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To determine the impact of artificial intelligence (AI) on the selected economies in the Asia-Pacific region. Methods: This secondary research collected data from macroeconomic and AI-specific data sets. The sources of data from which insights were gained included digital technology sectors and corporations and their functions. The focus was on the need to assess the capability of AI on business operations The macroeconomic data was collected from data resources of international organizations' including the World Economic Forum, the Organization for Economic Cooperation and Development (OECD), the World Intellectual Property Organization (WIPO), and the International Telecommunication Union (ITU). In addition, this study has considered 19 economic indicators to analyze the economic outcome of AI in selected economies of Asia-Pacific. Results: From the results, the period between 2014 and 2016 witnessed China leading with over 25,000 citable documents on the AI topic. Regarding institutions that were observed to publish over 500 times on the AI topic, the countries in the ascending order include China (600), Hong Kong (1,100), and Singapore (2,000). As such, this study established that Asia-Pacific economies such as Hong Kong and Singapore though have smaller populations, but the majority of their higher education institutions have made a significant contribution to AI research; with the small economies also having a relatively higher number of computer scientists among the top 1,000 individuals. Additionally, through empirically analyses, during 1998-2016 with annual observations, it is found that various economic outcomes of AI were presented in 8 economies of targeted region. Limitations: At first, the future outlook of AI is just discussed in conceptual meaning while empirical context still needs to be examined in upcoming studies. At second, covering the overall South Asian region provides better findings with more generalization which is missing in current research. At third, other dimensions of AI and economy like implication of AI impact index and its relationship with macroeconomic variables is also missing in current research which could be reconsidered in coming studies. Conclusion: It is evident that AI exhibits the potential to be the main driver of Asia-Pacific's economic growth. Relative to the net and gross effect of AI on labor markets and the gross domestic product (GDP) of the top Asia-Pacific economies demonstrate that by 2030, AI might yield a 16-percent increase in output, translating into an estimated amount of $13 trillion. Overall, it is concluded that Asia-Pacific, when compared to developed regions such as North America, is lagging but the availability of a large pool of user data implies that the region can move ahead-given better resource and talent allocation.

This research article investigates the impact of democracy on peak turning point of the environmental Kuznets curve in the context of the Association of South East Asian Nations (ASEAN) countries that have different levels of development and democracy. For this purpose, time-series data for the period of 1980-2014 have been employed. The empirical findings support the existence of the environmental Kuznets curve for CO 2 emission in the ASEAN countries. It is also found that democracy measured by civil liberties delays the turning point of the environmental Kuznets curve and, therefore, increases the environmental cost of economic growth. The research output provides meaningful inputs to formulate an effective public policy for the protection of the environment in the ASEAN countries.

This research article examines the impact of economic, health, environmental, and social-economic factors on diverse forms of pro-environmental consumption: energy conservation, water conservation, and recycling. Primary data concerning these variables were collected from 430 individuals using a structured questionnaire following the cluster sampling methodology. Results indicate that one unit increase in environmental, economic, and health concerns improve pro-environment behavior by 52, 64, and 25 units, respectively. In contrast, a 1 unit increase in income deteriorates pro-environment behavior by 0.01 units. Education, age, gender, and owning a home have an insignificant impact on pro-environmental habits. The model explains a 52% variation in pro-environmental habits. The study recommends that effective electronic and social media campaigns increase environmental, economic, and health concerns and improve green behavior. More courses on environmental sustainability in schools and universities can effectively increase ecological knowledge and concerns.