From individual use to collective intelligence: Evolution of collaboration strategies measured by AI
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The rapid adoption of artificial intelligence (AI) is transforming work from individual uses focused on productivity toward collaborative configurations, although uncertainty remains regarding when such interaction can be considered collective intelligence. This study aimed to analyze the evolution of collaboration strategies from individual AI use to human-AI configurations, considering interaction, coordination, complementarity, and performance. A qualitative, documentary, non-experimental, deductive, and exploratory study was conducted through the analysis of literature published between 2021 and 2026 and the coding of five analytical dimensions with supervised AI support. The results identified four configurations: individual assistance, iterative human-AI interaction, hybrid systems, and AI integration into teams; human-AI combinations outperformed humans working alone (g = 0.64), but not the best available agent (g = −0.23), while AI-supported teams achieved improvements of approximately 10.2% compared with individuals working without AI. The findings showed that enhanced productivity and collective synergy are not equivalent, as performance depended on task type, role distribution, and complementarity. It was concluded that collective intelligence emerges from specific collaborative configurations and requires assessing coordination, knowledge integration, diversity, and joint performance rather than AI adoption alone.
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