AI as a Pillar of Russian Hybrid Warfare
How is Russia Leveraging Artificial Intelligence in its War in Ukraine?
Bio: Erin is a sophomore at Georgetown University's Walsh School of Foreign Service pursuing a degree in International Politics and a certificate in Eurasian, Russian, and East European Studies. Her research interests include Russian and Eastern European history and politics, hybrid warfare, and the role of emerging technologies in modern conflict.
TLDR: This article outlines how Russia is using AI to bolster its war efforts in Ukraine. While Russia lags behind the US and China in frontier developments, it has built a diverse software and hardware stack leveraging open-source and commercially available technologies from both its allies and adversaries. This makeshift stack has enabled Russia to tailor its AI deployment in ways that forward its interests in the war, particularly on the battlefield and in cyberspace. Ultimately, Russia’s integration of AI shows how nations can lag behind the frontier of AI development while still succeeding at integrating the technology.
The Russo-Ukraine War is the first major conflict to feature AI-powered military technology and electronic warfare on both sides. Russia is deploying rapidly evolving AI technology across many theatres of hybrid warfare to maintain strategic leverage over Ukraine and rebuild its sphere of influence in Eastern Europe. Rather than building frontier foundation models from scratch, Russia has focused its AI development on targeted capabilities like computer vision, sensor fusion, and signal processing designed specifically to deliver effective results on the battlefield in Ukraine. As opposed to investing in end-to-end AI-driven command workflows, it has prioritized AI applications that speed up kill chains and deliver immediate battlefield utility. Beyond wartime applications like automated drone swarms, Russia has also deployed AI in other hybrid theaters, including cyber and information warfare. These operations include jamming Ukrainian communications, deploying social media disinformation, and initiating propaganda campaigns. Russia is not chasing cutting‑edge, general purpose AI, but it is selectively weaponizing practical AI to enhance coercion, disruption, and strategic leverage against Ukraine and the West.
Where is Russia’s AI Is Coming From?
To meet wartime requirements, Russia has pivoted away from developing its own AI infrastructure from scratch, instead embedding foreign-developed, commercially available software and open-source AI ecosystems into its military operations. Despite international sanctions, Russia has integrated AI software from the US, China, and Europe into its battlefield operations, deprioritizing indigenous development of end-to-end AI platforms and general-purpose large language models. This is both a choice to optimize results on the battlefield in Ukraine and out of necessity due to limited domestic technological capabilities.
Russia has built up a limited domestic AI stack that it has adapted and integrated into its military and security decision support. Russia’s AI frontier continues to lag years behind its biggest competitors, the United States and China. In November 2025, Russian President Vladimir Putin spoke at the “Journey to the World of AI” conference, attempting to highlight and kickstart Russia’s future in AI and in particular its militaristic uses. He emphasized that “dependence on foreign AI systems is unacceptable,” and stressed the necessity of “sovereign” AI. However, in reality Russia lags three to five years behind the United States and China in generative AI and ranks 31st out of 83 countries in AI implementation, particularly in natural-language processing capabilities similar to ChatGPT.
Russia’s technological lag is due to layers of technological limitations, including hardware availability. During the Cold War and again following Russia’s annexation of Crimea in 2014, the U.S. leveled significant sanctions and export controls on Russia that hindered its technological development. This prevented Russia from accessing key Western technologies, slowing Russia’s industrial modernization. The results of Russia’s ostracization from the Western market persist today, creating a seemingly insurmountable gap between Putin’s stated goal to compete with adversaries’ modern capabilities and Russia’s actual infrastructure and capacity. For example, while global leaders like the U.S., Taiwan, and Japan already have or are approaching mass production of 3-nanometer AI chips, Russia will only start producing 28-nanometer chips by 2030.
Out of necessity, Russia has turned to gray market supply chains to acquire critical components for AI architecture. In December 2025, the Russian company Delta Computers described its newly released system as “sovereign architecture,” independent of foreign technology. However, the system is powered by smuggled Intel and NVIDIA components that have been strictly banned from export to Russia.
Ukrainian intelligence services have also found evidence of Western AI components inside Russian drones used to attack Ukrainian cities. Russia’s Lancet, an unmanned aerial drone, was shot down over Kiev on March 16, 2026 and was found to be carrying 62 electronic components of foreign origin, primarily from the United States. Ukrainian intelligence determined that Russia was integrating autonomous targeting capabilities into the drone using AI components based on American Nvidia systems. Russia has also imported Western dual-use processors from companies such as NVIDIA and Xilinx, as well as components from companies like Intel and Sony to coordinate drone swarms and to navigate difficult terrain without GPS.
Russia uses Western AI chips to power its AI infrastructure but frames the product as though it is sovereign and domestic, minimizing the reality: Russia lacks the talent pool and research investment to catch up with Western and Chinese technologies, and thus is forced to build AI programs atop foreign models and components sourced through gray markets.
Not only is Russia using foreign chips and components to power its own AI systems, it is also adopting foreign and commercially available AI models and integrating them into its military operations. Russia is unable to train frontier models domestically due to its technological deficits, and thus outsources its AI models to avoid the cost and time lag associated with developing its own competitive AI systems from the ground up. Developing advanced AI systems requires extensive hardware and technological infrastructure. A product like ChatGPT is powered by a large language model (LLM), which costs millions of dollars to develop and requires enormous amounts of electricity and advanced hardware like high-end graphics processing units (GPUs).
Lacking these resources and infrastructure, Russia has co-opted a patchwork of foreign-developed AI models to sustain its wartime AI infrastructure. Once trained on sufficient hardware abroad, these AI models can be deployed on Russia’s far less sophisticated hardware—termed a “hybrid” approach. For example, Russia has co-opted Chinese LLMs like Qwen for malware command generation in its military intelligence operations. Other foreign models that Russia has used include Mistral, LLaMA, and YOLO.
