Strategic competition in military AI is intensifying, but governance has not kept pace. As reliance on AI-enabled decision making grows, adversarial attacks that disrupt, deny or manipulate military and critical infrastructure systems could undermine strategic stability. This study examines how such attacks may affect credibility, escalation, trust and attribution, and recommends measures to reduce their likelihood and impact worldwide.
Strategic competition in artificial intelligence (AI), including in the military domain, is intensifying, while global governance has not kept pace. The tactical implications of military AI are well documented: autonomous targeting, navigation in robotic systems, and decision-support tools for commanders are relatively well understood. Growing attention is now directed toward AI’s strategic effects and its influence on strategic stability.
Although research on the strategic implications of AI and governance options is expanding, it largely focuses on the potential benefits of effective AI systems. Little attention has been paid to how the disruption or denial of AI systems could threaten strategic stability. As a result, governance proposals rarely address these risks. Yet as AI is increasingly integrated in decision making and reliance on these systems grows, the consequences of adversarial interference will likewise intensify.
This project, commissioned by the UK Foreign Commonwealth and Development Office (FCDO), offers insights into how adversarial AI attacks targeting AI systems integrated in the military or critical national infrastructure may affect strategic stability, and offers recommendations to decrease the probability and impact of adversarial attacks on AI systems.
Key Takeaways
We analysed five scenarios to illustrate the breadth of implications of Adversarial AI attacks for strategic stability, resulting in the following findings. The comprehensive findings can be found in the report.
- The (perceived) vulnerability of AI systems to adversarial attacks undermines the credibility of defence to adversaries and allies.
- Adversarial AI may tip the offence-defence balance in favour of the offence.
- Ambiguity, distinguishing ‘normal’ AI malfunction due to model fragility and deliberate adversarial attacks, and the difficulty of attribution create opportunities for miscalculation and mistrust. Empowerment of non-state actors through democratisation of technology, and specifically adversarial AI, further complicates attribution.
- Entanglement of conventional and nuclear C3 increases the risk of an accidental attack on NC3, risking escalation.
Document Details
- Copyright: RAND Corporation
- Availability: Web-Only
- Year: 2026
- DOI:https://doi.org/10.7249/RRA4734-2
- Document Number: RR-A4734-2
Citation
Chicago Manual of Style
van Droffelaar, Irene, Kiran Suman-Chauhan, James Black, Thomas Kenchington, Angus Cooper, and William Mitchell Reid, Adversarial artificial intelligence: Implications of strategic stability attacks on military AI systems. Santa Monica, CA: RAND Corporation, 2026. https://www.rand.org/pubs/research_reports/RRA4734-2.html.
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This work was commissioned by the UK Foreign, Commonwealth, and Development Office (FCDO) and conducted by RAND Europe.
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