TRANSFORMATIVE IMPACTS OF AI ON DIGITAL MEDIA: AN ANALYSIS OF INDUSTRY-SPECIFIC TRENDS, ECONOMIC OUTCOMES, AND CONSUMER TRUST (2020-2025)

Abstract

The rapid evolution of artificial intelligence (AI) is reshaping the digital media landscape, prompting critical inquiries into its industry-specific impacts and implications for economic outcomes and consumer trust. This study presents a comprehensive analysis of AI adoption trends from 2020 to 2025, leveraging a mixed-methods approach that incorporates a Kaggle-sourced dataset with 1,240 industry-year observations.Our findings indicate substantial disparities in AI adoption rates, with the U.S. automotive sector leading at 81.06, while South Korean healthcare remains at a mere 10.53. High-adoption sectors experience remarkable revenue growth of 45.6–57.86, despite concurrent job losses ranging from 10.66 to 27.62. Employing sophisticated regression analyses, we identify infrastructure investment as a significant predictor of AI adoption (0.58, p < 0.01), contrasting with the detrimental effects of regulatory strictness (0.34, p < 0.05).A novel contribution of this research is the exploration of consumer trust dynamics, which inversely correlates with AI adoption rates (-0.12). This study reveals that trust levels vary significantly across sectors, with marketing achieving a trust rate of 81.58% compared to only 41.77 in gaming, largely driven by transparency tool adoption.In conclusion, we propose an innovative policy framework that aims to align AI-driven growth with ethical considerations, emphasizing the role of transparency and sector-specific governance. Our research enriches the understanding of technology adoption models and offers actionable insights for policymakers and industry leaders, facilitating sustainable innovation in the digital media sector. This study not only fills critical gaps in existing literature but also sets the stage for future research on the intersection of AI and digital media.