Generative AI and organisational collective intelligence: A dependency-structured framework

Generative AI (GenAI) is now part of everyday organisational knowledge work, affecting how information is gathered, interpreted, argued over, and stored. It should not be treated as a neutral aid: in many settings it can function as an active participant in collective intelligence, shaping what groups notice and how issues are framed and settled. This paper sets out a dependency-structured framework that connects information acquisition, sensemaking and framing, shared reasoning, coordinated action, and organisational memory. The framework is intended as a diagnostic and explanatory lens for organisational analysis, rather than a predictive or causal model. A key implication of the framework is that weaknesses in early stages can propagate upward and distort later decisions, even when outputs appear faster or more coherent. A hypothetical case of a mid-sized financial advisory firm illustrates how GenAI can strengthen performance while risking increased epistemic fragility when foundational processes are compressed or bypassed. The paper ends with diagnostic prompts and governance principles for information professionals, arguing that GenAI tends to amplify existing organisational tendencies rather than reliably augment intelligence.

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Publication Details

Journal
Business Information Review
Published
2026-02-24
DOI
https://doi.org/10.1177/02663821261429686
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Generative AI and organisational collective intelligence: A dependency-structured framework

Preeti Patel, Maitreyee Dey
Business Information Review
Ethics and Social Impacts of AI
article

Generative AI and organisational collective intelligence: A dependency-structured framework

Preeti Patel, Maitreyee Dey
article en

Abstract

Generative AI (GenAI) is now part of everyday organisational knowledge work, affecting how information is gathered, interpreted, argued over, and stored. It should not be treated as a neutral aid: in many settings it can function as an active participant in collective intelligence, shaping what groups notice and how issues are framed and settled. This paper sets out a dependency-structured framework that connects information acquisition, sensemaking and framing, shared reasoning, coordinated action, and organisational memory. The framework is intended as a diagnostic and explanatory lens for organisational analysis, rather than a predictive or causal model. A key implication of the framework is that weaknesses in early stages can propagate upward and distort later decisions, even when outputs appear faster or more coherent. A hypothetical case of a mid-sized financial advisory firm illustrates how GenAI can strengthen performance while risking increased epistemic fragility when foundational processes are compressed or bypassed. The paper ends with diagnostic prompts and governance principles for information professionals, arguing that GenAI tends to amplify existing organisational tendencies rather than reliably augment intelligence.

Business Information ReviewVol. 43(1)
London Metropolitan University (GB)
Openalex Percentile: Top 48%
Ethics and Social Impacts of AI
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