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The Impact of AI on Economic Growth: A Take for Emerging Economies

In: Tech Transformation and AI Readiness

Author

Listed:
  • Xiaohua Yang

    (University Canada West)

  • Abeba N. Turi

    (Northeastern University, University Canada West)

Abstract

AI has replaced some workers and is soon to do more. An important question to raise here is how AI impacts an economy. This work is a review of the current literature on the impact of AI on economic growth. The goal is to disclose and delineate the complex literature to identify the common areas of the research reviewed and point out the research gap. The general agreement of the literature reviewed is that AI promotes economic growth. There are three common areas of the current research reviewed. The first one is artificial intelligence and productivity growth. Researchers use different theoretical models to prove that AI increases productivity. Meanwhile, other researchers hold different views on empirical research. Although much empirical research finds that AI promotes productivity growth, the relationship is stable and significant. Some, however, come with opposing views to the extent that developing countries benefit less or face a decline in GDP with AI technology. The second area is artificial intelligence and idea production and innovation, which is mainly theoretical analysis. By introducing an idea production function or knowledge production function, researchers found that AI can aid idea production and promote the overall rate of innovation, thus leading to economic growth. The third area is firm-level analysis. Due to the difficulty of data acquisition on AI applications at the firm’s level, the research is limited. The current finding is that AI can help promote firm productivity and grow larger. Besides, we took use cases from China, India, Brazil, and South Africa as examples of the Global South economies and discussed their AI policies and implications. With the scanty literature focused on the Global South AI, this work draws baseline research with directions for future works to cover the literature gap.

Suggested Citation

Handle: RePEc:spr:fuobcp:978-3-031-73639-1_2
DOI: 10.1007/978-3-031-73639-1_2
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