Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Adoption of Artificial Intelligence in Defence Industry Supply Chain: Exploring Barriers and Opportunities for AI Adoption
Karlstad University.
Karlstad University.
2026 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

 Escalating global tensions have contributed to geopolitical instability and increased demands in the defence industry. This has resulted in a shift away from the cost centric focus in the early 2000s towards a current need for resource efficiency and industrial scaling. The increase in capacity requirements has significant implications for supply chain operations, thereby creating a need for accelerated processes and technological advancement, including AI. However, AI adoption within the defence industry presents a paradox due to the high security centered environment in which organizations operate. Consequently, a clear strategic vision and suitable organizational preconditions become critical factors for successful AI implementation and use. Despite the growing scientific interest in AI, its adoption within defence industry supply chains for operational efficiency remains limited.

This study partly bridges that gap by exploring AI adoption within the defence industry supply chain through a qualitative single case study in collaboration with BAE Systems Bofors. To address this gap, the study investigated Which barriers could occur when adopting AI in the defence industry supply chain? and Could AI be leveraged in the defence industry supply chain when exploring opportunities for operational development?. Therefore aiming to identify emerging barriers, risks and opportunities associated with the implementation and use of AI.  

The findings uncover several internal barriers for AI adoption at BAE, creating tensions and risks for the implementation and use with respect to cultural and security considerations. Additionally, alternatives for AI opportunities were identified and discussed in relation to compatibility and possible utilization for BAE. All together, highlighting a two step approach for AI adoption and the necessity to balance data availability with AI model complexity for risk mitigation, suggesting a pilot project for social sustainability and long term value creation.

Place, publisher, year, edition, pages
2026. , p. 55
Keywords [en]
Digital transformation, Artificial intelligence, Defence industry, Supply chain, Barriers, Organizational conditions, Ramp up
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kau:diva-111640OAI: oai:DiVA.org:kau-111640DiVA, id: diva2:2084460
External cooperation
BAE Systems Bofors
Educational program
Master of Science in Industrial Engineering and Management, 300 ECTS credits
Supervisors
Examiners
Available from: 2026-08-13 Created: 2026-07-05 Last updated: 2026-08-13Bibliographically approved

Open Access in DiVA

fulltext(1138 kB)1 downloads
File information
File name FULLTEXT01.pdfFile size 1138 kBChecksum SHA-512
797c51eda421d8aacfab982cebc1e7237f83b34a8d734a25d29f3d849f6d6b70b4dd48a028f8035fddf9fad89f8fd5f5b8a45b9c569d6f8a08d79b0c46c8e344
Type fulltextMimetype application/pdf

By organisation
Karlstad University
Other Engineering and Technologies

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 11 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf