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THREAT CLIMATE ASSESSMENT: US ACCELERATES INTEGRATION OF PRIVATE AI INTO CLASSIFIED MILITARY NETWORKS. RAPID ADOPTION WILL VERY LIKELY ESCALATE OPERATIONAL AND SECURITY RISKS ACROSS DEFENSE SYSTEMS

  • 1 day ago
  • 7 min read

Updated: 7 hours ago

Giovanni Lamberti, Christian Jackson, Noah Clarke, Sharon Preci, Matthew George, Julia Ruiz Redel, Aristide Devevey, Michela Sereno, Dominic Perfetti; NORTHCOM Team

Ben Joshua Gentemann, Editor; Elena Alice Rossetti, Senior Editor

March 18, 2026

Military Strategy in the Age of AI[1]


The US Department of War (DoW) accelerated the integration of privately developed AI systems into classified military and intelligence networks as part of its strategy to become an “AI-first” warfighting force.[2] Defense agencies awarded contracts to commercial AI companies, including xAI and OpenAI, to support defense-related AI applications across intelligence, logistics, and operational functions.[3] The DoW deployed these systems across multiple classification levels, with AI already supporting intelligence analysis, surveillance, and decision-making processes.[4] Political scrutiny has increased, with policymakers raising concerns regarding transparency, oversight, and security implications of granting private AI systems access to sensitive government data.[5] In the short term, this threat climate will very likely escalate as the pace of AI integration continues to outstrip existing governance and security frameworks, likely increasing exposure to cybersecurity vulnerabilities, misinformation risks, and operational dependency on non-governmental actors. In the long term, sustained reliance on private AI providers will very likely deepen structural dependencies and reduce government control over critical systems, likely increasing vulnerability to disruption, adversarial exploitation, and systemic failures across national security operations.


Introduction

On March 16, 2026, Senator Elizabeth Warren sent a letter to Defense Secretary Pete Hegseth requesting information about the Pentagon’s decision to provide Elon Musk’s xAI access to classified networks.[6] Warren urged transparency from Hegseth to provide details of the agreement with xAI, previous communications the Defense Secretary had in the build-up to an agreement being confirmed, and how xAI's large language model, Grok, will be utilized.[7] She also required further evidence of how xAI has implemented operational safeguarding measures that the General Services Administration (GSA) and National Security Agency (NSA) advised.[8] Concerns were raised after the Pentagon’s focus shifted to maintaining constant operational superiority,[9] and amid fallout with the private AI company Anthropic, which was unwilling to provide its services for mass surveillance and autonomous weapon systems.[10] xAI has agreed to the Pentagon’s “all lawful use standard”[11] and will have access to classified government information to train xAI systems for military operations.[12] The deal has occurred amid a growing political prioritization from the US government to focus on clearing outdated policies and regulations to remove obstacles to the scale of military production.[13] The DoW push to integrate AI into the military comes amidst the geopolitical backdrop of an ongoing effort by other major powers, including Russia[14] and China, to rapidly introduce AI into their own militaries in an effort to gain an advantage in the developing field of AI-supported warfighting.[15] These developments coincide with US government announcements to increase funding for AI innovation[16] and a recent growth in contracts, awarded by the DOW to private AI companies.[17] As the rapid incorporation of private AI companies into classified networks persists, AI systems-linked national security concerns, stemming from recent user data leaks and manipulation, raise data integrity issues.[18]


Analysis

Political

Political decision-making will very likely become increasingly permissive toward the rapid integration of private AI systems into classified military networks. Policymakers will likely prioritize operational advantage and strategic competitiveness over comprehensive regulatory oversight. Reduction in regulatory barriers will likely enable faster authorization to classified data, funding, and deployment of private sector AI capabilities. As political actors continue to support expedited AI-interaction, oversight mechanisms will likely struggle to keep pace and increase gaps in accountability and transparency. This trend will likely increase instability by allowing the expansion of AI-enabled systems that do not comply with previously established government safeguards,  very likely heightening exposure to operational and cybersecurity risks. Political prioritization of speed and competitiveness will very likely continue to drive faster and broader integration of AI systems, at the expense of controlled implementation processes and structured oversight.

