• Some media articles suggest that as rich countries automate, developing countries might lose out.
  • However, robots are quickly becoming a part of manufacturing in many developing countries.
  • The World Bank has created a working paper which explores the advantages of incorporating robots into developed and developing countries.
  • It emphasizes the importance of diffusing a range of technologies and not just the most advanced ones, particularly in developing countries.

A rising chorus of media articles highlight how rich countries are rapidly automating and that developing countries may lose out – jeopardizing the future of manufacturing-led development. Yet, robots are in fact rapidly becoming a part of manufacturing in many developing countries. Of course, technology always presents new opportunities as well as challenges. One potential upside of automation is that robots consistently perform tasks to greater precision than human workers, which can reduce production errors and increase product quality. In a recent working paper we examine whether robots lead to export quality upgrading and the potential gains for both developed and developing countries.

Convergence in robot use between developed and developing countries, 2000-2015
Robots can lead to export quality upgrading for both developed and developing countries.
Image: World Bank

The high standards of global value chains

A tide of automation is rippling throughout supply chains, with manufacturing in both rich and poor countries caught in the swell. Robot use in developing countries has increased nearly 10-fold over 2000-2015, outpacing growth in the labor supply. For example, Chinese manufacturing employed less than 1 robot per 1000 workers in 2000, rising to more than 80 by 2015. Robots are not only diffusing fast in China but also in several developing economies: by 2015 Brazil, India and Thailand had more robots than the average rich country. We find that suppliers adopt robots because of pressures from foreign customers that have automated themselves. Automation is now cascading throughout global value chains (GVCs).

While joining global value chains offers the potential of productivity growth and high-wage employment, quality standards can prevent poor countries from participating. Developing country manufacturing can indeed be plagued by poor production quality, therefore, hampering their access to export markets. In our data, developed country exports are on average around 60% higher quality than developing country exports. Foreign customers demand high quality products and these stringent quality standards are passed down supply chains. Firms that cannot meet these standards may miss out.

To err is human - can robots help?

While robots may replace some worker tasks, one potential upside is reducing human errors in production. Robots perform tasks repeatably to the same high-level of accuracy, so are commonly used in the assembly of small electronic components, precision welding of car parts or cutting of metals. Some types of advanced robots are able to operate within extremely accurate tolerances, for instance, those with lasers can cut to within 10 micrometers (0.01 millimeters). We find that automating leads to larger quality gains for initially lower-quality products. Since developing countries tend to produce lower quality goods, poorer countries have bigger quality gains from robot technology.

AI, machine learning, technology

How is the Forum helping governments to responsibly adopt AI technology?

The World Economic Forum’s Centre for the Fourth Industrial Revolution, in partnership with the UK government, has developed guidelines for more ethical and efficient government procurement of artificial intelligence (AI) technology. Governments across Europe, Latin America and the Middle East are piloting these guidelines to improve their AI procurement processes.

Our guidelines not only serve as a handy reference tool for governments looking to adopt AI technology, but also set baseline standards for effective, responsible public procurement and deployment of AI – standards that can be eventually adopted by industries.

Example of a challenge-based procurement process mentioned in the guidelines
Example of a challenge-based procurement process mentioned in the guidelines

We invite organizations that are interested in the future of AI and machine learning to get involved in this initiative. Read more about our impact.

Policy implications

First, technology always creates winners and losers. While automation poses risks to some workers and firms, for others – especially in developing countries – it presents opportunities to upgrade quality, reach new export markets, and create productive employment. Policy should allow such firms to grow, for example by lowering labor market rigidities, which may help to offset any negative effects of declining firms and sectors. Second, our findings warn that growing trade protectionism may slow cross-border technology diffusion. It may constrain the ability of firms in developing countries to upgrade production processes, move into higher value-added activities and produce the high-quality products demanded by consumers. Finally, there is no one-size fits all recipe for policy since different production technologies are appropriate for different firms and countries. We find that not every country adopts the same types of robots. While the diffusion of new technologies is important for improving product quality, policymakers shouldn’t encourage only the most advanced technologies, especially in developing economies.