Executive Summary

U.S. military strength has long depended on the ability to fight alongside allies and partners. From the Gulf War to Operation Epic Fury, coalition operations have amplified American power, but they have also exposed persistent friction: incompatible networks, conflicting classification rules, national caveats tracked in “enormous spreadsheets,” and language barriers that, at their worst, have contributed to near-fatal incidents in the field. The hope animating this paper is that AI-enabled decision support systems (AI-DSS)—software platforms that ingest, analyze, visualize, and share vast and disparate data—can help coalitions operate more effectively together. We find cause for that hope, but as with past technical evolutions, political will and bureaucratic change remain critical hurdles.

This paper examines four specific applications of AI-DSS for allied and partner operations: building a common operating picture (COP), supporting coalition targeting decisions, accelerating the foreign disclosure information-sharing process, and bridging language differences. In each case, AI-DSS offer real advantages in managing complex disclosure guidance, centralizing information, enabling real-time translation, and building a shared operational picture more quickly and reliably. We use the Maven Smart System (MSS), now deployed broadly across U.S. commands and in some cases already providing these services, as an exemplar throughout.^*

Tempering the hope that AI-DSS can improve coalition operations are the same technical and political constraints that have confounded prior interoperability efforts. These include political restrictions on information sharing, varying technical and cybersecurity standards, and trust deficits in coalition partners and in the technology itself.

Added to these historical hurdles are newer concerns. Allies and partners are facing political backlash over deals with U.S. technology vendors, ranging from AI-DSS developers like Palantir, the prime contractor for MSS, to generative AI companies. Concerns over the reliability of U.S. commercial partners are exacerbated by recent U.S. government actions against the AI company Anthropic. When paired with increased uncertainty over America’s support for allies and partners, nations are publicly seeking “sovereign AI” capabilities that may complicate future allied operations.

Despite these challenges, NATO’s adoption of AI-DSS has moved with unusual speed. As one example, security accreditation that can take 18 months on U.S. networks took only six months to reach initial security accreditation and one year to reach full approval in the case of NATO Maven. NATO is in a uniquely strong position to embrace AI-DSS today, with several factors we explore in this paper appearing to accelerate adoption.

Based on this research, we offer four recommendations to U.S. and international policymakers:

• Build and calibrate confidence in AI-DSS through demonstrations, exercises, and transparency. Uncertainty about AI-DSS can be partly addressed through direct exposure and experience. Exercises like the XVIII Airborne Corps’ Scarlet Dragon and NATO Task Force Maven’s outreach offer replicable models. Candid discussion of AI advantages and incidents will further calibrate allied confidence and demystify the technology for the public.
• Presume AI sovereignty and prepare for “haves and have-nots.” The sovereign AI impulse reflects durable political and economic interests that are unlikely to dissipate. CDAO should define technical and policy standards that willing partners can adopt to facilitate AI-DSS integration and interoperability.
• Invest in data, data sharing, and data governance. The AI-DSS opportunity is wasted without data. This means elevating allied data generation; establishing common cybersecurity certificates and data sharing agreements (such as common data use agreements or AUKUS-like ITAR exemptions); and accelerating investment in cross-domain solutions for the efficient transfer of information to coalition networks.
• Invest in NATO Maven. NATO has the infrastructure, policy frameworks, and political will that are preconditions for coalition AI-DSS success. CDAO should treat Task Force Maven as both an operational asset and a learning laboratory, and use those lessons to accelerate adoption with critical Pacific partners, with AUKUS Pillar II as a potential coordination forum.

Supporting AI-DSS adoption across allies is mutually beneficial, improving partner capabilities, spurring cutting-edge AI development, and building durable security. Our recommendations are meant to close the gap between the potential advantages and our current reality.

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^*MSS is a U.S. Department of War system; the prime contractor is Palantir.