Managing with Artificial Intelligence: An Integrative Framework

Managing with artificial intelligence (AI) refers to humans’ interaction with algorithms performing managerial tasks in organizations. Two literatures exploring this interaction—human-AI collaboration (HAIC) and algorithmic management (AM)—have focused on distinct managerial tasks: while HAIC examines executive decision-making, AM focuses on managerial control. This article presents a review of both literatures to identify opportunities for integration and advancement. We observe that HAIC’s and AM’s micro-level emphases on different managerial tasks have resulted in diverging conceptualizations of context, agency, interaction, and outcome. Adopting a more encompassing systems lens, we unveil previously concealed linkages between HAIC and AM, suggesting that the two literatures have analyzed two sides of the same phenomenon: while HAIC explores how humans use AI to manage, AM describes how humans are managed by AI. We develop an integrative framework that elevates the viewpoint from tasks to the organizational context, from individual to collective agency, from local to systemic interaction, and from micro-level to multilevel outcomes. By employing this framework, we lay the foundations for an organizational perspective on managing with AI.

Authors

Institutions

Publication Details

Journal
Academy of Management Annals
Published
2025-01-01
DOI
https://doi.org/10.5465/annals.2022.0072
Citations
60
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
252.09
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Managing with Artificial Intelligence: An Integrative Framework

Sebastian Raisch, Jonathan Schad, Luis Hillebrand
60 citations
Academy of Management Annals
Digital Economy and Work Transformation
252.09
article

Managing with Artificial Intelligence: An Integrative Framework

Sebastian Raisch, Jonathan Schad, Luis Hillebrand
article en
60 citations

Abstract

Managing with artificial intelligence (AI) refers to humans’ interaction with algorithms performing managerial tasks in organizations. Two literatures exploring this interaction—human-AI collaboration (HAIC) and algorithmic management (AM)—have focused on distinct managerial tasks: while HAIC examines executive decision-making, AM focuses on managerial control. This article presents a review of both literatures to identify opportunities for integration and advancement. We observe that HAIC’s and AM’s micro-level emphases on different managerial tasks have resulted in diverging conceptualizations of context, agency, interaction, and outcome. Adopting a more encompassing systems lens, we unveil previously concealed linkages between HAIC and AM, suggesting that the two literatures have analyzed two sides of the same phenomenon: while HAIC explores how humans use AI to manage, AM describes how humans are managed by AI. We develop an integrative framework that elevates the viewpoint from tasks to the organizational context, from individual to collective agency, from local to systemic interaction, and from micro-level to multilevel outcomes. By employing this framework, we lay the foundations for an organizational perspective on managing with AI.

Academy of Management AnnalsVol. 19(1)
University of Geneva (CH), Vrije Universiteit Amsterdam (NL)
Openalex Percentile: Top 0%
Digital Economy and Work Transformation
252.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.