Hybrid Upper Echelons: A Theorizing Review on AI in Executive Decision-Making
Type
conference paper
Date Issued
2026
Author(s)
Abstract
Artificial intelligence (AI) increasingly participates in strategic decision-making, challenging leadership theories that assume human agency at the top of organizations. Yet research on AI-enabled decision-making and upper echelons theory (UET) has largely evolved in parallel. We conduct a concept-centric literature review integrating management and information systems (IS) research to examine how AI affects executive decision-making. Our analysis identifies three mechanisms through which AI reconfigures UET: cognition reconfiguration through the mediation of information and attention, evaluation reconfiguration through the partial substitution of human judgment with algorithmic decision logic, and discretion reconfiguration through the delegation and embedding of decision authority. AI expands analytical capacity while introducing new constraints, shapes how alternatives are evaluated, and redistributes managerial discretion. We introduce the concept of hybrid upper echelons to explain how human and algorithmic actors jointly influence strategic outcomes, showing that executive influence increasingly shifts from making decisions to configuring and governing AI-enabled decision processes.
Language
English (United States)
Keywords
Artificial Intelligence
Upper Echelons Theory
Executive Decision-Making
HSG Classification
contribution to scientific community
Refereed
Yes
Event Title
European Conference on Information Systems
Event Location
Milan, Italy
Subject(s)
Division(s)
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Name
Mehler et al._2026 ECIS.pdf
Size
590.5 KB
Format
Adobe PDF
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