Generative AI in Business Analytics: Opportunities and Risks for National Economic Growth

Abstract

Generative Artificial Intelligence (AI) is a pioneering development in Business Analytics, redefining the role of generating insights by organizations and optimizing their decision-making and maintaining growth in the digital transformation age.This study explores how Generative Artificial Intelligence (AI) can offer a transformative change in Business Analytics and the implications such changes have on the economic development of a country and what opportunities and threats are presented by the introduction of AI into the economic processes. This study compares the impact of generative AI-based analytics on macroeconomic outcomes, financial inclusion, and sustainable development in five leading economies in the world, namely, the United States, China, India, Japan, and Germany, using the data provided by the World Bank, World Development Indicators (WDI), the Economic Policy and Debt and Financial Sector datasets. As a quantitative research method, data was processed and analyzed in Python, Tableau, and Microsoft Excel, which made it possible to approach the data statistically, comparatively, and visually. The GDP growth, adjusted net national income, education expenditure, and ownership of financial accounts constituted key indicators which were analyzed to investigate the influence of digital transformation, human capital and technological readiness on the national productivity and innovation. The findings indicate that the AI readiness correlates positively with financial inclusion and economic performance at a strong level. The more democratic economies with a larger amount of digital infrastructure, investment in education, and utilization of AI, like China and India, demonstrate better economic stability and growth inclusiveness. On the other hand, mature AI-based economic trends of developed countries are stable but oriented towards efficiency and sustainability and not on high growth. This study also lists the challenges such as data inequality, job displacement due to automation and lack of ethical governance. These results underline the importance of the idea that as much as generative AI can become the driver of innovation and development, it also requires a set of strategic policies that would reduce the risk of socio-economic and ethical consequences. Finally, the paper finds that Generative AI in Business Analytics is both a governance issue and a revolutionary opportunity to the global economies. Effective regulation of how countries strike the right balance between AI innovation, human capital development, and digital transformation to include everyone in growth and transformation will determine sustainable economic progress.