We live in an era of disruption in which powerful global forces are changing how we live and work. The rise of China, India, and other emerging economies; the rapid spread of digital technologies; the growing challenges to globalization; and, in some countries, the splintering of long-held social contracts are all roiling business, the economy, and society. These and other global trends offer considerable new opportunities to companies, sectors, countries, and individuals that embrace them successfully—but the downside for those who cannot keep up has also grown disproportionately. For business leaders, policy makers, and individuals, figuring out how to navigate these skewed times may require some radical rethinking.
This briefing note for the 2019 World Economic Forum in Davos draws on recent research by the McKinsey Global Institute (MGI). It focuses on both the value-creating opportunities and the intense competitive and societal challenges we all face in this era of technological ferment:
- The disruption is intensifying
- The gulf between those embracing change and those falling behind is growing
- Moving toward a more inclusive society
The disruption is intensifying
Powerful forces are changing our world. Their impact is touching all countries, sectors, companies, and, increasingly, workers and the environment. They are also morphing in some unexpected ways and combining to create even greater impact than we expected.
The center of economic gravity is shifting east and south
Emerging economies, led by China and India, have accounted for almost two-thirds of global GDP growth and more than half of new consumption in the past 15 years. Among emerging economies, our research has identified 18 high-growth “outperformers” that have achieved powerful and sustained long-term growth—and lifted more than one billion people out of extreme poverty since 1990.1 Seven of these outperformers (China, Hong Kong, Indonesia, Malaysia, Singapore, South Korea, and Thailand) have averaged GDP growth of at least 3.5 percent for the past 50 years. Eleven other countries (Azerbaijan, Belarus, Cambodia, Ethiopia, India, Kazakhstan, Laos, Myanmar, Turkmenistan, Uzbekistan, and Vietnam) have achieved faster average growth of at least 5 percent annually over the past 20 years. Underlying their performance are pro-growth policy agendas based on productivity, income, and demand—and often fueled by strong competitive dynamics. The next wave of outperformers now looms, as countries from Bangladesh and Bolivia to the Philippines, Rwanda, and Sri Lanka adopt a similar agenda and achieve rapid growth.
The dynamism of these economies has gone hand in hand with the rise of highly competitive emerging-market companies. On average, outperformer economies have twice as many companies with revenue over $500 million as other emerging economies. These companies play a growing role on the global stage: while they accounted for only about 25 percent of the total revenue and net income of all large public companies in 2016, they contributed about 40 percent of the revenue growth and net-income growth from 2005 to 2016. More than 120 of these companies have joined the Fortune Global 500 list since 2000,2 and by several measures, they are already more innovative, nimble, and competitive than Western rivals. They can also earn better returns for investors. Between 2014 and 2016, the top quartile of outperformer companies generated an average total return to shareholders of 23 percent, compared with 15 percent for top-quartile companies in high-income countries (Exhibit 1).
Globalization patterns are changing, with rapid growth in data flows
Much of the recent focus on globalization has been on trade pullbacks, rising protectionist measures, and public hostility. As a phenomenon, however, globalization has not gone into reverse; rather, it has shifted gears to become more data driven and more focused on south–south flows. While cross-border flows of goods and finance have lost momentum, data flows are helping drive global GDP. Cross-border data bandwidth grew by 148 times between 2005 and 2017, to more than 700 terabytes per second—a larger quantity per second than the quantity contained in the entire US Library of Congress—and is projected to grow by another nine times in the next five years as digital flows of commerce, information, searches, video, communication, and intracompany traffic continue to surge.
The developing world is driving global connectedness. For the first time in history, emerging economies are counterparts on more than half of global trade flows, and south–south trade is the fastest-growing type of connection. South–south and China–south trade jumped from 8 percent of the global total in 1995 to 20 percent in 2016.
Amid these shifts, our latest research suggests that China’s relationship with the world may be at a turning point. By 2017, China accounted for 15 percent of world GDP. For the first time since 1870, it overtook the United States to become the world’s largest economy in purchasing-power-parity terms. (In nominal terms, China’s GDP was 64 percent of the United States’ GDP in 2017, making it the second-largest economy in the world.) Over the past decade, even as its economy has grown, China’s exposure to the world, as measured by the magnitude of flows of trade, technology, and capital with the rest of the world relative to its economy, has declined. At the same time, the world’s exposure to China (the magnitude of flows with China relative to the global economy) has increased since 2000. Metrics used to measure exposure include China’s importance as a market and as a supplier of goods and services to the global economy, the importance of Chinese technological exports to global R&D spending and China’s technology import and its influence in domestic R&D, and, for capital, China’s importance as a supplier of financing and as a destination for investments (Exhibit 2).
