How much will AI/robotics/machine learning disrupt emerging and developing economies over the next decade? In our opinion, that is the single hardest question when it comes to emerging/frontier market investing just now. Very often, the discussion around technological disruption centers on what it means for Boston or Berlin. But what about Bangkok or Buenos Aires or Bamako?
The key issues: how many workers will need to retrain as technology makes their current jobs redundant, and do these economies have the bandwidth to make this happen? It is a very different calculus depending on whether we’re talking about developed or emerging economies:
- In the US, Western Europe and Japan, technology disrupts the existing labor force by replacing them with new capital. At the same time, these countries have older populations so there is some balance as retiring workers make way for younger (and generally more educated/tech savvy) ones.
- Emerging/developing economies may have it harder.[su_spacer]
First, their traditional export-driven path to economic success will be more difficult if automation moves production/services back to developed economies. Think apparel manufacturing or AI-powered voice recognition customer service here.
Second, most of these countries have younger workforces and limited educational systems. Adapting to global tech-enabled disruption could be hard and mass youth unemployment is typically a recipe for political instability.
We found three useful research pieces on the topic if you want to explore it more deeply. Here they are, with some brief summaries:
#1. A widely cited McKinsey study from late 2017 correlates country-specific labor force disruption between now and 2030 with GDP levels (good news for emerging economies, sort of…). For most developed economies, they estimate that 20-25% of their workforces will be displaced by technological disruption.
Some prominent emerging countries still face challenges, however. McKinsey puts Chinese workforce disruption by 2030 at 15-16%, which sounds OK until you realize that is 120 million people. Or 75% of the US workforce, just to give you a comparison point. The numbers for India are 9%, or 47 million people. Retraining this many workers will be a key challenge for both countries and we’re only talking about a dozen years or fewer before these changes occur.
#2. “Reshoring” – moving production back to developed economies – is one key underappreciated benefit for the US/Europe/Japan but could hit emerging economies especially hard. A UN Conference on Trade and Development paper highlighted this challenge by examining the number of industrial robots in China/Korea/Japan and Germany/North America and compared that to rest of world. The outsized leader here is China with double the capacity of North America. But outside China/Japan/North America/Europe, there are very few industrial robots at all.
UNCTAD’s policy recommendations for developing economies are direct: quickly improve education to embrace new technologies, invest in “massive data storage” to power the increased use of robots locally, and focus on small-scale manufacturing. None of which looks like the old model of developing economy growth, to say the least.
Source (click on link in the webpage to see the full report): http://unctad.org/en/pages/PublicationWebflyer.aspx?publicationid=1647
#3. A 2016 World Bank report called “Digital Dividends” is even more cautious on the role technology plays around the world. Developing economies have lower digital adoption rates for people, businesses and governments. Global productivity growth continues to decline. More than half the world remains unconnected to the Internet.
Unfortunately, their recommendations work better in developed economies than emerging ones. They call for more regulation (which requires a strong legal system), improved skills (good public schooling and universities) and accountable institutions.
Whole report here: http://www.worldbank.org/en/publication/wdr2016