Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/36643
Author(s): Mamede, Ricardo Paes
Date: Mar-2026
Title: Artificial Intelligence and the economy
Pages: 1-23
Collection title and number: DC_WP_2026_2
Reference: Mamede, R. P. (2026). Artificial Intelligence and the economy (WP No. 2026/02). DINÂMIA'CET-Iscte. 10.15847/dinamiacet-iul.wp.2026.02
DOI (Digital Object Identifier): 10.15847/dinamiacet-iul.wp.2026.02
Keywords: Inteligência artificial -- Artificial intelligence
Prediction technologies
Firm organisation
Inovação -- Innovation
Market structure
Digital platforms
Política industrial -- Industrial policy
Produtividade -- Productivity
Mercado de trabalho -- Labour market
Global value chains
Política da concorrência -- Competition policy
AI governance
Abstract: This paper examines the economic implications of recent advances in artificial intelligence (AI), focusing on the mechanisms through which AI affects firms, markets and macroeconomic outcomes. Building on the view that modern AI primarily reduces the cost of prediction and pattern recognition, the paper analyses how lower prediction costs reshape organisational decisions within firms, including task allocation, business processes, human resource management, strategic decision-making and innovation activities. It then considers how these firm-level transformations influence market structure, highlighting the emergence of a vertically organised AI stack – from semiconductors and cloud infrastructure to foundation models and applications – and the economic forces that may lead to concentration and new forms of market power. The analysis subsequently examines the material and systemic foundations of AI, including semiconductors, energy systems, data centres and critical minerals, and discusses how these inputs interact with geopolitical competition and industrial policy. The paper also reviews the uncertain macroeconomic consequences of AI, assessing its potential effects on productivity, employment and income distribution, while emphasizing the importance of organisational complements, adoption patterns and institutional frameworks in shaping aggregate outcomes. Finally, it explores governance challenges, outlining the roles of competition policy, corporate accountability, industrial strategy and labour market institutions in shaping how AI-driven transformations affect economic efficiency, resilience and equity. The paper concludes by identifying key areas where further empirical research and policy experimentation are needed to better understand and manage the economic transition associated with AI.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:DINÂMIA'CET-WP - Working papers com arbitragem científica

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