe cộ.vn/future-1/imager_4_82617_700.jpg> Full Report (PDF-9MB)

Building on our January 2017 report on automation, sathachlaixe.vn Global Institute’s lathử nghiệm report, Jobs lost, jobs gained: Workforce transitions in a time of automation (PDF–5MB), assesses the number và types of jobs that might be created under different scenargame ios through 2030 và compares that lớn the jobs that could be lost to lớn automation.

The results reveal a rich mosaic of potential shifts in occupations in the years ahead, with important implications for workforce skills and wages. Our key finding is that while there may be enough work lớn maintain full employment to 2030 under most scenarquả táo, the transitions will be very challenging—matching or even exceeding the scale of shifts out of agriculture & manufacturing we have seen in the past.


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1. What impact will automation have sầu on work?

We previously found that about half the activities people are paid to lớn vị globally could theoretically be automated using currently demonstrated technologies. Very few occupations—less than 5 percent—consist of activities that can be fully automated.

However, in about 60 percent of occupations, at least one-third of the constituent activities could be automated, implying substantial workplace transformations & changes for all workers.

While technical feasibility of automation is important, it is not the only factor that will influence the pace & extent of automation adoption. Other factors include the cost of developing và deploying automation solutions for specific uses in the workplace, the labor-market dynamics (including unique and quantity of labor và associated wages), the benefits of automation beyond labor substitution, and regulatory và social acceptance.


Interactive

Taking these factors inlớn account, our new retìm kiếm estimates that between almost zero and 30 percent of the hours worked globally could be automated by 2030, depending on the tốc độ of adoption. We mainly use the midpoint of our scenario range, which is automation of 15 percent of current activities. Results differ significantly by country, reflecting the mix of activities currently performed by workers & prevailing wage rates.

The potential impact of automation on employment varies by occupation and sector (see interactive above). Activities most susceptible lớn automation include physical ones in predictable environments, such as operating machinery và preparing fast food. Collecting & processing data are two other categories of activities that increasingly can be done better và faster with machines. This could displace large amounts of labor—for instance, in mortgage origination, paralegal work, accounting, và back-office transaction processing.

It is important to note, however, that even when some tasks are automated, employment in those occupations may not decline but rather workers may perform new tasks.

Automation will have a lesser effect on jobs that involve managing people, applying expertise, và social interactions, where machines are unable khổng lồ match human performance for now.

Jobs in unpredictable environments—occupations such as gardeners, plumbers, or providers of child- và eldercare—will also generally see less automation by 2030, because they are technically difficult lớn automate và often comm& relatively lower wages, which makes automation a less attractive business proposition.

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2. What are possible scenarquả táo for employment growth?

Workers displaced by automation are easily identified, while new jobs that are created indirectly from technology are less visible và spread across different sectors & geographies. We model some potential sources of new labor dem& that may spur job creation to lớn 2030, even net of automation.


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For the first three trends, we model only a trendline scenario based on current spending và investment trends observed across countries.

Rising incomes and consumption, especially in emerging economies

We have sầu previously estimated that global consumption could grow by $23 trillion between 2015 and 2030, và most of this will come from the consuming classes in emerging economies. The effects of these new consumers will be felt not just in the countries where the income is generated but also in economies that export lớn these countries. Globally, we estimate that 250 million to lớn 280 million new jobs could be created from the impact of rising incomes on consumer goods alone, with up lớn an additional 50 million lớn 85 million jobs generated from higher health & education spending.

Aging populations

By 2030, there will be at least 300 million more people aged 65 years and older than there were in 2014. As people age, their spending patterns shift, with a pronounced increase in spending on healthcare & other personal services. This will create significant new demand for a range of occupations, including doctors, nurses, và health technicians but also home-health aides, personal-care aides, and nursing assistants in many countries. Globally, we estimate that healthcare & related jobs from aging could grow by 50 million to 85 million by 2030.

Development và deployment of technology

Jobs related to lớn developing & deploying new technologies may also grow. Overall spending on công nghệ could increase by more than 50 percent between năm ngoái và 2030. About half would be on information-công nghệ services. The number of people employed in these occupations is small compared lớn those in healthcare or construction, but they are high-wage occupations. By 2030, we estimate that this trkết thúc could create đôi mươi million to 50 million jobs globally.

For the next three trends, we mã sản phẩm both a trendline scenario và a step-up scenario that assumes additional investments in some areas, based on explicit choices by governments, business leaders, and individuals khổng lồ create additional jobs.

Investments in infrastructure và buildings

Infrastructure and buildings are two areas of historic underspending that may create significant additional labor demand if action is taken to lớn bridge infrastructure gaps & overcome housing shortages. New dem& could be created for up lớn 80 million jobs in the trendline scenario and, in the sự kiện of accelerated investment, up khổng lồ 200 million more in the step-up scenario. These jobs include architects, engineers, electricians, carpenters, và other skilled tradespeople, as well as construction workers.