Global value chains are also evolving. They are being reshaped in part by technology, including automation, which could amplify the shift toward more localized production of goods near consumer markets. And they are changing along with global demand, as China and other developing countries consume more of what they produce and export a smaller share. As emerging economies build more comprehensive domestic supply chains, they are reducing their reliance on imported intermediate inputs.
Would you like to learn more about the McKinsey Global Institute?
The result is that goods-producing value chains have become less trade intensive, even as cross-border services are growing briskly—and generating more economic value than trade statistics capture, according to our analysis. Trade based on labor-cost arbitrage has been declining and now makes up only 20 percent of goods trade. Global value chains are becoming more knowledge intensive and reliant on high-skill labor. Finally, goods-producing value chains (particularly those for automotive as well as computers and electronics) are becoming more regionally concentrated, as companies increasingly establish production in proximity to demand.
The pace of technological progress is accelerating
Businesses have been harnessing advanced analytics and the Internet of Things to transform their operations, and those in the forefront reap the benefits: companies that are digital leaders in their sectors have faster revenue growth and higher productivity than their less-digitized peers do. They improve profit margins three times more rapidly than average and are often the fastest innovators and the disruptors of their sectors. The forces of digital have yet to become fully mainstream, however: on average, industries are less than 40 percent digitized.
Now comes the next wave of innovation, in the form of advanced automation and artificial intelligence (AI). An explosion in algorithmic capabilities, computing capacity, and data is enabling beyond-human machine competencies and a new generation of system-level innovation, such as the driverless car. Machines already surpass human performance in areas like image recognition and object detection, and these capabilities can be used to diagnose skin cancer or lip-read more accurately than human experts can.
While these technologies still have limitations, massive productivity gains across sectors are already visible, with AI use cases in functions such as sales and marketing (for example, “next product to buy” personalization), supply chain and logistics, and preventive maintenance. Our analysis of more than 400 use cases found that AI could improve on traditional analytics techniques in 69 percent of potential use cases. Deep learning could account for as much as $3.5 trillion to $5.8 trillion in annual value, or 40 percent of the value created by all analytics techniques (Exhibit 3). For the global economy, too, AI adoption could be a boon, potentially raising global GDP by as much as $13 trillion by 2030, or about 1.2 percent additional GDP growth per year, according to a simulation we conducted.
AI could also contribute to tackling pressing societal challenges, from healthcare to climate change to humanitarian crises; a library of social-good use cases we collected maps to all 17 of the United Nation’s Sustainable Development Goals. Yet AI is not a silver bullet. Significant bottlenecks, especially relating to data accessibility and talent, will need to be overcome, and AI presents risks that will need to be mitigated.
As populations age, developed regions must rely more on waning productivity and greater migration
Labor-productivity growth is near historic lows in the United States and much of Western Europe, despite a job-rich recovery after the global financial crisis. Productivity growth averaged just 0.5 percent in 2010 to 2014, down from 2.4 percent a decade earlier. This weakness comes as birth rates in countries from Germany, Japan, and South Korea to China and Russia are far below replacement rates and working-age-population growth has either slowed or gone into reverse. These demographic trends put a greater onus on productivity growth to propel GDP growth: over the past 50 years, just under half of GDP growth in G-20 countries came from labor-force growth, while productivity growth accounted for the remainder.
Digitization promises significant productivity-boosting opportunities in the future, but the benefits have not yet materialized at scale in productivity data because of adoption barriers and lag effects as well as transition costs. Our research suggests that productivity could grow by at least 2 percent annually over the next ten years, with 60 percent coming from digital opportunities.
