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AI's Impact On World Economy

Updated: Oct 21, 2019

| AI + T |

Artificial intelligence (AI) has the potential to incrementally add 16 percent or around $13 trillion by 2030 to current global economic output; an annual average contribution to productivity growth of about 1.2 percent between now and 2030, according to a September, 2018 report by the McKinsey Global Institute on the impact of AI on the world economy.

“If delivered, this impact would compare well with that of other general-purpose technologies through history,” suggests McKinsey. “Consider, for instance, that the introduction of steam engines during the 1800s boosted labor productivity by an estimated 0.3 percent a year, the impact from robots during the 1990s around 0.4 percent, and the spread of IT during the 2000s 0.6 percent.”

The McKinsey report is based on simulation models of the impact of AI at the country, sector, company and worker levels. It looked at their adoption of five broad categories of AI technologies: computer vision; natural language; virtual assistants, robotic process automation, and advanced machine learning. Data sources included survey data from approximately 3,000 firms in 14 different sectors and economic data from several organizations including the United Nations, the World Bank and the World Economic Forum.

In conjunction with a recent report by PwC, which found that AI technologies and applications will increase global GDP by up to 14% between now and 2030, the McKinsey report offers more evidence that AI is poised to deliver big economic opportunities for those companies and workers best positioned. Below is a summary of the report’s key findings:

Several factors will significantly impact such AI-driven economic changes.

AI could lead to a gross GDP growth of around 26 percent or $22 trillion by 2030. The major contributors to this figure are the automation of labor, which could add up to 11 percent or around $9 trillion to global GDP by 2030, and innovations in products and services, which could increase GDP by about 7 percent or around $6 trillion by 2030.

However, in addition to its economic benefits, AI will also lead to significant disruptions for workers, companies and economies. There will likely be considerable costs associated with managing labor-market transitions, especially for workers being left behind by AI technologies, which could reduce the gross impact of AI by around 10 percentage points, leading to the net GDP increase of 16 percent or $13 trillion by 2030.

Economic impact may emerge gradually and be visible only over time

McKinsey’s models showed that AI marketplace adoption will likely follow a typical S curve pattern with a slow start in the early stages, followed by a steep acceleration as the technology matures and firms learn how to best deploy it, then tapering off in the technology’s late stages. In the case of AI, the contributions to growth are likely to be 3 to 5 times higher by 2030 and beyond than between now and 2023.

At the ‘AI and the Future of Work’ conference held November 2017, MIT professor Erik Brynjolfsson explained that such S-curve deployment patterns are typical of transformative, general purpose technologies like the steam engine, electricity and computing. Their deployment time-lags are longer because attaining their full benefits requires several complementary co-inventions and investments, including additional technologies, applications, processes, business models, and regulatory policies. Over time, AI likely will become such a historical trandformative technology. But other than a relatively small number of leading-edge firms, we’re still in the early stages of AI’s deployment. It’s only been in the last few years that complementary innovations like machine learning have taken AI from the lab to early adopters in the marketplace. Considerable innovations and investments are required for its wider deployment in robotics, self-driving cars, truly intelligent personal assistants, and advanced applications like smart health care.

AI adoption could widen gaps between countries, companies, and workers.

Best positioned, of course are China and the US, the two countries currently responsible for most AI-related activities. Developed economies, such as those in Germany Japan and Canada, and smaller globally economies like Sweden, Singapore and Finland are well positioned to capture the benefits of AI, as well as highly motivated to do so due to their slow productivity growth. Economies with moderate foundations like India, Italy, and Malaysia may lag the leaders, but they have strengths in specific areas around which they may be able to build their AI capabilities. But developing economies, which have relatively underdeveloped foundations in investment capacity, digital infrastructure and talent risk falling further behind.

Adoption rates among firms generally fall into three main categories:

Front-runners. Early adopters, comprising about 10 percent of companies, will benefit disproportionately by embracing a broad set of AI technologies and applications over the next 5 to 7 years. As a result, a set of winner-take-all firms may well capture the bulk of the profit pool in their respective industries.

Followers. This group, comprising 20 to 30 percent of firms, are slowly, cautiously embracing AI, having seen the benefits enjoyed by front-runners as well as the competitive threats of falling behind.

Laggards. This final group, comprising 60 to 70 percent of firms, are not seriously investing in AI, if at all. Capability issues may prevent such companies from embracing AI, forcing them to respond by reducing costs and cutting investments.

In addition, AI will lead to large shifts in the demand for skills, potentially widening the gaps between workers. The report estimates that “up to 375 million workers, or 14 percent of the global workforce, may need to change occupations - and virtually all workers may need to adapt to work alongside machines in new ways.” While some workers are at risk of being replaced by machines, there could be a shortage of workers whose value is greatly amplified by working alongside machines. “Overall, the picture that emerges is one of rising wage and employment opportunity inequality… groups with superior skill sets may capture a disproportionate share of gains.”

“The economic impact of AI is likely to be large, comparing well with other general-purpose technologies in history,” notes the report in conclusion. “At the same time, there is a risk that a widening AI divide could open between those who move quickly to embrace these technologies and those who do not adopt them, and between workers who have the skills that match demand in the AI era and those who don’t. The benefits of AI are likely to be distributed unequally, and if the development and deployment of these technologies are not handled effectively, inequality could deepen, fueling conflict within societies.”

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