Easy to read, easier to write: the politics of AI in consultancy trade research

AI systems have been rapidly implemented in all sectors, of all sizes and in every country. In this article, we conduct a bibliometric review of references in recent consultancy reports on AI use in business, policymaking, and strategic management. The uptake of these reports is high. We find three positive factors: focus on client-facing solutions, speed of production, and ease of access. We find that the evidentiary quality of reports is often unsatisfactory because of references-clubbing with other consultancy reports, references to surveys without transparency, or poor or missing references. To optimize the utility of consultancy reports for decision-makers and their pertinence for policy, we present recommendations for the quality assessment of consultancy reporting on AI’s use in organizations. We discuss how to improve general knowledge of AI use in business and policymaking, through effective collaborations between consultants and management scientists. In addition to being of interest to managers and consultants, this work may also be of interest to media, political scientists, and business-school communitie

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Publication Details

Journal
Cogent Social Sciences
Published
2025-03-04
DOI
https://doi.org/10.1080/23311886.2025.2470368
Citations
1
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
4.20
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article

Easy to read, easier to write: the politics of AI in consultancy trade research

Branislav Radeljić, Theresa Mackenzie, Olivia Heslinga
1 citations
Cogent Social Sciences
Digital Economy and Work Transformation
4.20
article

Easy to read, easier to write: the politics of AI in consultancy trade research

Branislav Radeljić, Theresa Mackenzie, Olivia Heslinga
article en
1 citations

Abstract

AI systems have been rapidly implemented in all sectors, of all sizes and in every country. In this article, we conduct a bibliometric review of references in recent consultancy reports on AI use in business, policymaking, and strategic management. The uptake of these reports is high. We find three positive factors: focus on client-facing solutions, speed of production, and ease of access. We find that the evidentiary quality of reports is often unsatisfactory because of references-clubbing with other consultancy reports, references to surveys without transparency, or poor or missing references. To optimize the utility of consultancy reports for decision-makers and their pertinence for policy, we present recommendations for the quality assessment of consultancy reporting on AI’s use in organizations. We discuss how to improve general knowledge of AI use in business and policymaking, through effective collaborations between consultants and management scientists. In addition to being of interest to managers and consultants, this work may also be of interest to media, political scientists, and business-school communitie

Cogent Social SciencesVol. 11(1)
Universidad Nebrija (ES), University of Belgrade (RS)
Reduced inequalities
Openalex Percentile: Top 9%
Digital Economy and Work Transformation
4.20
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