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When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Bajramovic, Almir LU and Saleh, Samar LU (2026) BUSN49 20261
Department of Business Administration
Abstract
Abstract

Title: When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Authors: Bajramović, Almir; Saleh, Samar

Submission Date: 27th of May, 2026
Word Count: 21 238
Supervisor: Sverre Spoelstra

Aim: This study explores how managers interpret, evaluate and integrate Generative AI (GenAI) as a source of advice in their day-to-day work. As GenAI becomes more embedded in organizational contexts, the study identifies a need to better understand how managers make sense of AI-generated suggestions in situations characterized by ambiguity, time pressure and uncertainty.

Methodology: In this qualitative study, we adopt an abductive approach within an interpretivist framework. Seven semi-structured... (More)
Abstract

Title: When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Authors: Bajramović, Almir; Saleh, Samar

Submission Date: 27th of May, 2026
Word Count: 21 238
Supervisor: Sverre Spoelstra

Aim: This study explores how managers interpret, evaluate and integrate Generative AI (GenAI) as a source of advice in their day-to-day work. As GenAI becomes more embedded in organizational contexts, the study identifies a need to better understand how managers make sense of AI-generated suggestions in situations characterized by ambiguity, time pressure and uncertainty.

Methodology: In this qualitative study, we adopt an abductive approach within an interpretivist framework. Seven semi-structured interviews were conducted with managers from different organizational contexts who actively used GenAI in their professional work. We have analyzed empirical material through the lens of sensemaking theory, with a specific focus on extracted cues, plausibility, identity construction and social context.

Contributions: Our study demonstrates how AI-generated advice becomes embedded within managerial interpretation and judgment rather than functioning only as external decision support. The study further shows how AI-generated formulation shapes managerial reasoning, influencing how organizational situations are understood before decisions are consciously evaluated. The study therefore contributes to advice-taking and managerial sensemaking literature by arguing that AI-generated formulation itself can function as a form of advice before decisions are consciously evaluated.

Keywords: Generative AI, managerial sensemaking, AI-generated advice, formulation, plausibility, managerial judgment, AI-supported managerial work (Less)
Popular Abstract
Abstract

Title: When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Authors: Bajramović, Almir; Saleh, Samar

Submission Date: 27th of May, 2026
Word Count: 21 238
Supervisor: Sverre Spoelstra

Aim: This study explores how managers interpret, evaluate and integrate Generative AI (GenAI) as a source of advice in their day-to-day work. As GenAI becomes more embedded in organizational contexts, the study identifies a need to better understand how managers make sense of AI-generated suggestions in situations characterized by ambiguity, time pressure and uncertainty.

Methodology: In this qualitative study, we adopt an abductive approach within an interpretivist framework. Seven semi-structured... (More)
Abstract

Title: When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Authors: Bajramović, Almir; Saleh, Samar

Submission Date: 27th of May, 2026
Word Count: 21 238
Supervisor: Sverre Spoelstra

Aim: This study explores how managers interpret, evaluate and integrate Generative AI (GenAI) as a source of advice in their day-to-day work. As GenAI becomes more embedded in organizational contexts, the study identifies a need to better understand how managers make sense of AI-generated suggestions in situations characterized by ambiguity, time pressure and uncertainty.

Methodology: In this qualitative study, we adopt an abductive approach within an interpretivist framework. Seven semi-structured interviews were conducted with managers from different organizational contexts who actively used GenAI in their professional work. We have analyzed empirical material through the lens of sensemaking theory, with a specific focus on extracted cues, plausibility, identity construction and social context.

Contributions: Our study demonstrates how AI-generated advice becomes embedded within managerial interpretation and judgment rather than functioning only as external decision support. The study further shows how AI-generated formulation shapes managerial reasoning, influencing how organizational situations are understood before decisions are consciously evaluated. The study therefore contributes to advice-taking and managerial sensemaking literature by arguing that AI-generated formulation itself can function as a form of advice before decisions are consciously evaluated.

Keywords: Generative AI, managerial sensemaking, AI-generated advice, formulation, plausibility, managerial judgment, AI-supported managerial work (Less)
Please use this url to cite or link to this publication:
author
Bajramovic, Almir LU and Saleh, Samar LU
supervisor
organization
course
BUSN49 20261
year
type
H1 - Master's Degree (One Year)
subject
keywords
Keywords: Generative AI, managerial sensemaking, AI-generated advice, formulation, plausibility, managerial judgment, AI-supported managerial work
language
English
id
9241329
date added to LUP
2026-06-18 16:38:46
date last changed
2026-06-18 16:38:46
@misc{9241329,
  abstract     = {{Abstract

Title: When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work

Authors: Bajramović, Almir; Saleh, Samar

Submission Date: 27th of May, 2026
Word Count: 21 238
Supervisor: Sverre Spoelstra 

Aim: This study explores how managers interpret, evaluate and integrate Generative AI (GenAI) as a source of advice in their day-to-day work. As GenAI becomes more embedded in organizational contexts, the study identifies a need to better understand how managers make sense of AI-generated suggestions in situations characterized by ambiguity, time pressure and uncertainty. 

Methodology: In this qualitative study, we adopt an abductive approach within an interpretivist framework. Seven semi-structured interviews were conducted with managers from different organizational contexts who actively used GenAI in their professional work. We have analyzed empirical material through the lens of sensemaking theory, with a specific focus on extracted cues, plausibility, identity construction and social context.

Contributions: Our study demonstrates how AI-generated advice becomes embedded within managerial interpretation and judgment rather than functioning only as external decision support. The study further shows how AI-generated formulation shapes managerial reasoning, influencing how organizational situations are understood before decisions are consciously evaluated. The study therefore contributes to advice-taking and managerial sensemaking literature by arguing that AI-generated formulation itself can function as a form of advice before decisions are consciously evaluated.

Keywords: Generative AI, managerial sensemaking, AI-generated advice, formulation, plausibility, managerial judgment, AI-supported managerial work}},
  author       = {{Bajramovic, Almir and Saleh, Samar}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{When Generative AI Becomes a Colleague: Managers Making Sense of AI Advice at Work}},
  year         = {{2026}},
}