The retired and elderly over 60 in many developed countries are increasingly important drivers of global consumption. The number of people in this age group will grow by more than one-third, from 164 million today to 222 million in 2030. We estimate that they will generate 51 percent of urban consumption growth in developed countries, or $4.4 trillion, in the period to 2030. That is 19 percent of global consumption growth. The 75-plus age group’s urban consumption is projected to grow at a compound annual rate of 4.5 percent between 2015 and 2030. In addition to increasing in number, individuals in this group are consuming more, on average, than younger consumers are, mostly because of rising public- and private-healthcare expenditure.
With low fertility in the developed world, migration has become the primary driver of worldwide population and labor-force growth in key developed regions. Since 2000, growth in the total number of migrants in developed countries has averaged 3.0 percent annually, far outstripping the 0.6 percent annual population growth in these nations. Besides contributing to output today, immigrants provide a needed demographic boost to the current and future labor force in destination countries. Improving the old-age-dependency ratio is of critical importance to countries like Canada, Germany, Spain, and the United Kingdom, where worsening dependency ratios threaten to make many pay-as-you-go plans unsustainable.
The gulf between those embracing change and those falling behind is growing
Disparity is growing among countries, sectors, companies, and individuals, contributing to increasing political and social discontent, with unpredictable results that have added to the disruption.
‘Superstar’ effects: Disproportionately large gains for top performers and correspondingly heavy losses for those falling behind
We analyzed nearly 6,000 of the world’s largest public and private companies with annual revenues of at least $1 billion; together, they make up 65 percent of global corporate pretax earnings. “Superstars” constitute the top 10 percent of companies and capture 80 percent of the economic profit. Superstar companies come from all sectors of the global economy, and their diversity has increased over the past 20 years. Among them are US and Chinese tech companies that didn’t exist 20 years ago (including Alibaba, Alphabet, Facebook, and Tencent) as well as global brands that have been around for decades (such as Coca-Cola and Nestlé) but also Chinese banks, French luxury companies, and German automakers. US companies still make up the largest share of the leaders, accounting for 38 percent, compared with 45 percent in the 1990s. Companies from China, India, Japan, and South Korea have made the biggest gains and now account for 22 percent of the total, up from 7 percent.
These top-decile companies capture 1.6 times more economic profit today compared with 20 years ago, with larger revenues and higher profit margins than in the past. By contrast, the bottom decile destroys more value than the top 10 percent creates (Exhibit 4). The economic losses of this bottom 10 percent of companies are 1.5 times larger on average than those of their counterparts 20 years ago.
The skew is greater still when looking at the top 1 percent. The world’s 58 largest economic-value-creating companies account for 6 percent of all economic profit. They have 20 times more sales, four times more profit (based on net income margin), and five times more R&D investment than do median companies with annual sales above $1 billion.
Superstars are not entrenched incumbents. Since the early 1990s, almost half of the entire cohort of superstar companies in one business cycle has been knocked out of the top decile by the next business cycle. The fall can be steep: about two in five of the erstwhile highfliers dropped from the top decile to the bottom decile. This often occurs because the size of the invested capital base amplifies any decline in the returns to capital relative to the cost of capital. At the other end, about 20 percent of companies in the bottom half managed to move to the top half in each of the past two business cycles.3
Technology adoption is uneven across sectors, companies, and countries
Digitization has widened the gap between early adopters and others within sectors and among companies. Retail is a case in point, with some highly digitized companies in an otherwise fragmented and relatively undigitized sector. In most countries, a few sectors are relatively more highly digitized—for example, financial services, media, and the tech sector itself.
With the advent of AI, we find that sectors highly ranked in MGI’s Industry Digitization Index are also leading AI adopters and have the most ambitious AI-investment plans. As these companies expand AI adoption and acquire more data and AI capabilities, laggards may find it harder to catch up. In our surveys of companies, about half say they have embedded at least one AI capability into their standard business practices, and another 30 percent are piloting use of AI. For now, however, only about 20 percent of companies say they have embedded AI in several parts of the business. AI spending remains a small fraction of overall digital spending, and many organizations still lack the foundational practices to create value from AI at scale.