Russia’s military AI integration has largely involved developing systems that can track and intercept targets through target recognition, coordinate swarming techniques, and navigate autonomously. These are immediately successful on the battlefield in Ukraine but do not reflect a solid foundation of domestically-produced Russian AI capabilities. On the contrary, it reveals both Russia’s technological dependencies on foreign nations and the weakness of Western sanctions on technology components critical to AI system development.
Partnerships with Western Adversaries
Russia has taken advantage of its strategic partnerships with China, Iran, and North Korea, the United States’ four primary adversaries, to maximize its AI-driven warfare capabilities. The war in Ukraine has accelerated cooperation between CRINK nations (China, Russia, Iran, and North Korea), enabling faster deployment of AI-enabled systems and allowing U.S. adversaries to test their capabilities. The flow of weapons transfers shifted significantly following Russia’s invasion of Ukraine. While pre-2022 numbers showed Russia as the main exporter in the CRINK arms trade, the invasion led Moscow to begin relying heavily on arms from Iran and dual-use components from China.
In June 2025, Ukrainian drone hunters discovered AI-powered components and new Iranian technology among weapons debris from a Russian assault in 2025, revealing the extent to which Iran has supported Russian wartime operations. The drone wreckage included an AI computing platform that would help the drone navigate autonomously if communications were jammed (an “anti-jamming” technique). Russia’s reliance on Iran extends back to 2022, importing hundreds of Iranian SRBMs and missiles and thousands of Shahed loitering munitions (or suicide drones). Iran has also shared additional technologies with Russia, such as providing advanced modifications for enhancing weapon AI capabilities.
China has not supplied weapons directly to the same extent, but has sold critical commercial and dual-use goods to Russia. This includes a list of “high-priority items” including computer chips, radars, and sensors that are essential to producing AI-enabled weapons systems. Accessing critical components from China has enabled Russia to evade Western sanctions and maintain its industrial production of military goods. Russia’s easy workaround highlights the ineffectiveness of Western sanctions, which were intended to undercut Russia’s wartime operations. Russia has circumvented them by capitalizing on its partnerships with Iran, China, and North Korea.
Russia’s Strategic Uses of AI in Ukraine - the battlefield, cyberspace, and the information ecosystem
Russia has deployed its AI tools to achieve several broad strategic objectives in Ukraine, including battlefield and operational level uses alongside cyber, electronic warfare, and information operations. Russia’s AI-enabled battlefield and operational level include air defenses or partial AI-enabled command and control pathways that accelerate decision cycles and “kill chains.”
Preceding the war in Ukraine, Russia’s Ministry of Defence wanted to build an automated command and control (C2) system, which would seamlessly link sensor technology, commanders, and weapons in an end-to-end, digital warfighting system. An ideal, AI-powered version of this would allow for fully autonomous military operations with minimal human involvement, from high-level decision-making to tactical operations. However, Russia’s technological deficits have hindered Russia’s progress towards this goal, and the war in Ukraine prompted Russia to shift its priorities toward developing effective tools on a short timeline to achieve immediate results on the battlefield.
This has led to Russia’s development of a patchwork of foreign and domestic AI models and applications, fused together in real time over the course of the war with dramatically uneven capabilities. Russia’s more advanced capabilities, the visual and data processing tools such as computer vision, sensor fusion, and signal analysis, are used to power unmanned aircraft systems (UAS) and automatic target recognition (ATR). UASs now make up 80 percent of all fire missions in the Russia-Ukraine war, with Russia striking around 300 Ukrainian targets each day, illustrating the necessity of leaning into investment in automated aircraft capabilities on both sides.
Russia has integrated AI into several layers of its drone attacks. Over the course of the war, Russia has transformed its drone warfare from just a peripheral component of its military to a strategic mainstay. During the Ukraine war, Russia has significantly expanded its use of drones for intelligence, surveillance, and reconnaissance (ISR) and has augmented several layers of its ISR techniques with AI. Today, Russia uses unmanned aircraft systems (UASs) for everything from surveillance and imaging to tracking troop movements, identifying targets, developing AI-driven strike systems, and evading Ukrainian electronic warfare attacks. While both Russia and Ukraine have made significant advances in their drone warfare, neither have reached full autonomy via AI-powered systems that require minimal to no human oversight. However, AI continues to improve many functions of both countries’ warfighting systems.
One example of Russia’s use of AI is using AI-powered UASs to counter Ukrainian jamming techniques, a form of electronic warfare (ER). Radio frequency (RF) jamming is a tactic used to interfere with the radio signals connecting drones with their human operators. If Russia is operating UASs to target Ukrainian infrastructure, Ukrainians can jam the signal to disrupt the Russian operator’s control over the drone and make the drone lose track of its target. Russia has begun using AI-based automatic target-locking systems to allow its drones to navigate autonomously when jamming occurs, equipping them with sophisticated computer vision capabilities. Once the operator identifies a target, the drone can effectively operate by itself. Ukraine is deploying the same technology against Russian-operated drones, alongside sophisticated AI-powered swarming techniques.
Beyond these capabilities that make up Russia’s hybrid assortment of various AI-enabled command workflows and targeting capabilities, Russia has also allocated significant AI resources towards electronic warfare, cyber, and information operations. As Ukrainian engineer Yaroslav Azhnyuk puts it, it is not hard to envision modern battlefields with “swarms of autonomous drones carrying other autonomous drones to protect them against autonomous drones, which are trying to intercept them, controlled by AI agents overseen by a human general somewhere.” As Russia continues expanding its command and control infrastructure and applying AI to its military, cyber, and information operations, this vision may not be so far-fetched.
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