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Artificial Intelligence to Give Global Economy $13T Shot in Arm: McKinsey

By Rob Preston

September 24th, 2018

Artificial intelligence could inject an additional $13 trillion into the global economy by 2030, amounting to 1.2 percent additional growth in gross domestic product per year, according to a new report by McKinsey Global Institute.

A number of factors, including AI-based productivity improvements and innovations, will contribute to this economic stimulus, according to the report, which nonetheless warns that AI adoption could widen the digital divide among countries, companies and workers.

In its economic models, McKinsey assessed the impact of five AI technologies: computer vision/image recognition, natural language processing, virtual assistants/chatbots, robotic process automation and advanced machine learning. By 2030, McKinsey’s average simulation shows, some 70 percent of companies “might” have adopted at least one type of AI technology but less than half will have fully absorbed all five.

The most cautious companies will take an “opportunistic approach,” the report states, piloting AI only for a specific function or two, like automating certain sales activities or helping recruiters identify the best job candidates. The boldest companies will absorb all five AI technologies, across their entire organizations, and the biggest winners will be those that start now.

The McKinsey report predicts that AI’s contribution to global economic growth might be at least three times higher by 2030 than it will be over the next five years, due to the substantial upfront learning and deployment costs. However, “it would be a misjudgment to interpret this ‘slow burn’ pattern of impact as proof that the effect of AI will be limited,” the report states. “The size of benefits for those who move early into these technologies will build up in later years at the expense of firms with limited or no adoption.”

Supporting Research

McKinsey’s economic thesis jibes with one advanced by Dr. Michael Mandel, senior fellow at the Wharton School’s Mack Institute of Innovation Management, who argues in a recent report that U.S. GDP alone could grow by an additional $2 trillion cumulatively during the next decade just from the “diffusion” of advanced technologies and industry best practices made possible by widespread business adoption of cloud services.

As cloud software and platform services make not only AI, but also blockchain, predictive analytics, autonomous systems and the Internet of Things (IoT), readily available to small and big companies alike, they will drive “a new wave of productivity that will accelerate growth and living standards in the United States and worldwide,” according to Mandel’s research, commissioned by the Technology CEO Council.

Both the Mandel and McKinsey reports are also consistent with the recent findings of researchers at German-based Berenberg Bank, which maintain that companies worldwide are still adjusting to stage one of the latest three-stage economic “super-cycle”—the “discovery” stage—in which entrepreneurs struggle to turn AI, IoT and other major tech innovations into economic and societal gains. The Berenberg researchers argue, however, that the global economy is starting to move into the “dispersion” stage, a period of robust productivity and output growth, as “people figure out how to utilize the new technologies cheaply and implement them widely. As old technologies are replaced at a rapid pace, progress improves.”

Widening Gap?

Despite the optimistic tone of the McKinsey report, it raises the concern that developed economies are likely to increase their lead over developing economies by adopting AI more quickly and thoroughly.

The report makes the case that policymakers in developed countries will have no choice but to push AI to boost productivity growth, partly to compensate for their aging populations and thinning workforces. In contrast, most of the industries in developing countries are still catching up in their implementation of less advanced technologies and business practices.

Among individual companies, AI “front-runners” could potentially double their cash flows by 2030, while non-adopters might experience a 20 percent decline, the McKinsey report says. It notes that front-runners “tend to have a strong starting IT base, a higher propensity to invest in AI, and positive views of the business case for AI.”

Not noted in the McKinsey report, however, is the fact that cloud computing itself could close the gap between the AI haves and have-nots. Subscription cloud services embedded with AI and other advanced technologies won’t require the specialist IT staffs and deep capital investments of earlier technologies, letting even the smallest, most tech-challenged companies take advantage of the latest breakthroughs.

Job Boom or Bust?

A more common concern is that AI-powered automation will threaten millions of jobs, just as earlier forms of automation eliminated certain assembly line, customer-service and other jobs in previous generations.

“Job profiles characterized by repetitive activities or that require a low level of digital skills could experience the largest decline as a share of total employment, to around 30 percent by 2030, from some 40 percent,” the McKinsey report posits. “The largest gain in share could be in non-repetitive activities and those that require high digital skills, rising from roughly 40 percent to more than 50 percent.”

Overall, however, the “adoption” and “absorption” of artificial intelligence will likely have only a minor impact on net employment, the report concludes, as AI-powered IT systems and business processes put a premium on higher-skilled workers. As with the introduction of any powerful new technology, there will be some disruption.

“Policymakers will need to show bold leadership to overcome understandable discomfort among citizens about the perceived threat to their jobs as automation takes hold,” the report states. “Companies will also be important actors in searching for solutions [to] the mammoth task of skilling and reskilling people to work with AI.”

Rob Preston is editorial director in Oracle’s Content Central organization.
