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The impact of [Coronavirus Disease 2019] COVID-19 on work, the workforce, and the workplace will persist after the health crisis has subsided. This research examines how the trends accelerated by the pandemic may reshape work in the long term. We explore these changes through 2030 in eight countries with diverse economic and labor market models: China, France, Germany, India, Japan, Spain, the United Kingdom, and the United States. Together, these eight countries account for almost half the global population and 62 per cent of GDP. The pandemic has, for the first time, elevated the importance of the physical dimension of work. In this research, we define ten work arenas that group occupations according to their proximity to coworkers and customers, the number of interpersonal interactions involved, and their on-site and indoor nature. We find that jobs in work arenas with higher levels of proximity are likely to see greater transformation after the pandemic, triggering knock-on effects in other work arenas as business models shift in response.

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The US labor market is going through a rapid evolution in the way people work and the work people do. The nature of work has changed as many workers have stuck with remote or hybrid models and employers have sped up their adoption of automation technologies. More recently, the accelerated development of generative artificial intelligence (AI), with its advanced natural language capabilities, has extended the possibilities for automation to a much wider set of occupations. Multiple forces are set to fuel growth in certain occupations and erode jobs in others. They generally fall into three categories: automation, including generative AI; an injection of federal investment into infrastructure and the net-zero transition; and long-term structural trends such as aging, continuing investment in technology, and the growth of e-commerce and remote work. This report explores: Which jobs will be in demand? Which ones are shrinking? And which ones could be hardest to fill?

Key findings include: (1) By 2030, activities that account for up to 30 per cent of hours currently worked across the US economy could be automated - a trend accelerated by generative AI. However, we see generative AI enhancing the way [science, technology, engineering and mathematics] STEM, creative, and business and legal professionals work rather than eliminating a significant number of jobs outright. Automation's biggest effects are likely to hit other job categories. Office support, customer service, and food service employment could continue to decline; (2) An additional 12 million occupational transitions may be needed by 2030. As people leave shrinking occupations, the economy could reweight toward higher-wage jobs. Workers in lower-wage jobs are up to 14 times more likely to need to change occupations than those in highest-wage positions, and most will need additional skills to do so successfully. Women are 1.5 times more likely to need to move into new occupations than men; and (3) The US will need workforce development on a far larger scale as well as more expansive hiring approaches from employers. Employers will need to hire for skills and competencies rather than credentials, recruit from overlooked populations (such as rural workers and people with disabilities), and deliver training that keeps pace with their evolving needs.

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