For now, China and the United States are responsible for the most AI-related research activities and investment. A second group of countries that includes Canada, Germany, Japan, and the United Kingdom has a history of driving innovation on a major scale and may accelerate the commercialization of AI solutions. Smaller, globally connected economies, such as Belgium, Singapore, South Korea, and Sweden, also score highly on their ability to foster productive environments where novel business models thrive. Countries in a third group, including but not limited to Brazil, India, Italy, and Malaysia, are in a relatively weaker starting position, but they exhibit comparative strengths in specific areas on which they may be able to build. India, for instance, produces around 1.7 million graduates a year with science, technology, engineering, and mathematics degrees—more than the total of STEM graduates produced by all G-7 countries. Other countries with relatively underdeveloped digital infrastructure, innovation and investment capacity, and digital skills risk falling behind their peers.
Automation and AI adoption will bring occupational and skill shifts
We developed scenarios for the impact of automation on the workforce based on the pace and extent of adoption. Under a midpoint scenario, about 15 percent of the global workforce, or the equivalent of about 400 million workers, could be displaced by automation in the period of 2016 to 2030. At the same time, 550 million to 890 million new jobs could be created from productivity gains, innovation, and catalysts of new labor demand, including rising incomes in emerging economies and increased investment in infrastructure, real estate, energy, and technology.
This suggests that the growth in demand for work, barring extreme scenarios, would more than offset the number of jobs lost to automation. No less significant are the jobs that will change as machines increasingly complement human labor in the workplace. Our research has found that about 30 percent of the activities in 60 percent of all occupations could be automated by adapting currently demonstrated technologies—but that in only about 5 percent of occupations are nearly all activities automatable. In other words, more occupations are likely to be automated partially than wholly.
We see four key transitions from automation and AI adoption. First, millions of workers will likely need to change occupations. Some of these shifts will happen within companies and sectors, but many will occur across sectors and even geographies. While occupations requiring physical activities in highly structured environments and in data processing will decline, others that are difficult to automate will grow.
Second, workers will need different skills to thrive in the workplace of the future. Demand for social and emotional skills, such as communication and empathy, will grow almost as fast as does demand for many advanced technological skills. Demand for basic digital skills has been increasing in all jobs. Automation will also spur growth in the need for higher-level cognitive skills, particularly critical thinking, creativity, and complex information processing. Demand for physical and manual skills will decline, but these will remain the single largest category of workforce skills in 2030 in many countries (Exhibit 5).
Third, workplaces and work flows will change as more people work alongside machines. This will be challenging both to individual workers, who will need to be retrained, and to companies, which must become more adaptable.
Finally, automation will likely put pressure on average wages in advanced economies. Many middle-wage jobs in advanced economies are dominated by highly automatable activities in fields such as manufacturing and accounting, which are likely to decline. High-wage jobs, especially for high-skill medical and tech or other professionals, will grow significantly. However, many of the jobs expected to be created, such as teachers and nursing aides, typically have lower wage structures. The wage pressure is likely to be lower in emerging economies, where relatively low wages for many workers make the business case for adoption less compelling.
Increasingly unequal societies are polarizing, and the social contract is perceived to be broken
Despite growth in incomes and wealth across economies, variability and inequality in outcomes have also risen, and in some advanced economies, a portion of the population perceives the social contract as broken. This has helped fuel growing political and social tensions, which have been manifested in various ways, including the rise of antiestablishment parties promising to break the mold in some countries, Britain’s 2016 vote to leave the European Union, and recent protests by yellow-vest-wearing gilets jaunes in France. Our research found that in 2005 to 2014, real market incomes were flat or fell for between 65 and 70 percent of households in advanced economies. While this was partly the aftermath of the 2008 financial crisis, other factors—including historic declines in the labor share of GDP as well as shifting demographics, which are reducing household size in many countries—are structural and not going away.
Stretching the period to 2017, in the labor market, we see increasing real income per capita but little change in average income inequality. In the capital market, we see an increase in real wealth per adult and lower old-age poverty but greater wealth inequality, an increase in the number of heavily indebted households, and lower net pension-replacement rates.
Environmental stress is increasing, with implications for the most vulnerable countries, industries, and people
Increasing levels of economic activity at a global scale are having impact, both positive and negative, on the environment. Rising levels of carbon emissions from energy production and use are linked to increasing risks to endangered environments and higher levels of environmental stress. At the same time, breakthroughs in AI, batteries, and renewables are enabling a more carbon-efficient growth path.
Download Navigating a world of disruption, the briefing note on which this article is based (PDF–271KB).