Investments in renewable energy, energy efficiency, and climate adaptation

Investments in renewable energy, such as wind và solar; energy-efficiency technologies; and adaptation và mitigation of climate change may create new dem& for workers in a range of occupations, including manufacturing, construction, and installation. These investments could create up to lớn ten million new jobs in the trendline scenario và up lớn ten million additional jobs globally in the step-up scenario.

‘Marketization’ of previously unpaid domestic work

The last trend we consider is the potential khổng lồ pay for services that substitute for currently unpaid and primarily domestic work. This so-called marketization of previously unpaid work is already prevalent in advanced economies, và rising female workforce participation worldwide could accelerate the trend. We estimate that this could create 50 million lớn 90 million jobs globally, mainly in occupations such as childcare, early-childhood education, cleaning, cooking, và gardening.

When we look at the net changes in job growth across all countries, the categories with the highest percentage job growth net of automation include the following:

healthcare providers professionals such as engineers, scientists, accountants, & analysts IT professionals and other giải pháp công nghệ specialists managers & executives, whose work cannot easily be replaced by machines educators, especially in emerging economies with young populations “creatives,” a small but growing category of artists, performers, and entertainers who will be in dem& as rising incomes create more demand for leisure và recreation builders và related professions, particularly in the scenario that involves higher investments in infrastructure and buildings manual & service jobs in unpredictable environments, such as home-health aides and gardeners
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Upcoming workforce transitions could be very large

The changes in net occupational growth or decline imply that a very large number of people may need khổng lồ shift occupational categories and learn new skills in the years ahead. The shift could be on a scale not seen since the transition of the labor force out of agriculture in the early 1900s in the United States and Europe, & more recently in in Đài Loan Trung Quốc.

Seventy-five sầu million to lớn 375 million may need to switch occupational categories & learn new skills.

We estimate that between 400 million & 800 million individuals could be displaced by automation and need lớn find new jobs by 2030 around the world, based on our midpoint & earliest (that is, the most rapid) automation adoption scenartiện ích ios. New jobs will be available, based on our scenargame ios of future labor demvà và the net impact of automation, as described in the next section.

However, people will need khổng lồ find their way inkhổng lồ these jobs. Of the total displaced, 75 million lớn 375 million may need khổng lồ switch occupational categories & learn new skills, under our midpoint và earliest automation adoption scenarios; under our trendline adoption scenario, however, this number would be very small—less than 10 million (Exhibit 1).


Exhibit 1

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In absolute terms, China faces the largest number of workers needing khổng lồ switch occupations—up khổng lồ 100 million if automation is adopted rapidly, or 12 percent of the 2030 workforce. While that may seem like a large number, it is relatively small compared with the tens of millions of Chinese who have moved out of agriculture in the past 25 years.

For advanced economies, the chia sẻ of the workforce that may need lớn learn new skills và find work in new occupations is much higher: up lớn one-third of the 2030 workforce in the United States and Germany, và nearly half in nhật bản.

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3. Will there be enough work in the future?

Today there is a growing concern about whether there will be enough jobs for workers, given potential automation. History would suggest that such fears may be unfounded: over time, labor markets adjust khổng lồ changes in demand for workers from technological disruptions, although at times with depressed real wages (Exhibit 2).


Exhibit 2

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We address this question about the future of work through two different sets of analyses: one based on modeling of a limited number of catalysts of new labor demand and automation described earlier, và one using a macroeconomic Mã Sản Phẩm of the economy that incorporates the dynamic interactions aý muốn variables.

If history is any guide, we could also expect that 8 lớn 9 percent of 2030 labor dem& will be in new types of occupations that have not existed before.

Both analyses lead us to lớn conclude that, with sufficient economic growth, innovation, và investment, there can be enough new job creation lớn offset the impact of automation, although in some advanced economies additional investments will be needed as per our step-up scenario khổng lồ reduce the risk of job shortages.

A larger challenge will be ensuring that workers have sầu the skills & tư vấn needed khổng lồ transition to new jobs. Countries that fail to lớn manage this transition could see rising unemployment và depressed wages.

The magnitude of future job creation from the trends described previously và the impact of automation on the workforce vary significantly by country, depending on four factors.

Wage level

Higher wages make the business case for automation adoption stronger. However, low-wage countries may be affected as well, if companies adopt automation khổng lồ boost quality, achieve tighter production control, move production closer lớn over consumers in high-wage countries, or other benefits beyond reducing labor costs.

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Demvà growth

Economic growth is essential for job creation; economies that are stagnant or growing slowly create few if any net new jobs. Countries with stronger economic & productivity growth & innovation will therefore be expected to experience more new labor dem&.

