AI and policy: what makes AI different?

Artificial intelligence (AI) is no longer a speculative or emerging technology but a transformative force affecting firms, workers and economic institutions. Recent studies show its deep integration into economies, highlighting its dual role as a driver of innovation and a source of significant social changes both at the macro and micro levels. In Europe, employment shares in AI-exposed occupations have increased, particularly among younger and more skilled workers, as shown by Albanesi et al. (2025). These changes, however, vary across EU countries, depending on education systems, regulatory frameworks and technology diffusion rates. In the United States, research by Bonfiglioli et al. (2025) reveals a polarizing impact: AI has displaced low-skill and production jobs while creating opportunities for high-wage and STEM-based professions. The impact of AI is also likely to differ significantly across countries at different levels of development or with different economic structures (Cazzaniga et al., 2024). Advanced economies are more vulnerable to and better prepared to capitalize on AI advancements due to their reliance on problem-solving and analytical skills. Meanwhile, emerging markets and developing economies risk falling behind in early productivity benefits due to inadequate infrastructure and human capital. Beyond labor markets, AI technologies, particularly foundation models, reshape production chains and market structures inside and outside the AI industry. Within the industry, Korinek and Vipra (2025) argue that these systems exhibit significant economies of scale and scope, driving market concentration and creating risks of monopolistic behaviour. However, as argued below, AI also disrupts existing markets, providing new transformative technologies. Taking stock of all these effects, Acemoglu (2025) considers the overall contribution of AI on productivity and growth, estimating modest macroeconomic gains from AI-driven productivity improvements, and warns of its potential to exacerbate income disparities, particularly between capital and labour. These findings highlight the urgency for interdisciplinary research and policy action to address AI’s rapid diffusion, its nuanced impacts on labour and markets, and its role in shaping the global economy. With adoption rates outpacing those of previous disruptive technologies, AI’s percolation across industries and geographies demands understanding and proactive governance. In what follows, we provide reasons why AI fundamentally differs of earlier technologies and warrants increased attention. Many of these draw on our own journey in the economics of AI, primarily in competition policy, considering why the tools firms adopt may pose heightened antitrust risks.