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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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How can South Africa embrace the Fourth Industrial Revolution (4IR) to rekindle economic growth and transformation, revitalise skills, and create high-quality jobs in large numbers? And how can the country mitigate the risk that the 4IR will lead to job losses - given that unemployment today stands at 29 per cent, its highest level in a decade? This paper is intended as a contribution to the national conversation about the 4IR and the future of work in South Africa. The paper focuses on the elements of digitisation, machine learning and automation and draws on key findings and insights from McKinsey's research on the future of work in an age of rapid technology adoption - both in South Africa and across the globe. It also benefits from interviews with several leading businesspeople, education providers and social-sector leaders.

Building on this evidence and these insights, our research suggests that while the advance of technology could be disruptive, it primarily represents a substantial opportunity. South Africa can harness technology to reignite productivity, growth, and job creation. But, to seize that opportunity, concerted action will be needed from businesses, government, labour organisations and educational institutions. The case for taking such action is compelling, given South Africa's high levels of unemployment and the need to accelerate inclusive economic growth. One key challenge is that the country has been slow to nurture the skills needed for companies to compete and grow in an increasingly technology-driven world. That matters for the millions of young South Africans struggling to build their own futures.

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Automation is not a new phenomenon, and fears about its transformation of the workplace and effects on employment date back centuries, even before the Industrial Revolution in the 18th and 19th centuries. Rapid recent advances in automation technologies, including artificial intelligence, autonomous systems, and robotics are now raising the fears anew - and with new urgency. The January 2017 report on automation, 'A future that works: automation, employment, and productivity' [available in VOCEDplus at TD/TNC 127.353], analyzed the automation potential of the global economy, the timelines over which the phenomenon could play out, and the powerful productivity boost that automation adoption could deliver. This report goes a step further by examining both the potential labor market disruptions from automation and some potential sources of new labor demand that will create jobs. It includes scenarios that seek to address some of the questions most often raised in the public debate. Will there be enough work in the future to maintain full employment, and if so what will that work be? Which occupations will thrive, and which ones will wither? What are the potential implications for skills and wages as machines perform some or the tasks that humans now do?

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The age of automation, and on the near horizon, artificial intelligence (AI) technologies, offer new job opportunities and avenues for economic advancement but women face new challenges overlaid on long-established ones. Between 40 million and 160 million women globally may need to transition between occupations by 2030, often into higher-skilled roles. This research argues that, to weather this disruption, women (and men) need to be skilled, mobile, and tech-savvy but women face pervasive barriers on each, and will need targeted support to move forward in the world of work. The research finds that if women make these transitions, they could be on the path to more productive, better-paid work. If they cannot, they could face a growing wage gap or be left further behind when progress toward gender parity in work is already slow.

This new research explores potential patterns in 'jobs lost' (jobs displaced by automation), 'jobs gained' (job creation driven by economic growth, investment, demographic changes, and technological innovation), and 'jobs changed' (jobs whose activities and skill requirements change from partial automation) for women by exploring several scenarios of how automation adoption and job creation trends could play out by 2030 for men and women given current gender patterns in the global workforce. These scenarios are not meant to predict the future; rather, they serve as a tool to understand a range of possible outcomes and identify interventions needed. The term jobs is used as shorthand for full-time-equivalent workers. The research examines six mature economies (Canada, France, Germany, Japan, the United Kingdom, and the United States) and four emerging economies (China, India, Mexico, and South Africa), which together account for around half of the world's population and about 60 per cent of global GDP.

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Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance in a range of work activities, including ones requiring cognitive capabilities. In this report, part of the McKinsey Global Institute's ongoing research into the future of work, the authors analyze the automation potential of the global economy, the factors that will determine the pace and extent of workplace adoption, and the economic impact associated with its potential. The five factors affecting pace and extent of adoption are technical feasibility, cost of developing and deploying solutions, labour market dynamics, economic benefits, and regulatory and social acceptance.

Other key points are that: (1) automation of activities can enable businesses to improve performance by reducing errors and improving quality and speed, and in some cases, achieving outcomes that go beyond human capabilities; (2) while less than five per cent of all occupations can be automated entirely using demonstrated technologies, about 60 per cent of all occupations have at least 30 per cent of constituent activities that could be automated - more occupations will change than will be 'automated away'; (3) activities most susceptible to automation involve physical activities in highly structured and predictable environments, as well as the collection and processing of data; (4) people will need to continue working alongside machines to produce the growth in per capita [gross domestic product] GDP to which countries around the world aspire; and (5) for business, the performance benefits of automation are relatively clear, but the issues are more complicated for policy makers - encouraging investment and innovation whilst helping workers and institutions adapt to the impact on employment.

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