Economy and empirical research perspectives towards Artificial Intelligence: A deep dive investigative exploration analysis

Zarif Bin Akhtar

Department of Computing, Institute of Electrical and Electronics Engineers, USA.

https://orcid.org/0009-0004-5498-6458

Ahmed Tajbiul Rawol

Department of Computer Science, Faculty of Science and Technology, American International University-Bangladesh.

DOI: https://doi.org/10.20448/economy.v11i1.6270

Keywords: Artificial intelligence, Economic growth, Economic models, Economic paradigms, Economics science, Economy, Empirical research perspectives.


Abstract

The transformative potential of Artificial Intelligence (AI) has sparked significant interest across economic and empirical research domains, inspiring investigations into its impacts on productivity, labor markets, economic growth, and policy adaptation. This study offers a comprehensive analysis of AI's economic implications, focusing on its integration into diverse sectors and its measurable effects on economic performance. Through a multi-dimensional approach, we explore AI’s role in enhancing productivity and efficiency, reshaping workforce dynamics, and influencing the distribution of economic benefits. Supported by recent empirical studies and quantitative analyses, this research highlights AI’s capacity to drive innovation while examining its challenges, such as labor displacement, income inequality, and skill gaps. Case studies and data-driven insights provide evidence of AI’s role in fostering new economic models, underscoring its dual potential to stimulate growth and exacerbate disparities. Furthermore, the study delves into the evolving landscape of policy responses, analyzing how different regulatory frameworks influence AI’s integration and impact across economies. By offering nuanced perspectives on AI’s transformative effects, this investigation identifies key trends and areas requiring further research, including the long-term implications for developing economies and global inequality. The findings aim to equip policymakers, researchers, and industry leaders with evidence-based insights to navigate AI’s complexities, ensuring sustainable and inclusive economic advancement in an AI-driven future.

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