Application of artificial intelligence in the Norwegian Defence Material Agency

FFI-Report 2024
This publication is only available in Norwegian

About the publication

Report number

24/01322

ISBN

978-82-464-3549-7

Format

PDF-document

Size

1.3 MB

Language

Norwegian

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Petter Fredrik Hemnes Sofie Thingsaker
The Norwegian government is investing significantly in defense. This investment will lead to increased workload in the Norwegian Defense Material Agency (NDMA), and NDMA should improve its processes to handle the increased workload. One avenue for improvement is increased use of new technologies such as artificial intelligence. In this report, we propose some uses of artificial intelligence that can be relevant to NDMA. We focus on applications which may involve low investment costs, that can be connected to an area of improvement for NDMA, and that can be tested without significant new gathering of data, infrastructure improvements, and coordination with other government agencies. We group these applications in three areas: 1) information retrieval 2) decision support to resource allocation 3) support to the requirement specification processes We summarize and connect the applications to challenges identified by a recently published analysis of artificial intelligence maturity in the defense sector’s support functions. Our summary shows that NDMA faces challenges both at the organizational level and as an employer. On the other hand, NDMA has already started using artificial intelligence (AI), and further piloting and experimentation with the technology can lead to increased maturity. For NDMA to be better positioned to use AI, we make several recommendations. Besides a few adaptations, these are recommendations that have been made before in an earlier maturity assessment. We recommend that NDMA: 1) operationalize the defense sector’s AI strategy 2) enhance culture and attitudes toward AI 3) centralize competency on AI 4) work to increase knowledge of AI amongst all employees 5) create an AI project portfolio 6) adapt existing acquisition processes 7) increases data collection 8) assess the need for further investments in technological infrastructure

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