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Productivity: the question we are not asking
Publication: ECO
Author: Conteúdo Patrocinado
Source published: 15/10/2026, 15:00:00 UTC
Briefing created: 25/10/2026, 10:39:06 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 15/10/2026, 16:41:25 UTC.
Briefings
The article argues that productivity is not a universal metric but depends on organizational goals, leading to a disconnect between AI's ability to automate tasks and actual organizational productivity gains. It highlights the OECD definition of productivity as output divided by input, noting that AI gains at the individual task level often fail to translate to organizational efficiency due to context-specific factors like workflow organization and decision-making capacity. The text emphasizes that without a clear understanding of organizational purpose, technology cannot solve the productivity problem.
Key points
- The OECD defines productivity as the relationship between output volume and resource consumption, serving as a standard metric for measuring efficiency.
- AI can increase productivity at the individual task level but does not guarantee organizational productivity gains due to contextual factors like workflow organization and decision-making capacity.
Context
The article discusses the widespread use of productivity as a daily vocabulary and a universal challenge, often paired with AI promises. It contrasts the simple measurement of output in manufacturing with the complex measurement of value in knowledge-based organizations, highlighting the OECD's definition as a standard but noting the lack of a single interpretation within organizations.
Limitations
The evidence is limited to the OECD's definition of productivity and the article's analysis of AI's impact on task-level versus organizational productivity. The source does not provide specific data on AI adoption rates, organizational productivity metrics, or causal links between AI implementation and productivity outcomes.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 25/10/2026, 10:39:06 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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