THE AI BUBBLE: BETWEEN TECHNOLOGICAL PROMISES AND ECONOMIC REALITY

This study examines the phenomenon of the artificial intelligence (AI) bubble through an integrated economic and technological lens, contextualizing the recent surge in AI development—particularly generative models like ChatGPT and Midjourney—within broader cycles of financial speculation and innovation hype. Drawing on classical economic theories of bubbles (Kindleberger, Minsky, Shiller) and contemporary reports from institutions such as the OECD, World Economic Forum, and McKinsey, the research examines whether current investment patterns and market valuations in the AI sector reflect sustainable growth or speculative excess. The study highlights parallels with previous episodes of technological overvaluation, such as the dotcom and cryptocurrency bubbles, and identifies behavioral and structural indicators of potential market distortion. While acknowledging the transformative potential of AI, the study argues that inflated expectations may obscure underlying risks, particularly for emerging economies vulnerable to global financial shocks. It concludes that the AI bubble, if managed prudently, could serve as a corrective phase that redirects innovation toward long-term sustainability. Policy recommendations include diversifying funding sources, safeguarding labor markets, strengthening regulatory frameworks, and investing in human capital to ensure a responsible and inclusive transition toward humane artificial intelligence.