This study examines Korea’s artificial intelligence (AI) policy and current status using the AI Innovation Ecosystem (AIIE) framework. In the proposed AIIE, AI is being developed and utilised through the interactions among various actors with infrastructure, markets, and global linkages. Korea’s AI policy history and ecosystem are characterised by strong government intervention and big firms in the manufacturing and semiconductor industries. Up to now, the Korean government is known to be successful in supporting the development of manufacturing industries. However, there is a question of whether such a past policy type would still be effective when AI affects various industries and society together at high speed. It is analysed that the Korean government and industries are pursuing a manufacturing-based ‘physical AI’ strategy. At the same time, there is not a big change in the labour market yet, as predicted by many experts, but it is obvious that firms prefer more skilled manpower and do not hire as much, especially the entry-level workforce, which can be supported by AI such as accounting and law clerk. The study shows that AI competitiveness of a nation is more dependent on the national AI ecosystem than on individual technologies, and thus the government has to pursue system policies and coordination rather than the development or use of individual technologies. At the same time, the Korean case provides insight into how a middle-power economy navigates AI-driven transformation under conditions of global technology competition and interdependence.
This study assesses the impact of artificial intelligence (AI) on Indian economy. To do so, we first analyse the linkage between AI, employment and economic growth. Second, this study elaborates on the role of AI in shaping India’s Human Development Index (HDI) and compares it with three major economies. Finally, to supplement the analysis, the article makes a quantitative assessment of the effect of AI on economic growth in India. The analysis does not reveal that the displacement effect of AI on employment outweighs the complementary effect in the Indian context so far. However, from the demand side perspective, there might be a reduction in demand for non-AI-related jobs and an increase in AI-related jobs. Further, results show that an increase in AI vibrancy index support better performance of HDI in India in comparison to the China, Germany and the US. Finally, by employing an ARDL model, the results reveal that AI only positively affect the economic growth in the long-run but not in the short run. From a policy perspective, while the Government of India has taken proactive steps for AI-enabled schemes, greater emphasis on appropriate strategies is required to generate more employment through the adoption of AI.
Artificial intelligence (AI) and Industry 4.0 technologies are transforming manufacturing systems globally, with significant implications for labour markets in emerging economies. This article examines how AI adoption reshapes employment structures, skills demand, and training effectiveness in the automotive manufacturing sector in Vietnam. Drawing on the frameworks of skill-biased technological change and routine-biased technological change, the study develops an integrated model linking AI adoption to task reconfiguration, skills mismatch, and employment outcomes. Using labour force statistics, the findings show that AI adoption increases demand for high-skilled and hybrid technical workers while reducing demand for others. However, substantial skills mismatches persist, particularly among domestic firms and small and medium-sized enterprises. Training systems play a critical mediating role, with firms investing in workforce development experiencing better productivity and labour retention outcomes. The article argues that, without coordinated policies linking industrial upgrading, skills development, and social protection, AI-driven transformation may exacerbate inequality.
Generative artificial intelligence (AI) is increasingly viewed as a general-purpose technology with far-reaching labour-market implications. While existing evidence is largely drawn from advanced economies, much less is known about the impact of generative AI on employment in emerging economies. This article examines the labour-market impact of generative AI in T & uuml;rkiye using individual-level administrative records from the Social Security Institution combined with occupation-level exposure measures from the International Labour Organisation. We find that the share of AI-exposed employment within the top 20% of the exposure distribution (fifth quintile) amounts to 17% of total employment. About 2.3 million registered jobs in T & uuml;rkiye are highly exposed to generative AI. Employment effects are strongly age-asymmetric: since 2023, job growth has weakened mainly for early-career workers in highly exposed occupations, while no comparable losses are observed for workers over thirty. These patterns survive controls for sectoral reallocation, suggesting that generative AI operates primarily through hiring margins, displacing inexperienced workers while complementing experienced ones.