Migration flows linked to the environment are on the rise. The number of refugees and asylum seekers rose by 2.5 million between 2005 and 2010, then jumped by 8.1 million between 2010 and 2015. In the future, climate change and other environmental stresses may drive more people from their homes.
Higher requirements for sustainability in industry are forcing companies to rethink how they design and deliver products, services, and projects to increase focus on waste reduction and abatement of carbon emissions. By 2030, for example, the share of electrified vehicles could reach as much as 50 percent of new-vehicle sales in some places, with adoption rates highest in developed, dense cities with strict emission regulations and consumer incentives.
Moving toward a more inclusive society
Rekindling inclusive growth so that more people will benefit from future economic growth and global flows will be an imperative. As thought starters for further discussion, we sketch out what a more sustainable society might look like.
Adopt a pro-growth mind-set and a business–public sector agenda that leads to rapid and sustained GDP per capita growth
All economies—both advanced and developing—can learn from the pro-growth agendas across both the public and private sectors put in place by outperforming emerging economies. These include steps to boost capital accumulation through industrial policies and savings, deeper connections to the global economy, creation of the impetus for competition, and building of greater competence, agility, and openness to regulatory experimentation in governments themselves.
Capture the net positive economic impact of AI and automation
The largest economic impacts of AI will likely be through labor-market effects, including labor substitution, augmentation, and contributions to labor productivity. AI will also create positive externalities, facilitating more efficient cross-border commerce and enabling expanded use of valuable cross-border data flows. Inclusive application of technology can raise GDP and bring real benefits in traditional areas, such as agriculture, healthcare, and transportation.
Address the labor-market implications of technology adoption, including through large-scale retraining and transitioning of workers
Workers will need to acquire new skills and be more adaptable as they work ever more closely with evolving machines. Some companies—such as Walmart, SAP, AT&T,4 and emerging market companies including Tata, Infosys, and Tech Mahindra—are adopting broad reskilling initiatives, but a much larger societal push is needed to revamp education to make it relevant for the workplace of tomorrow, as well as to provide midcareer workers with new skills. A new emphasis is needed on creativity, critical and systems thinking, and adaptive learning.
Address societal concerns on AI and automation
Along with the widening economic gaps that might emerge as an unintended consequence of AI deployment, business leaders and governments will need to address other areas of concern, including misuse of AI and data privacy.
Pave the way for a rise in independent work
About 20 to 30 percent of the working-age population in the European Union and the United States is engaged in independent work. While only about 15 percent of independent work is conducted on digital platforms now, that proportion is growing rapidly as people use these platforms to learn, find work, showcase their talent, and build personal networks. Policy makers and business leaders can do more to facilitate new work opportunities and to accelerate changing orthodoxies of work.
Increase gender parity for a potential boost to growth for most economies
Our research on gender equality has found that a “full potential” scenario, in which women participate in the economy identically to men, would add as much as $28 trillion, or 26 percent, to annual global GDP in 2025 compared with a business-as-usual scenario. This impact is roughly equivalent to the size of the combined Chinese and US economies today. An alternative “best in region” scenario, in which all countries match the rate of improvement of the best-performing country in their region, would add as much as $12 trillion in annual GDP in 2025, equivalent in size to the current GDP of Germany, Japan, and the United Kingdom combined (Exhibit 6).
Remaining challenges include notably low labor participation in high quality jobs, weak senior representation in the pipeline, high financial and digital exclusion, entrenched social attitudes about women’s roles, and pervasive problems of violence against women and girls.
Integrate migrants effectively to realize a positive impact on global productivity and reduce economic and social gaps
Workers moving to higher-productivity settings contributed roughly $6.7 trillion, or 9.4 percent, to global GDP in 2015—some $3 trillion more than they would have produced in their origin countries. North America captured up to $2.5 trillion of this output, while up to $2.3 trillion went to Western Europe. Narrowing the wage gap between immigrant and native workers to 5 to 10 percent, from 20 to 30 percent, through better economic, social, and civic integration would translate into an additional $800 billion to $1 trillion in global annual output.
Each of the disruptive forces we highlighted would be challenging on its own; taken together, they can seem daunting. Yet the opportunities for the economy, business, and society that these global forces generate are equally compelling and are already creating new prosperity for those quick to harness them. Embracing the trends while mitigating their negative impact on those who cannot keep up and on our environment is the new imperative of our era.