Digital Content Quality and Market Dynamics in the Era of Artificial Intelligence: An Economic Framework for Understanding Information Ecosystems

Abstract

The rapid advancement of artificial intelligence—particularly large language models—has fundamentally transformed the economics of digital content creation. This transformation introduces profound challenges for preserving information quality, sustaining market efficiency, and safeguarding social welfare. Unlike traditional economic theories that focus on information asymmetries, today’s digital landscape is characterized by the mass production of apparently credible yet low-quality content at minimal cost, while generating high-quality, verified content remains resource-intensive. This paper presents a comprehensive economic framework to analyze how AI-induced cost differentials reshape digital information markets, create novel market failures, and demand innovative governance responses. Using both theoretical models and empirical evidence, we demonstrate that current market dynamics contribute to a systemic erosion of content quality. We introduce a multidimensional index to assess ecosystem health and propose adaptable policy frameworks suited to rapid technological change. Our findings deepen the understanding of technological disruption in information markets and inform the design of evidence-based policy solutions for the digital economy.