 

Geopolitical

Geopolitical competition with China and Russia will very likely act as a primary driver of escalation in the integration of private AI systems into US military and intelligence networks. China’s focus on long-term technological dominance and civil-military use, and Russia’s emphasis on operational AI applications in conflict settings, will likely intensify pressure on the US to accelerate adoption. This dynamic will likely expand reliance on AI across key domains, including intelligence analysis, cyber operations, and logistics. The need to maintain technological superiority will likely create sustained urgency for rapid capability development and deployment, very likely reducing tolerance for delays linked to testing, regulation, or risk mitigation. This competitive pressure will likely compress decision-making timelines, very likely pushing defense authorities to accelerate AI adoption to avoid perceived strategic disadvantages such as longer target identification times and slower force management capabilities. As rival powers continue advancing their own AI-enabled military systems, the US defense strategy will likely prioritize speed, scale, and operational effectiveness to secure strategic advantage, very likely increasing reliance on the private sector. Normalizing rapid and competitive AI integration will very likely increase the risk of instability in contested environments, as compressed decision-making timelines and reduced human oversight will likely increase the risk of misinterpretation of adversary actions and unintended escalation.


Military 

Military operational demands will very likely drive the DoW toward deeper reliance on private-sector systems for intelligence processing and logistics, with limited progress in developing a competitive in-house AI capability. Deepened dependency on the private sector will likely reduce operational and strategic autonomy, expanding shared control over critical functions.  Increased reliance on private AI companies, such as xAI, will likely lead to a redistribution of influence, where private firms will very likely gain a prominent role in shaping and defining national security capabilities, escalating pressure on military decision-making, and accelerating the integration of commercial priorities. External vendors will very likely pursue preexisting commercial roadmaps, product strategies, and profit development priorities, which will unlikely reflect national security objectives. This dynamic will very likely reshape national security capabilities to accommodate public-private models. The DoW’s desire to access superior private sector technology over investing in creating an ad-hoc system with DoW-defined specifics will likely lead to an escalation in the military’s dependence on external vendors for logistical capacity, very likely signaling that remaining competitive requires long-term private sector partnerships.

Technology

Rapid advancements in private-sector AI capabilities will very likely drive the accelerated integration of these systems into classified military intelligence networks, as the DoW will likely seek to leverage cutting-edge technologies not available through internal development alone. The government’s inability to develop internal AI systems will likely reinforce its reliance on external innovation as a necessary component of technological competitiveness. The government’s dependence on external innovation will likely increase its exposure to threats by incentivizing the adoption of potentially vulnerable systems, very likely expanding the attack surface and adversarial exploitation within classified environments. By adopting complex, privately developed systems despite their unresolved cybersecurity risks, the DoW will likely face an escalating risk of adversarial exploitation, data leaks, and system compromise.


Recommendations

  • The Counterterrorism Group (CTG) recommends that congressional and DoW oversight bodies mandate review mechanisms for public-private AI military contracts. This should include pre-deployment risk assessments of data access, system vulnerabilities, and operational use.

  • Congress and the DoW should expand specialized personnel capacity to strengthen coordination and ensure consistent enforcement of governance frameworks for AI use in classified military systems.

  • The DoW should expand engagement with Small and Medium-sized Enterprises (SME) and startups to diversify and strengthen access to reliable AI infrastructure and innovation, enabling efficiency, flexibility, and secure development to keep pace with advancements by China and Russia.

  • US defense and congressional leaders should advance coordinated standards and structured engagement with key competitors, including China and Russia, to reduce escalation risks from rapid military AI integration while preserving strategic stability.

  • The US Government should require that all critical military decisions solely based on AI need to be reviewed by a board of non-partisan third-party regional experts and analysts.

  • The military should establish a portfolio of third-party AI systems to reduce the risk of a dominant system shaping intelligence analysis and military responses.

