跳过导航


Editorial Rating

9

getAbstract Rating

  • Analytical
  • Well Structured
  • Overview

Recommendation

In this timely update on the future of work in the United States, researchers from the McKinsey Global Institute examine the trends that have emerged since their 2019 study on automation and US workplaces. They catalog the forces shaping their forecast, including lasting pandemic effects, federal investment and technological advances, particularly AI. In the post-pandemic landscape, the emergence of generative AI tools like ChatGPT raises job loss concerns. The researchers emphasize the likelihood of significant shifts in occupational demand, urging you to prepare for job transitions amid ongoing uncertainty as companies work to build an inclusive, productivity-driven economy.

Summary

The pandemic changed the US job market and increased the demand for better, higher-paying jobs.

Examining the job market that experts believe will develop in the United States in the decade leading up to 2033 requires considering its current trajectory. After COVID-19 setbacks, the US job market rebounded strongly, maintaining an unemployment rate below 4% for more than a year, dating from early 2022. Significant occupational shifts occurred during this tight labor market, as people quit their jobs to pursue better prospects and higher pay in both 2021 (48 million people) and 2022 (51 million people).

Managers and professionals who make essential contributions in business, law and STEM fields thrived due to remote work. These sectors collectively added 3.3 million jobs between 2019 and 2022. The surge in e-commerce bolstered transportation services, notably warehousing, resulting in more than 30% growth in jobs for workers handling stock and filling orders, and around 15% growth in shipping, receiving and inventory clerking. Researchers expect similar trends to persist into the future.

The United States&#...

About the Authors

The report’s authors are research leaders Kweilin Ellingrud, an McKinsey Global Institute (MGI) director, McKinsey partner Saurabh Sanghvi; MGI senior expert and associate partner Gurneet Singh Dandona; MGI partners Anu Madgavkar and Michael Chui; MGI director Olivia White; and project team leader Paige Hasebe.  MGI executive editor Lisa Renaud edited the report.


Comment on this summary

More on this topic

Related Skills

人工智能转型,实施基于人工智能的流程优化,跨部门整合人工智能解决方案,评估企业采用人工智能的准备情况
数字化转型
启用数字化组织,促进数字化组织变革,提高运营中的数字化效率,支持数字工具的整合,为数字平台调整工作流
创业
人力资源
利用人工智能进行产品开发,识别产品创作的人工智能工具,将人工智能整合到产品生命周期中,利用人工智能洞
在日常任务中利用人工智能,将人工智能工具整合到工作流程中,使用人工智能自动化重复性任务,利用人工智能
管理学习与发展,制定企业学习战略,管理员工学习路径,评估团队的发展需求,优化学习资源分配,评估培训项
理解人工智能,向同事解释基本的人工智能概念,区分人工智能与传统软件解决方案,总结人工智能在现代工作场
职场技能
了解生成性人工智能,识别生成性人工智能机会,探索生成性人工智能的应用,生成性人工智能在商业中的案例研
理解人工智能对工作的影响,评估人工智能对日常任务的影响,评估人工智能驱动的工作场所变化,识别人工智能
提升员工技能和知识
利用人工智能生成创意,使用人工智能工具进行头脑风暴,利用人工智能算法增强创造力,利用人工智能生成新产
利用人工智能提升个人生产力,结合人工智能工具优先处理任务,通过人工智能应用简化日常工作,利用人工智能