How AI Can Help Developing Economies Achieve Faster Growth

A research has identified and analyzed potential areas which can give a country comparative advantage and expansion in economic activities.

The findings indicate that developing economies can leverage Artificial Intelligence (AI) to achieve a faster and more sustainable growth.

This has led to countries worldwide racing to harness AI to make their industries more competitive and helping to diversify economies.

Artificial intelligence (AI) is often likened to electricity due to its potential to revolutionize various aspects of our lives.

AI technology spans a wide array of applications from detecting early signs of cancer and predicting virus mutations to creating art, managing investment portfolios, and even assisting in content creation like this blog.

The increasing number of AI applications is reshaping traditional notions of human employment.

Given its transformative potential, countries worldwide are actively seeking to leverage AI to enhance their industrial competitiveness in global markets and uncover new areas of comparative advantage.

This pursuit is particularly crucial for developing economies, which typically rely on exports to fuel economic growth but may be overly reliant on a limited range of products or commodities.

Diversification emerges as a key strategy for these economies, offering a pathway to new sources of growth and bolstering resilience against unforeseen disruptions, akin to how a diversified investment portfolio offers greater stability compared to relying on a single security.

A new paper, titled: AI Specialization for Pathways of Economic Diversification, co-written with Robert Koopman, Giuditta de Prato, Keith Streir, Julie Kim, and Nikola Spatafora, provides a possible answer.

The paper presents quantitative evidence of the linkages between different forms of AI and a country’s comparative advantage. According to them, AI can uncover new areas of a country’s economic comparative advantage.

In the paper, the authors utilized an economic concept known as the product space to analyze potential areas for a country’s comparative advantage and expansion in economic activities.

They developed a novel database comprising private investments in AI categorized into 29 sectors, including autonomous vehicles, agri-tech, robotics, and gaming/e-sports.

The researchers assessed each country’s specialization in AI and established a network linking the network analysis revealed that different AI technologies exhibit varying degrees of association with specific sectors.

For example, robot automation is closely linked with machinery manufacturing, metal products, chemicals, and boilers, while image recognition and visual search are advantageous for industries such as food processing and ecommerce.

Thus, the study ranked sectors with growth potential for each country, considering specialization in AI, goods, and services.

The findings suggest strategies for both developed and developing nations to capitalize on AI specialization and diversify their sources of comparative advantage.

For instance, the research proposes that Mexico could enhance its metal product fabrication through investments in robot automation, while investing in FinTech related to booking and payment systems could maintain its competitive edge in travel services.

Similarly, for India, investing in AI agricultural technology could boost farmers’ productivity.

With the increasing demand for AI-based services and advancements in communication technology, many AI solutions can now be produced in one location and operated elsewhere.

For instance, KUKA Robotics, a German firm, deploys its AI-integrated industrial robots across various countries and industries such as automotive, aerospace, and electronics manufacturing.

The study suggests that AI solutions could be integrated into every stage of the production process, from research and development to distribution, repair, and recycling, potentially shaping the future wealth of nations through participation in global value chains.

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