Entangled by Design: A structured Overview of Management Challenges concerning AI Adoption in Organizations

Artificial Intelligence (AI) adoption poses complex, multidimensional challenges for organizations that extend beyond technical implementation. While strategic interest in AI is rising, many initiatives struggle to scale sustainably. This paper addresses the fragmented state of AI adoption research by offering a theory-driven synthesis of the key management challenges organizations face. Based on a systematic literature review and grounded in the socio-technical systems (STS) perspective, the study identifies challenges across technological, organizational, and social domains - such as data governance, organizational inertia, skill shortages, and ethical ambiguity - as mutually reinforcing. The resulting framework highlights the systemic entanglement of these barriers, underscoring the limits of isolated interventions. This study contributes to Information Systems (IS) research by conceptualizing AI adoption as a socio-technical transformation and providing an integrative typology of adoption challenges. The findings offer a foundation for future empirical research and guide strategic decision-makers in navigating the organizational complexity of AI integration.

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Publication Details

Journal
Annals of Computer Science and Information Systems
Published
2025-10-15
DOI
https://doi.org/10.15439/2025f1129
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Entangled by Design: A structured Overview of Management Challenges concerning AI Adoption in Organizations

Niculin Prinz, T.B. Klos, Constanze Riedinger, Melanie Huber et al.
Annals of Computer Science and Information Systems
Big Data and Business Intelligence
article

Entangled by Design: A structured Overview of Management Challenges concerning AI Adoption in Organizations

Niculin Prinz, T.B. Klos, Constanze Riedinger, Melanie Huber, Christopher Rentrop, Alessandra Zarcone
article en

Abstract

Artificial Intelligence (AI) adoption poses complex, multidimensional challenges for organizations that extend beyond technical implementation. While strategic interest in AI is rising, many initiatives struggle to scale sustainably. This paper addresses the fragmented state of AI adoption research by offering a theory-driven synthesis of the key management challenges organizations face. Based on a systematic literature review and grounded in the socio-technical systems (STS) perspective, the study identifies challenges across technological, organizational, and social domains - such as data governance, organizational inertia, skill shortages, and ethical ambiguity - as mutually reinforcing. The resulting framework highlights the systemic entanglement of these barriers, underscoring the limits of isolated interventions. This study contributes to Information Systems (IS) research by conceptualizing AI adoption as a socio-technical transformation and providing an integrative typology of adoption challenges. The findings offer a foundation for future empirical research and guide strategic decision-makers in navigating the organizational complexity of AI integration.

Annals of Computer Science and Information SystemsVol. 43
Technische Hochschule Augsburg (DE), Betrieb für InformationsTechnologie (DE), HTWG Hochschule Konstanz - Technik, Wirtschaft und Gestaltung (DE)
Openalex Percentile: Top 32%
Big Data and Business Intelligence
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