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Combining Human and Artificial Intelligence: Hybrid Problem-Solving in Organizations

Raisch, Sebastian, Fomina, Kateryna·2025·Academy of Management Review

Abstract

Organizations increasingly use artificial intelligence (AI) to solve previously unexplored problems. While routine tasks can be automated, the intricate nature of exploratory tasks, such as solving new problems, demands a hybrid approach that integrates human intelligence with AI. We argue that the outcomes of this human–AI collaboration are contingent on the processes employed to combine human intelligence and AI. Our model unpacks three hybrid problem-solving processes and their outcomes: Compared to human problem-solving, autonomous search generates more distant solutions, sequential search enables more local solutions, and interactive search promotes more recombinative ones. Collectively, these hybrid problem-solving processes broaden the range of organizational search outcomes. We enrich the behavioral theory of the firm with a technology-conscious perspective of organizational problem-solving that complements its traditional human-centric perspective. Additionally, we contribute to the literature on AI in management by extending its scope from using predictive AI for routine tasks to generative AI applications for more exploratory tasks.

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Cited by

Metadata

Authors
Raisch, S., & Fomina, K.
Venue
Academy of Management Review
Published
2025-04
Volume
50
Issue
2
Pages
441-464
ISSN
  • 0363-7425 (ISSN-L)
  • 1930-3807
OpenAlex
W4390605317
Cited by
280
References
24
FWCI
41.67
Type
journal article
Language
en
Open access
closed

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