Measurement of Organizational AI Exposure:

Latifa Borni; Fella Achour; Liamine Falta

doi:10.2991/978-94-6239-711-8_28

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Measurement of Organizational AI Exposure:

An AI-Assisted Comparative Approach in the Algerian Insurance Industry

Authors

Latifa Borni¹, Fella Achour²^{, *}, Liamine Falta³

¹Department of Management, University Mohammed Khider, Biskra, Algeria

²Department of Economics, University Mohammed Khider, Biskra, Algeria

³Department of Management, University Mohammed Khider, Biskra, Algeria

^*Corresponding author. Email: fella.achour@univ-biskra.dz

Corresponding Author

Fella Achour

Available Online 24 June 2026.

DOI: 10.2991/978-94-6239-711-8_28 How to use a DOI?
Keywords: Artificial Intelligence Exposure; Insurance; process exposure; administrative exposure; competitive exposure; SAA; Alliance Assurances
Abstract: This study aims to measure and analyze the organizational AI exposure in two different Algerian insurance companies, SAA and Alliance, using a proposed conceptual framework within an AI-assisted comparative case approach to assess AI Exposure through three core dimensions: process, administrative, and competitive exposure. The results from the strategic matrix show that Alliance is positioned within a controlled exposure configuration due to its high internal capabilities (83.65%) and low external pressure (46.6%), reflecting a voluntary and active adoption. In contrast, SAA is positioned at the boundary between defensive exposure and total exposure, characterized by moderate internal exposure (60.4%), high competitive pressure (73.2%), and limited administrative exposure (53%). This study suggests reinforcing digital sovereignty, prioritizing skills upgrading, and adopting flexible administrative models before making extensive investments in artificial intelligence.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Artificial Intelligence Applications in Business Administration in MENA Region (ICAIABA 2026)
Series: Advances in Economics, Business and Management Research
Publication Date: 24 June 2026
ISBN: 978-94-6239-711-8
ISSN: 2352-5428
DOI: 10.2991/978-94-6239-711-8_28 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Latifa Borni
AU  - Fella Achour
AU  - Liamine Falta
PY  - 2026
DA  - 2026/06/24
TI  - Measurement of Organizational AI Exposure:
BT  - Proceedings of the International Conference on Artificial Intelligence Applications in Business Administration in MENA Region (ICAIABA 2026)
PB  - Atlantis Press
SP  - 299
EP  - 310
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-711-8_28
DO  - 10.2991/978-94-6239-711-8_28
ID  - Borni2026
ER  -

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