  • US defense institutions should require contracted external  AI providers to register and share with the government the training data sources, the system model, its architecture, and a list of third-party components used to implement data in the system to ensure transparency of potential vulnerabilities.

  • US defense leadership and congressional oversight bodies should establish a dedicated unit to audit and supervise AI systems across government networks, with the authority to inspect systems and prevent private-sector companies' exploitation or concealment of vulnerabilities that threaten classified operations.


Threat Climate Assessment

Analysis indicates there is a HIGH PROBABILITY that the threat climate will shift from a state-centered model of AI integration into classified military systems to an externally dependent model increasingly shaped by private companies, VERY LIKELY resulting in increased reliance on government-contracted companies for critical defense functions. This shift will LIKELY alter US defense and policy behavior in the short term by prioritizing rapid deployment over regulatory oversight, increasing coordination challenges across political and DoW institutions, while deepening dependence on private AI providers. In the long term, this focus on rapid AI deployment will LIKELY increase structural vulnerabilities, reducing operational autonomy, exposure to cybersecurity threats, and the gradual alignment of national security capabilities with private-sector priorities rather than government objectives. Escalation thresholds, such as expanded access of private AI systems to military classified networks or the emergence of significant system vulnerabilities, will VERY LIKELY challenge the defense sector, increasing the likelihood of operational disruption and adversarial exploitation. The continued acceleration of AI integration without corresponding governance capacity will LIKELY constrain the US government’s ability to independently control, secure, and sustain its core defense functions, VERY LIKELY requiring immediate attention to oversight, resilience, and strategic autonomy.

[1] The ultimate game of chess: war games, machine learning, and artificial intelligence, by Naval Information Warfare Center (NIWC) Pacific, licensed under Public Domain (The appearance of U.S. Department of Defense (DoD)/ Department of War (DoW) visual information does not imply or constitute DoD/DoW endorsement.)

[2] Artificial Intelligence Strategy for the Department of War, DoW, January 2026, https://media.defense.gov/2026/Jan/12/2003855671/-1/-1/0/ARTIFICIAL-INTELLIGENCE-STRATEGY-FOR-THE-DEPARTMENT-OF-WAR.PDF 

[3] OpenAI reaches deal to deploy AI models on US Department of War classified network, Reuters, February 2026,

[4] 2025 in Review: How the US Military Put AI to Work, Military.com, December 2025,

[5] Warren demands Hegseth share information about xAI's access to classified networks, NBC News, March 2026,

[6] Ibid

[7] Ibid

[8] Ibid

[9] ‘Accelerate like hell’: Hegseth moves to reshape DOD’s AI and tech hubs, Defencescoop, January 2026, https://defensescoop.com/2026/01/13/hegseth-ai-tech-hubs-reorganization-dod-dow/

[10] Big Tech backs Anthropic in fight against Trump administration, BBC, March 2026, https://www.bbc.co.uk/news/articles/c4g7k7zdd0zo 

[11] Musk's xAI and Pentagon reach deal to use Grok in classified systems, Axios, February 2026, https://www.axios.com/2026/02/23/ai-defense-department-deal-musk-xai-grok 

[12] Ibid

[13]  Artificial Intelligence Strategy for the Department of War, DoW, January 2026, https://media.defense.gov/2026/Jan/12/2003855671/-1/-1/0/ARTIFICIAL-INTELLIGENCE-STRATEGY-FOR-THE-DEPARTMENT-OF-WAR.PDF 

[16] Trump announces private-sector $500 billion investment in AI infrastructure, Reuters, January 2025, https://www.reuters.com/technology/artificial-intelligence/trump-announce-private-sector-ai-infrastructure-investment-cbs-reports-2025-01-21/  

[17] US defense department awards contracts to Google, Musk’s xAI, Reuters, July 2025, https://www.reuters.com/business/autos-transportation/us-department-defense-awards-contracts-google-xai-2025-07-14/ 

[18] Ibid

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