AI, Automation, and the Future of Work: Navigating the Transformation

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Explore how AI and automation are reshaping the workplace, creating both opportunities and challenges. Learn about workforce transitions, required skills, and key solutions for a smooth adaptation. (158 characters)

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AI, automation, future of work, workforce transitions, job displacement, skills gap, reskilling, upskilling, AI adoption, workplace redesign, economic growth, productivity, policy recommendations

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AI, Automation, and the Future of Work: Ten Things to Solve For

As machines increasingly complement human labor in the workplace, we will all need to adjust to reap the benefits. Automation and artificial intelligence (AI) are transforming businesses and will contribute to economic growth via contributions to productivity. They will also help address “moonshot” societal challenges in areas from health to climate change.

At the same time, these technologies will transform the nature of work and the workplace itself. Machines will be able to carry out more of the tasks done by humans, complement the work that humans do, and even perform some tasks that go beyond what humans can do. As a result, some occupations will decline, others will grow, and many more will change.

While we believe there will be enough work to go around (barring extreme scenarios), society will need to grapple with significant workforce transitions and dislocation. Workers will need to acquire new skills and adapt to the increasingly capable machines alongside them in the workplace. They may have to move from declining occupations to growing and, in some cases, new occupations.

This article examines both the promise and the challenge of automation and AI in the workplace and outlines some of the critical issues that policymakers, companies, and individuals will need to solve.

Accelerating Progress in AI and Automation

Rapid Technological Progress

New generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. AI has made especially large strides in recent years, as machine-learning algorithms have become more sophisticated and made use of huge increases in computing power and of the exponential growth in data available to train them.

Potential to Transform Businesses and Contribute to Economic Growth

Deployment of AI and automation technologies can do much to lift the global economy and increase global prosperity, at a time when aging and falling birth rates are acting as a drag on growth. AI and automation have the potential to reverse that decline: productivity growth could potentially reach 2 percent annually over the next decade, with 60 percent of this increase from digital opportunities.

Potential to Help Tackle Several Societal Moonshot Challenges

AI is also being used in areas ranging from material science to medical research and climate science. Application of the technologies in these and other disciplines could help tackle societal moonshot challenges. For example, researchers at Geisinger have developed an algorithm that could reduce diagnostic times for intracranial hemorrhaging by up to 96 percent.

Challenges Remain

AI and automation still face challenges. The limitations are partly technical, such as the need for massive training data and difficulties “generalizing” algorithms across use cases. Potential bias in the training data and algorithms, as well as data privacy, malicious use, and security are all issues that must be addressed. Adoption is already uneven across sectors and countries. The finance, automotive, and telecommunications sectors lead AI adoption.

How AI and Automation Will Affect Work

Even as AI and automation bring benefits to business and society, we will need to prepare for major disruptions to work.

Automation of Activities

Our analysis of more than 2000 work activities across more than 800 occupations shows that certain categories of activities are more easily automatable than others. They include physical activities in highly predictable and structured environments, as well as data collection and data processing. These account for roughly half of the activities that people do across all sectors. The least susceptible categories include managing others, providing expertise, and interfacing with stakeholders.

Nearly all occupations will be affected by automation, but only about 5 percent of occupations could be fully automated by currently demonstrated technologies. We find that about 30 percent of the activities in 60 percent of all occupations could be automated. This means that most workers—from welders to mortgage brokers to CEOs—will work alongside rapidly evolving machines. The nature of these occupations will likely change as a result.

Jobs Lost and Gained

Automation will displace some workers. Around 15 percent of the global workforce, or about 400 million workers, could be displaced by automation in the period 2016–2030. Even as workers are displaced, there will be growth in demand for work and consequently jobs. Some of the largest gains will be in emerging economies such as India, where the working-age population is already growing rapidly.

Many other new occupations that we cannot currently imagine will also emerge and may account for as much as 10 percent of jobs created by 2030.

Jobs Changed

Partial automation will become more prevalent as machines complement human labor. For example, AI algorithms that can read diagnostic scans with a high degree of accuracy will help doctors diagnose patient cases and identify suitable treatment. In other fields, jobs with repetitive tasks could shift toward a model of managing and troubleshooting automated systems.

Key Workforce Transitions and Challenges

While we expect there will be enough work to ensure full employment in 2030 based on most of our scenarios, the transitions that will accompany automation and AI adoption will be significant. The mix of occupations will change, as will skill and educational requirements. Work will need to be redesigned to ensure that humans work alongside machines most effectively.

Skills for the Future

Automation will accelerate the shift in required workforce skills. Demand for advanced technological skills such as programming will grow rapidly. Social, emotional, and higher cognitive skills, such as creativity, critical thinking, and complex information processing, will also see growing demand. Basic digital skills demand has been increasing and that trend will continue and accelerate. Demand for physical and manual skills will decline but will remain the single largest category of workforce skills in 2030 in many countries.

Occupational Changes

Our research suggests that, in a midpoint scenario, around 3 percent of the global workforce will need to change occupational categories by 2030, though scenarios range from about 0 to 14 percent. Some of these shifts will happen within companies and sectors, but many will occur across sectors and even geographies.

Workplace Evolution

Workplaces and workflows will change as more people work alongside machines. As intelligent machines and software are integrated more deeply into the workplace, workflows and workspaces will continue to evolve to enable humans and machines to work together.

Wage Pressure

The occupational mix shifts will likely put pressure on wages. The risk is that automation could exacerbate wage polarization, income inequality, and the lack of income advancement that has characterized the past decade across advanced economies, stoking social, and political tensions.

Existing Workforce Challenges

Most countries already face the challenge of adequately educating and training their workforces to meet the current requirements of employers. One lesson of the past decade is that while globalization may have benefited economic growth and people as consumers, the wage and dislocation effects on workers were not adequately addressed.

Ten Things to Solve For

In the search for appropriate measures and policies to address these challenges, we should not seek to roll back or slow diffusion of the technologies. Rather, the focus should be on ways to ensure that the workforce transitions are as smooth as possible. This is likely to require actionable and scalable solutions in several key areas:

• Ensuring robust economic and productivity growth.
• Fostering business dynamism.
• Evolving education systems and learning for a changed workplace.
• Investing in human capital.
• Improving labor-market dynamism.
• Redesigning work.
• Rethinking incomes.
• Rethinking transition support and safety nets for workers affected.
• Investing in drivers of demand for work.
• Embracing AI and automation safely.

Conclusion

There is work for everyone today and there will be work for everyone tomorrow, even in a future with automation. Yet that work will be different, requiring new skills, and a far greater adaptability of the workforce than we have seen. Training and retraining both midcareer workers and new generations for the coming challenges will be an imperative. Government, private-sector leaders, and innovators all need to work together to better coordinate public and private initiatives, including creating the right incentives to invest more in human capital. The future with automation and AI will be challenging, but a much richer one if we harness the technologies with aplomb—and mitigate the negative effects.