Existing literature has highlighted the relevance of collective intelligence in bringing about successful collaboration between Artificial Intelligence (AI) tools and employees, and bringing out results that are valued by the organization. Despite the many benefits offered by AI, such as the automation and optimization of processes, or the augmentation of human intelligence through superior analytical capabilities, the majority of companies still fail to anticipate or exploit these latter benefits. The main difficulty observed in organizations is that of introducing intelligent systems into workers’ practices, production processes and business strategies.
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When time is of the essence and teams face unexpected contextual changes, they must adapt quickly, sometimes even in real time, that is, they may have to improvise. This paper adopts an inductive approach to explore how teams decide to engage in improvised adaptation, and what happens during those processes for improvisation to be successful. The study analyzes improvisation from the perspective of paradox
theory and identifies six paradoxical tensions driven by these contexts: deployment, development, temporal, procedural, structural, and behavioral tensions. We propose a dynamic equilibrium model of team improvised adaptation that leads to team plasticity.
ABRANTES Antonio - TBS Education |
- Recherche
- Management de l'Innovation