Keynesianism in the Age of Platform Capitalism and AI

ABSTRACT: The rapid adoption of artificial intelligence (AI) and platform capitalism is reshaping economic structures, labor markets, and wealth distribution. This paper examines the continued relevance of Keynesianism in addressing the economic disruptions caused by AI-driven automation and the dominance of digital platforms such as Google, Meta, and Amazon. While Keynesian economic theory has historically provided policy frameworks for full employment and economic stability, the emergence of jobless productivity growth, wealth concentration in digital monopolies, and algorithmic control over demand challenges the effectiveness of traditional Keynesian interventions. Through a combination of theoretical analysis and empirical case studies, this study evaluates how Keynesian policies—such as fiscal stimulus, public investment, and progressive taxation—must evolve to remain effective in an AI-driven economy. The findings suggest that while Keynesianism remains a valuable tool for mitigating economic instability, it requires adaptations, including the taxation of digital monopolies, universal basic income (UBI) trials, AI-driven workforce reskilling, and stronger antitrust regulations. Furthermore, the paper explores alternative and complementary economic models, including post-Keynesianism, welfare economics, and innovation-led growth strategies, to address labor market disruptions and rising inequality. The study concludes that Keynesianism can still serve as a foundation for economic policy but must be reimagined to regulate platform capitalism, redistribute AI-generated wealth, and ensure broad-based prosperity in the 21st-century economy.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-23
DOI
https://doi.org/10.5281/zenodo.18030929
Primary Topic
Digital Economy and Work Transformation
Type
article
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article

Keynesianism in the Age of Platform Capitalism and AI

Fernando C. Gaspar
Zenodo (CERN European Organization for Nuclear Research)
Digital Economy and Work Transformation
article

Keynesianism in the Age of Platform Capitalism and AI

Fernando C. Gaspar
article en

Abstract

ABSTRACT: The rapid adoption of artificial intelligence (AI) and platform capitalism is reshaping economic structures, labor markets, and wealth distribution. This paper examines the continued relevance of Keynesianism in addressing the economic disruptions caused by AI-driven automation and the dominance of digital platforms such as Google, Meta, and Amazon. While Keynesian economic theory has historically provided policy frameworks for full employment and economic stability, the emergence of jobless productivity growth, wealth concentration in digital monopolies, and algorithmic control over demand challenges the effectiveness of traditional Keynesian interventions. Through a combination of theoretical analysis and empirical case studies, this study evaluates how Keynesian policies—such as fiscal stimulus, public investment, and progressive taxation—must evolve to remain effective in an AI-driven economy. The findings suggest that while Keynesianism remains a valuable tool for mitigating economic instability, it requires adaptations, including the taxation of digital monopolies, universal basic income (UBI) trials, AI-driven workforce reskilling, and stronger antitrust regulations. Furthermore, the paper explores alternative and complementary economic models, including post-Keynesianism, welfare economics, and innovation-led growth strategies, to address labor market disruptions and rising inequality. The study concludes that Keynesianism can still serve as a foundation for economic policy but must be reimagined to regulate platform capitalism, redistribute AI-generated wealth, and ensure broad-based prosperity in the 21st-century economy.

Zenodo (CERN European Organization for Nuclear Research)
Instituto Superior de Ciências da Administração (PT)
Decent work and economic growth
Openalex Percentile: Top 24%
Digital Economy and Work Transformation
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