Demographics

Countries with a rapidly growing workforce, such as India, may enjoy a “demographic dividend” that boosts GDPhường growth—if young people are employed. Countries with a shrinking workforce, such as nhật bản, can expect lower future GDPhường. growth, derived only from productivity growth.

Mix of economic sectors & occupations

The automation potential for countries reflects the mix of economic sectors & the mix of jobs within each sector. nhật bản, for example, has a higher automation potential than the United States because the weight of sectors that are highly automatable, such as manufacturing, is higher.

Automation will affect countries in different ways

The four factors just described combine lớn create different outlooks for the future of work in each country (see interactive heat map). Japan is rich, but its economy is projected lớn grow slowly to lớn 2030. It faces the combination of slower job creation coming from economic expansion and a large nói qua of work that can be automated as a result of high wages & the structure of its economy.


However, nhật bản will also see its workforce shrink by 2030 by four million people. In the step-up scenario, & considering the jobs in new occupations we cannot envision today, Japan’s net change in jobs could be roughly in balance.

The United States and Germany could also face significant workforce displacement from automation by 2030, but their projected future growth—and hence new job creation—is higher. The United States has a growing workforce, và in the step-up scenario, with innovations leading lớn new types of occupations and work, it is roughly in balance. Germany’s workforce will decline by three million people by 2030, và it will have more than enough labor demand to lớn employ all its workers, even in the trendline scenario.

At the other extreme is India: a fast-growing developing country with relatively modest potential for automation over the next 15 years, reflecting low wage rates. Our analysis finds that most occupational categories are projected to lớn grow in India, reflecting its potential for strong economic expansion.

However, India’s labor force is expected to grow by 138 million people by 2030, or about 30 percent. India could create enough new jobs to lớn offset automation & employ these new entrants by undertaking the investments in our step-up scenario.

Đài Loan Trung Quốc & Mexico have higher wages than India and so are likely khổng lồ see more automation. China is still projected lớn have sầu robust economic growth và will have a shrinking workforce; like Germany, China’s problem could be a shortage of workers.

Mexico’s projected rate of future economic expansion is more modest, & it could benefit from the job creation in the step-up scenario plus innovation in new occupations and activities to make full use of its workforce.

Displaced workers will need to be reemployed quickly lớn avoid rising unemployment

To Model the impact of automation on overall employment và wages, we use a general equilibrium Model that takes into account the economic impacts of automation and dynamic interactions. Automation has at least three distinct economic impacts. Most attention has been devoted to lớn the potential displacement of labor. But automation also may raise labor productivity: firms adopt automation only when doing so enables them khổng lồ produce more or higher-unique output with the same or fewer inputs (including material, energy, và labor inputs). The third impact is that automation adoption raises investment in the economy, lifting short-term GDPhường growth. We Mã Sản Phẩm all three effects. We also create different scenargame ios for how quickly displaced workers find new employment, based on historical data.

The results reveal that, in nearly all scenarios, the six countries that are the focus of our report (Đài Loan Trung Quốc, Germany, India, Japan, Mexico, & the United States) could expect to be at or very near full employment by 2030. However, the Model also illustrates the importance of reemploying displaced workers quickly.

If displaced workers are able lớn be reemployed within one year, our model shows automation lifting the overall economy: full employment is maintained in both the short và long term, wages grow faster than in the baseline Model, and productivity is higher.

However, in scenargame ios in which some displaced workers take years to find new work, unemployment rises in the short to medium term. The labor market adjusts over time and unemployment falls—but with slower average wage growth. In these scenartiện ích ios, average wages kết thúc up lower in 2030 than in the baseline mã sản phẩm, which could dampen aggregate dem& & long-term growth.

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4. What will automation mean for skills & wages?

In general, the current educational requirements of the occupations that may grow are higher than those for the jobs displaced by automation. In advanced economies, occupations that currently require only a secondary education or less see a net decline from automation, while those occupations requiring college degrees and higher grow.

In India and other emerging economies, we find higher labor demand for all education levels, with the largest number of new jobs in occupations requiring a secondary education, but the fastest rate of job growth will be for occupations currently requiring a college or advanced degree.

Workers of the future will spkết thúc more time on activities that machines are less capable of, such as managing people, applying expertise, và communicating with others. They will spkết thúc less time on predictable physical activities and on collecting and processing data, where machines already exceed human performance. The skills và capabilities required will also shift, requiring more social và emotional skills và more advanced cognitive sầu capabilities, such as logical reasoning và creativity.

Wages may stagnate or fall in declining occupations. Although we vày not mã sản phẩm shifts in relative wages across occupations, the basic economics of labor supply & dem& suggests that this should be the case for occupations in which labor dem& declines.

