Artificial intelligence (AI) has emerged as a general-purpose technology at the heart of the Fourth Industrial Revolution (4IR), with the potential to transform production, innovation, and global competition. Micro-level field experiments and firm studies consistently show sizable productivity gains from AI tools in tasks such as customer support and software development, often with the largest benefits accruing to less-experienced workers. Yet, at the macro level, productivity acceleration has been uneven and lagged, reflecting diffusion frictions, complementary-capital gaps, skills shortages, and measurement issues. This paper synthesizes the latest empirical evidence and policy analyses to: (1) map the channels through which AI raises productivity (task automation/augmentation, product and process innovation, and improved decision quality); (2) examine why firm-level gains have not yet fully translated into broad-based productivity growth; and (3) discuss industrial-competitiveness implications for advanced and emerging economies, including manufacturing reconfiguration, data-center and semiconductor races, and the evolving policy landscape in the EU and globally. The paper concludes with a policy playbook—skills, diffusion support for SMEs, trustworthy AI governance, competition and data-sharing rules, and mission-oriented investments—to translate AI’s promise into inclusive productivity growth and resilient industrial advantage.
Bibi et al. (Sun,) studied this question.
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