The limitations of AI and their implications for the economy
AI limitations
Fecha: mayo 2026
Wolfgang Münchau
SEFO, Spanish and International Economic & Financial Outlook, V. 15 N.º 3 (May 2026)
Assessments of AI’s economic impact are often distorted by a flawed understanding of intelligence — one that conflates pattern recognition with reasoning, and imitation with creativity. AI excels at the former, defining both its power and its limits: it can outperform humans in structured, repetitive cognitive tasks while remaining incapable of original inquiry or genuine creativity. Early productivity data support this distinction. In the United States, a 10 percentage point increase in AI adoption between 2019 and 2025 is associated with a cumulative productivity gain of 2.9 percentage points, meaningful but far from transformative. The more consequential divergence, however, is geographic. In 2026, 43% of U.S. employees used AI compared with 32% in the EU, while adoption gaps within Europe continue to follow familiar divides between Northern and Central Europe on the one hand, and Southern and Eastern Europe on the other, rooted more in management practices than in access to technology. Europe’s combination of strong employment protection, precautionary regulation, and hierarchical corporate cultures is likely to slow the labour reallocation required for AI-driven productivity gains to materialise. The distributional effects also challenge conventional assumptions. Evidence suggests that AI may disproportionately augment lower-educated workers while putting pressure on structured mid-level roles, reversing the pattern observed during earlier technological transitions. AI will destroy some jobs and create others, but countries with more rigid labour markets are likely to absorb the transition more slowly, deferring the productivity dividend rather than avoiding the disruption itself.