Our analysis shows that most job growth in the United States và other advanced economies will be in occupations currently at the high over of the wage distribution. Some occupations that are currently low wage, such as nursing assistants và teaching assistants, will also increase, while a wide range of middle-income occupations will have sầu the largest employment declines.

Income polarization could continue. Policy choices such as increasing investments in infrastructure, buildings, and energy transitions could help create additional demand for middle-wage jobs such as construction workers in advanced economies.

The wage-trover picture is quite different in emerging economies such as Đài Loan Trung Quốc and India, where our scenarios show that middle-wage jobs such as retail salespeople và teachers will grow the most as these economies develop. This implies that their consuming class will continue to grow in the decades ahead.

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5. How do we manage the upcoming workforce transitions?

The benefits of artificial intelligence & automation lớn users & businesses, và the economic growth that could come via their productivity contributions, are compelling. They will not only contribute to dynamic economies that create jobs but also help create the economic surpluses that will enable societies khổng lồ address the workforce transitions that will likely happen regardless.

Faced with the scale of worker transitions we have sầu described, one reaction could be to lớn try to lớn slow the pace and scope of adoption in an attempt to preserve the status quo. But this would be a mistake. Although slower adoption might limit the scale of workforce transitions, it would curtail the contributions that these technologies make lớn business dynamism and economic growth. We should embrace these technologies but also address the workforce transitions & challenges they bring. In many countries, this may require an initiative on the scale of the Marshall Plan, involving sustained investment, new training models, programs khổng lồ ease worker transitions, income support, & collaboration between the public and private sectors.

All societies will need lớn address four key areas.

Maintaining robust economic growth khổng lồ support job creation

Sustaining robust aggregate demand growth is critical to support new job creation, as is support for new business formation & innovation. Fiscal và monetary policies that ensure sufficient aggregate dem&, as well as tư vấn for business investment & innovation, will be essential. Targeted initiatives in certain sectors could also help, including, for example, increasing investments in infrastructure và energy transitions.

Scaling and reimagining job retraining & workforce skills development

Providing job retraining & enabling individuals khổng lồ learn marketable new skills throughout their lifetime will be a critical challenge—and for some countries, the central challenge. Midcareer retraining will become ever more important as the skill mix needed for a successful career changes. Business can take a lead in some areas, including with on-the-job training & providing opportunities lớn workers khổng lồ nâng cấp their skills.

Improving business and labor-market dynamism, including mobility

Greater fluidity will be needed in the labor market khổng lồ manage the difficult transitions we anticipate. This includes restoring now-waning labor mobility in advanced economies. Digital talent platforms can foster fluidity, by matching workers & companies seeking their skills và by providing a plethora of new work opportunities for those open to lớn taking them. Policy makers in countries with inflexible labor markets can learn from others that have sầu deregulated, such as Germany, which transformed its federal unemployment agency into a powerful job-matching entity.

Providing income & transition support to workers

Income support and other forms of transition assistance khổng lồ help displaced workers find gainful employment will be essential. Beyond retraining, a range of policies can help, including unemployment insurance, public assistance in finding work, và portable benefits that follow workers between jobs.

We know from history that wages for many occupations can be depressed for some time during workforce transitions. More permanent policies lớn supplement work incomes might be needed khổng lồ tư vấn aggregate demvà và ensure societal fairness. More comprehensive sầu minimum-wage policies, universal basic income, or wage gains tied to productivity growth are all possible solutions being explored.

Policy makers, business leaders, và individual workers all have sầu constructive sầu và important roles to play in smoothing workforce transitions ahead. History shows us that societies across the globe, when faced with monumental challenges, often rise to the occasion for the well-being of their citizens.

Yet over the past few decades, investments và policies lớn support the workforce have eroded. Public spending on labor-force training và tư vấn has fallen in most member countries of the Organisation for Economic Co-operation và Development (OECD). Educational models have sầu not fundamentally changed in 100 years. It is now critical khổng lồ reverse these trends, with governments making workforce transitions và job creation a more urgent priority.

We will all need creative visions for how our lives are organized and valued in the future, in a world where the role & meaning of work start khổng lồ shift.

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Businesses will be on the front lines of the workplace as it changes. This will require them khổng lồ both retool their business processes and reevaluate their talent strategies và workforce needs, carefully considering which individuals are needed, which can be redeployed khổng lồ other jobs, & where new talent may be required. Many companies are finding it is in their self-interest—as well as part of their societal responsibility—to lớn train and prepare workers for a new world of work.

Individuals, too, will need khổng lồ be prepared for a rapidly evolving future of work. Acquiring new skills that are in dem& and resetting intuition about the world of work will be critical for their own well-being. There will be demvà for human labor, but workers everywhere will need khổng lồ rethink traditional notions of where they work, how they work, and what talents và capabilities they bring lớn that work.