Will you lose your jobs in 2030?

Workforce transitions in a time of automation

Visuals by Shiying Cheng | Dec 9, 2017

"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, and algorithms that respond to customer-service inquiries are all manifestations of powerful new forms of automation. Yet even as these technologies increase productivity and improve our lives, their use will substitute for some work activities humans currently perform—a development that has sparked much public concern."

In the following section, this visualization project highlights "scenarios for the future of work in six countries: China, Germany, India, Japan, Mexico, and the United States. The charts show a range of possible outcomes for jobs displaced by automation adoption to 2030 and scenarios for future jobs that could be created by seven catalysts of labor demand, as well as by new occupations that could arise."

Text and Data from McKinsey Global Institute’s latest report, Jobs lost, jobs gained: Workforce transitions in a time of automation

Creatives

Includes: Aritists, designers, entertainers, and media workers

Technology professionals

Includes: Computer engineers, and computer specialists

Managers and executives

Includes: CEOs, sales managers

Teachers

Includes: Schoolteachers, postsecondary teachers, other education professionals, and education support workers

Builders

Includes: Building engineers, architects, surveyors, construction workers, installation and repair workers, crane and tower operators

Care providers

Includes: Doctors, nurses, physician assistants, pharmacists, therapists, health aides and health support, childcare workers, health technicians, community and social workers

Professionals

Includes: Account managers, engineers, business and financial specialists, lawyers and judges, legal-industry support staff, math specialists, scientists, and academics

In 2030

China: "China’s shift out of agriculture into manufacturing and services is likely to continue and, as incomes continue rising, consumption will increase. With its aging and shrinking workforce, China will benefit from embracing automation to increase productivity and meet projected 2030 labor needs."

Germany: "Germany has an aging population and a declining working-age population. Relatively high wages make a stronger case for early automation adoption, while medium GDP growth creates sufficient labor demand in most scenarios. Health-care needs from aging and increased consumer spending will drive most job creation."

India: "India is expected to continue industrializing as its economy shifts away from agriculture. As GDP per capita continues to expand amid rapid growth of the labor force, many of India’s jobs of the future will be driven by construction and the consumption habits of the expanding middle class."

Japan: "Japan’s sector mix and relatively high wages will speed automation adoption, while relatively slow GDP per capita growth could dampen labor demand. The decline in the working-age population will act as a countervailing force, but a step-up scenario of job creation will be needed to sustain future employment."

Mexico: "Mexico has a young population and a growing workforce. Mid- to low-wage levels may slow automation adoption, while comparatively low GDP growth may temper growth in labor demand. The step-up scenario will create enough labor demand to offset the effects of both automation and demographics."

United States: "Automation adoption will likely be significant in the United States, even as steady projected GDP per capita growth drives new labor demand. While labor demand will enable employment of displaced workers in the step-up scenario, up to one-third of the workforce may need to change occupational categories."