An Approach for Enterprise Architects to Analyse Opportunities and Constraints for Applying Artificial Intelligence in Military Transformations

Juha Mattila*, Simon Parkinson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Military Forces are seeking strategic advantages promised by the latest advances in Artificial Intelligence (AI) trained with data collected from networked military things. In some countries like USA, Russia and China, the quest to develop advantages with AI has become the next arms race. Most visibly, the race is on in autonomous systems, but there are further ambitions behind what has been published. Enterprise Architecture (EA) practitioners are being asked where and how to implement AI for the best military benefits. Firstly, the answers would be naturally based on the availability of data, the computer performance and stability of processes and environment. Secondly, the answers may be sought within an organisation's cultural features, its ability to adopt new technology, create explicit knowledge, and flexibility when facing unexpected. The existing EA frameworks provide tools to answer the first questions but, unfortunately, do not include models to analyse the evolutionary or revolutionary paths for the development of military capabilities. EA practitioners are facing questions like: What is the readiness of military enterprise to benefit from features of AI? How fast does a military organisation adopt the opportunities offered by AI? Which AI features may be the best to start the transformation? This paper introduces an enhanced EA tool that improves the success of EA practitioner in assessing opportunities and challenges of military enterprises applying AI in their transformations. We approach the challenge from pragmatic view using design research methodology to define the problem, find a tool for a solution, demonstrate it in a case study and evaluate results. The proposed Tool helps the EA practitioner in modelling the full stack of an enterprise from culture down to technology. Secondly, it helps EA practitioner to recognise opportunities for using the features of AI. Thirdly, the Tool illuminates the interrelated evolutionary forces between the structural layers and reveal possible challenges in transformation. Consequently, the EA practitioner can provide advice to military decision makers in implementing features of AI, avoiding the typical pitfalls of practice.

Original languageEnglish
Title of host publicationProceedings of the European Conference on the Impact of Artificial Intelligence and Robotics ECIAIR 2019
EditorsP Griffiths, MN Kabir
PublisherACADEMIC CONFERENCES INTERNATIONAL
Pages215-224
Number of pages10
ISBN (Electronic)978-1-912764-44-0
ISBN (Print)978-1-912764-45-7
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in a conference publication
EventEuropean Conference on the Impact of Artificial Intelligence and Robotics - Oxford, United Kingdom
Duration: 31 Oct 20191 Nov 2019

Conference

ConferenceEuropean Conference on the Impact of Artificial Intelligence and Robotics
Abbreviated titleECIAIR
CountryUnited Kingdom
CityOxford
Period31/10/201901/11/2019

Keywords

  • Enterprise architecture
  • Artificial intelligence
  • Military transformation
  • Evolution of system of systems
  • Adaptive architecture
  • Evolutionary theory

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