Recent research by my employer, the McKinsey Global Institute, sheds light on the transformations ahead on both sides of the Atlantic and highlights a dual challenge: the need to accelerate technology adoption amid tightening labor markets and a need to upskill and reskill to increase productivity growth.
This latest look at the future of work reveals that by 2030, up to 30 percent of current work hours could be automated due to automation and generative AI. Our updated modeling finds that demand for workers in STEM-related, healthcare, and other high-skill professions would rise, while demand for lower-wage occupations such as office workers, production workers, and customer service representatives would decline. Efforts to achieve net-zero emissions, an aging workforce, growth in e-commerce, infrastructure and technology investment, and overall economic growth will also affect employment demand.
Automation and generative AI represent an opportunity for productivity growth—probably one of the biggest opportunities for productivity growth that we have seen in decades. Productivity—the measure of a country’s or company’s outputs with the same inputs—has been decelerating in the U.S. and Europe for almost a generation. We care about productivity growth because over time it is key to improving living standards. Productivity growth in the U.S. hit 4% after World War II and has been in the 1 – 2% range for the last 20 years. And while European Union productivity growth was in the 6 - 8% range for a few decades after World War II, it has been below 2% (and even often below 1%) for the last 30 years.
However, capturing the productivity opportunity from AI will require workers to transition from declining occupations to rising ones. Companies need workers with more skills and different skills to match the jobs we will have in the future. In Europe, by our estimates, a faster technology adoption scenario could be associated with productivity growth of roughly 2 to 3 percent per year, and require some 12 million occupational transitions, roughly double the pace of pre-COVID occupational shifts. In the United States, with its more dynamic labor market, the trend would be closer to the historical norm.
Businesses Will Need A Major Skills Upgrade
While the productivity improvement from automation and generative AI is appealing, the successful integration of AI into the workplace will require a major skills upgrade. Demand for technological and social and emotional skills could rise as demand for physical and manual and higher cognitive skills stabilizes. Surveyed executives in Europe and the United States expressed a need not just for advanced IT and data analytics but also for critical thinking, creativity, and teaching and training—skills they report as currently being in short supply. To bridge these gaps, companies are increasingly focusing on retraining their workforce, rather than relying solely on hiring or subcontracting. For example, in the automotive industry, executives anticipate that 36 percent of their workforce will require retraining, while executives in financial services indicated 28 percent of their workers will need to be retrained.
The implications of these shifts are profound, not only for businesses but also for workers across different wage brackets. Lower-wage workers, in particular, face the risk of job displacement if they cannot transition to higher-wage roles. This could lead to a more polarized labor market, with significant disparities between high and low-wage earners.
To mitigate these risks and capitalize on the opportunities presented by AI, organizations and policymakers need to foster an environment that promotes rapid technology adoption and proactive worker redeployment. This balanced approach will be crucial in turning the challenges of the AI era into opportunities to increase productivity and societal well-being.
For companies, leading through AI advancements will require a strong understanding of the potential of AI and generative AI—not just in a few senior roles, but across a broad range of leaders. This understanding will not be static. It will require ongoing education and discussion and also feed into business planning and innovation. In addition, planning the full strategic workforce shift at the company level will require understanding what skills employees have today and what skills will be needed in the future. Mapping that out and assessing the biggest gaps and how to fill them will be key. Then training to fill those gaps or acquiring them externally will enable progress.
Acting on these elements can help companies and leaders make faster progress in capturing value from AI while ensuring their employees are able to capture some of the benefits as well.
This article originally appeared in Forbes.
