The Economic Impact of Self‑Learning Artificial Intelligence
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This study examines the transformative impact of self-learning artificial intelligence (AI) on the global economy, characterizing it as a shift comparable to the Industrial Revolution. Unlike traditional software, self-learning AI’s ability to adapt and make autonomous decisions has fundamentally altered productivity, decision-making, and operational efficiency across sectors such as finance, manufacturing, and retail. Through a qualitative and analytical methodology—utilizing industry reports, case studies, and comparative sectoral analysis—the research evaluates the dual nature of AI integration. The findings indicate that while AI significantly drives innovation, reduces operational costs, and creates high-value roles in data science and engineering, it simultaneously presents critical socio- economic challenges. These include the displacement of routine labor, increased market concentration among data-rich firms, and potential systemic risks in financial markets. The study concludes that while self-learning AI is an essential driver for future economic growth, its benefits must be balanced through proactive policymaking, workforce re-skilling, and regulatory frameworks to mitigate inequality and ensure sustainable economic development.
Keywords
Economic Transformation, Labor Market Dynamics, Productivity, Self-Learning Artificial Intelligence