This chapter revisits and updates Marc Porat’s seminal 1977 framework for understanding the information economy in the context of today’s rapidly emerging artificial intelligence (AI) economy. As AI technology transitions from speculative innovation to an essential general-purpose driver of economic transformation, the traditional information-centric model requires significant expansion and refinement. Building on Porat’s foundational work, this chapter introduces a three-tier model comprising an AI Core Sector (firms explicitly dedicated to AI development), AI-Integrated Industries (traditional sectors increasingly infused with AI technologies), and the AI-Augmented Workforce (occupations transformed and enhanced through AI). Using the latest market data (2023–2025), it provides robust empirical evidence for AI’s accelerating economic significance, underscoring the projected growth from a market worth under $200 billion to potentially trillions of dollars in the coming decades. Moreover, this chapter critically examines the public policy implications arising from this revised categorization. By explicitly defining and measuring AI as an economic category, policymakers gain enhanced tools for targeted management, regulatory oversight, and fiscal innovation, including the potential implementation of a “robot tax” designed to alleviate disruptive economic transitions and prevent radical disparities in income and wealth concentration. Ultimately, this updated framework aims not only to better conceptualize and quantify the AI economy but also to guide policymakers toward informed strategies that ensure inclusive and equitable growth in the era of artificial intelligence.

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The AI Economy and Public Policy: Updating Porat’s Information Economy Framework in the Era of Artificial Intelligence

  • Michael J. Ahn

摘要

This chapter revisits and updates Marc Porat’s seminal 1977 framework for understanding the information economy in the context of today’s rapidly emerging artificial intelligence (AI) economy. As AI technology transitions from speculative innovation to an essential general-purpose driver of economic transformation, the traditional information-centric model requires significant expansion and refinement. Building on Porat’s foundational work, this chapter introduces a three-tier model comprising an AI Core Sector (firms explicitly dedicated to AI development), AI-Integrated Industries (traditional sectors increasingly infused with AI technologies), and the AI-Augmented Workforce (occupations transformed and enhanced through AI). Using the latest market data (2023–2025), it provides robust empirical evidence for AI’s accelerating economic significance, underscoring the projected growth from a market worth under $200 billion to potentially trillions of dollars in the coming decades. Moreover, this chapter critically examines the public policy implications arising from this revised categorization. By explicitly defining and measuring AI as an economic category, policymakers gain enhanced tools for targeted management, regulatory oversight, and fiscal innovation, including the potential implementation of a “robot tax” designed to alleviate disruptive economic transitions and prevent radical disparities in income and wealth concentration. Ultimately, this updated framework aims not only to better conceptualize and quantify the AI economy but also to guide policymakers toward informed strategies that ensure inclusive and equitable growth in the era of artificial intelligence.