Strategic Implications of Deploying Artificial Intelligence in Defence

James Black

ResearchPosted on rand.org May 29, 2026Published in: The Artificial Intelligence Revolution: Challenges and Opportunities, Part III, Chapter 11, pages 299-320 (2026). DOI: 10.1007/978-3-032-11814-1_11

Artificial Intelligence (AI) is rapidly transforming defence and security, with militaries worldwide accelerating their investments in AI and related technologies. This chapter examines the strategic-level implications of AI adoption in defence, moving beyond the typical narrower focus on tactical applications and on ethical debates surrounding Lethal Autonomous Weapons Systems (LAWS) or the controversial use of AI in targeting. This strategic-level analysis is ultimately grounded in a systems-thinking approach, recognising AI as a family of general purpose technologies whose potential to disrupt the military balance of power will be shaped by the interplay of social, organisational, cultural, doctrinal, and technical factors. The chapter explores how military applications of AI could enhance lethality, alter the offence-defence balance, accelerate proliferation, and empower non-state actors, thereby increasing strategic instability if not carefully managed. It further considers the shifting determinants of national and military competitiveness in an age of AI—including governance and regulatory effectiveness, or access to talent, data, and compute—and discusses the risks to international peace and security of an escalating race for advanced AI or Artificial General Intelligence (AGI). The chapter concludes by arguing for an integrated approach that uses both hard and soft power levers to manage global competition and avoid unintended escalation to interstate conflict. Ultimately, responsible AI adoption in defence and efforts to de-risk international competition both in and through AI are essential to ensuring strategic stability in an era of rapid technological change.

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Document Details

  • Publisher: Springer
  • Availability: Non-RAND
  • Year: 2026
  • Pages: 22
  • DOI: https://doi.org/10.7249/pubs
  • Document Number: EP-71351

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