当代经济科学2026，Vol.48Issue(3)：1-15,15.DOI:10.20069/j.cnki.DJKX.2026039
智能经济的发展历程、内涵特征与基本规律研究
Research on the Evolutionary Path,Connotative Characteristics,and Fundamental Laws of the AI Economy
摘要
Abstract
As a new-generation general-purpose technology,artificial intelligence(AI)is profoundly reshaping the division of labor within global value chains and serves as a key force driving the global economy from the digital age toward the intelligent age.The rapid diffusion of AI technologies is transforming production processes,resource allocation,industrial organization,and international competitiveness,and is emerging as a fundamental driver of long-term economic growth.Against this backdrop,this study seeks to address three interrelated questions:how AI reshapes macroeconomic structures and long-term growth dynamics;through what mechanisms it affects productivity,industrial organization,and factor allocation;and what policy responses are required to ensure inclusive and sustainable development in the intelligent era. Existing studies have primarily focused on either the micro-level impacts of AI on firms,labor markets,and technological innovation or the descriptive characteristics of AI technologies.However,few studies systematically integrate these insights to analyze the AI economy at the macroeconomic level,and there is a lack of frameworks that simultaneously account for technological,economic,institutional,and societal dimensions.This study aims to fill this gap by providing a comprehensive and theoretically grounded analysis of AI's role in shaping economic evolution. Drawing on a dual perspective that integrates the techno-economic paradigm with endogenous economic growth,this paper transcends traditional,narrow analytical frameworks to systematically map the trajectory of artificial intelligence's impact on the macroeconomy.It comprehensively outlines the evolutionary path of the AI economy—from the incubation of technological seeds and the diffusion phase of industrial penetration to the explosive growth phase marked by a surge in total factor productivity—and elucidates the underlying driving mechanisms resulting from the synergistic interplay of technological iteration,factor restructuring,and institutional adaptation.Building on this analytical framework,this paper makes three main contributions.First,it moves beyond a narrow technological determinism and,from a long-run historical perspective,clarifies the internal logic underlying the evolution of the AI economy,identifying its stage-specific characteristics and major developmental trends.Second,it develops a comprehensive analytical framework encompassing technological,economic,institutional,and societal dimensions,thereby establishing the theoretical positioning of AI as a core component of new productive forces.Third,it systematically distills the fundamental patterns governing the AI economy across micro,meso,macro,and international levels,addressing the evolving form of the"Solow paradox"under new technological conditions and revealing how the computing power divide reshapes the global economic landscape. Research findings indicate that the AI economy is not a single technological innovation,but rather exhibits highly complex and synergistic multidimensional characteristics.At the technological level,it is characterized by the integration of data,computing power,and algorithms,as well as exponential innovation spillovers.At the economic level,it exhibits near-zero marginal costs and increasing returns to scale,fundamentally challenging the operational logic of the traditional industrial economy.At the institutional level,it is accelerating the transition toward platform-centric governance,reshaping conventional hierarchical organizational structures.At the societal level,it is evolving toward a new form of human-machine collaboration and symbiosis,redefining the foundations of social division of labor and production-consumption patterns. Building on this foundation,the study further analyzes the underlying mechanisms of the AI economy,including task-skilling substitution and complementarity,rising market concentration driven by the blurring of industrial boundaries,the J-curve pattern of productivity growth,and the dynamic shift in international comparative advantage from traditional factor endowments to computing power endowments.The analysis highlights that the evolution of the AI economy depends not only on technological advancement but also on institutional adaptation and the effective coordination of multiple economic and social factors. Looking ahead,the AI economy faces several structural challenges,including data monopolies,structural unemployment,and growing inequality in wealth distribution.These challenges are particularly reflected in the potential widening of the"AI divide"and the weakening of workers' bargaining power relative to capital.In response,this paper proposes a policy framework to support the sustainable development of the AI economy along four key dimensions:reforming education and lifelong learning systems to foster new forms of human-machine collaboration;deepening the integration of digital technologies with the real economy to promote AI adoption in core industrial sectors;improving institutional arrangements for data as a production factor,including breaking down data silos and enabling inclusive value sharing;and establishing an inclusive and adaptive governance system.关键词
智能经济/人工智能/内生经济增长/产业边界/"数据—算力—算法"融合/平台中心化治理/人机协同/全要素生产率Key words
AI economy/artificial intelligence/endogenous economic growth/industry boundaries/integration of data,computing power,and algorithms/centralized platform governance/human-machine collaboration/total factor productivity引用本文复制引用
徐翔,陈睿..智能经济的发展历程、内涵特征与基本规律研究[J].当代经济科学,2026,48(3):1-15,15.基金项目
国家社会科学基金重大项目(25&ZD093). （25&ZD093）
