I missed (April) this one, maybe western media is not interested in informing about Russian innovation? What US has to learn from Russia, not from Ukraine.
Kateryna Bondar analyzes how Russia is leveraging applied AI and building drone ecosystem, combining decentralized innovation, commercial tech, and state coordination to accelerate battlefield autonomy.
www.csis.org
For the United States, the central lesson is that success in AI-enabled unmanned systems requires an ecosystem approach. To advance its ambitions in autonomous technology, the United States must implement a national systems project approach that incorporates and aligns training, testing, dual-use innovation, government implementation, and civil-military cooperation.
Ukrainian technical analysis of intercepted V2U drones indicates the absence of communication components required for operator control, alongside the presence of onboard computing sufficient to run AI-enabled perception and decision-making software.
U.S. firms account for roughly 69 percent of memory hardware, 57 percent of processors, and 38 percent of sensors. By comparison, China supplies less than 9 percent of total AI-enabling components.
Projects such as Molniya demonstrate a recurring pattern: rapid experimentation by civilian engineers and volunteer groups at the “garage” level, followed by selective state intervention to finance, standardize, and mass-produce systems that prove operationally effective. This approach allows the state to capture the benefits of decentralized innovation while avoiding the inefficiencies of attempting to centrally design solutions under wartime pressure.
Dual-use firms can draw on far larger and more varied datasets, iterate software in real operational environments, and continuously retrain models based on civilian and security applications. This access to data, testing opportunities, and feedback loops allows AI capabilities to mature faster and transition more smoothly into battlefield use than systems developed exclusively inside closed military programs.
Once a design proves viable, it is quickly repurposed across multiple roles—for example, as a loitering munition, reconnaissance platform, or logistics carrier—through minimal airframe changes and software updates. Simple construction and modular architecture allow fast iteration based on frontline feedback, accelerating the diffusion of successful designs across different mission sets.
(Even if I read something about this, western media is almost always about Ukrainian innovation; Russia is still using sharpened spades.)
The objective is to move beyond political rhetoric and evaluate the underlying system of planning, coordination, and state oversight that shapes Russia’s approach to innovation under wartime conditions.
(We shouldn't pay that much attention to "political rhetoric", in general.)
The strategy
(updated in 2024 and goals for 2030/2036) focuses on the applied, dual-use dimensions of AI. In practice, Russia seeks to leverage algorithms and models already developed abroad, integrating them into domestic applications across defence, security, and industrial automation.
The practical orientation of Russia’s strategy has already translated into tangible progress on the battlefield, rather than remaining confined to policy documents or strategic declarations.
Russia intends to replace foreign UASs, components, and software with its own systems.
Kronshtadt, Orion, unsuccessful. ZALA, Lancet, successful. Molniya, extremely successful. V2U, beyond.
In one reported case in May 2025, a group of seven V2U loitering munitions deviated from a pre-planned mission after detecting a concentration of vehicles and civilians, autonomously forming a circular holding pattern before initiating coordinated attacks.
Project Archangel. Typically through two- to three-month courses focused on practical drone operations, counter-drone tactics, and the integration of emerging technologies into combat units, it does not merely supplement state training but also helps create parallel pipelines capable of rapidly absorbing battlefield lessons and translating them into structured instruction.
The group has actively shaped technological adaptation. Its engineers developed systems such as the Archangel counter-UAS system and paired hardware innovation with operator training programs to ensure fielded systems could be employed effectively. Training centres integrated advanced software tools, including the Glaz/Groza complex for improved reconnaissance and strike coordination and Kvadrosim, a combat simulator for drone operation and interception, thereby embedding digital tools directly into the instructional process.
The Russian military has restructured elements of its force by concentrating experienced operators, validating systems, refining tactics into elite formations, and then scaling these practices across the broader force—culminating in the establishment of the dedicated Unmanned Systems Forces and centralized training and innovation centers designed to standardize and expand drone warfare expertise.
However, reports indicate that the effectiveness of this training is limited by inadequate equipment and lack of standardization. Moreover, training timelines can also be rushed: contract soldiers may receive just three weeks of total training before participating in frontline operations.
(Not to say that Ukrainians get 3 months. As, I cannot say that, I got.)
The progression from decentralized volunteer groups to Rubicon as a centralized elite unit, and ultimately to the Unmanned Systems Forces, illustrates how Russia identifies operationally successful models, concentrates expertise, and then scales them across the broader force through formal institutional mechanisms.
Training, not hardware alone, determines battlefield outcomes.
(A lesson that must always be relearned.)
Russia’s adaptation in drone warfare has been driven less by isolated technological breakthroughs and more by the systematic integration of training, doctrine, and organizational reform, an approach that increasingly shapes successes on the battlefield.
The structural vulnerabilities of globally integrated semiconductor and electronics markets, where dual-use technologies remain widely accessible despite sanctions and export control regimes.
(We were supplying Iran and Iraq, not supplying Russia would be a bad business strategy.)
The findings also complicate narratives that emphasize China as the primary supplier of Russian drone components. While China plays a role in the broader electronics ecosystem, Western firms, particularly U.S.-headquartered companies, remain central suppliers of AI-relevant hardware.
Battlefield effectiveness has emerged not from elegant autonomy architectures, but from low-cost, modular, rapidly iterated systems embedded with narrowly scoped but mission-critical AI functions. Scale, speed, and feedback loops have proven more decisive than technological sophistication alone.
The central lesson is that ecosystem coherence, not individual programs, determines success in AI-enabled unmanned warfare.
Then I found this...
Software could make ethically superior decisions to humans in high-pressure moments, claims ex-GCHQ head David Omand
www.theguardian.com
Trump's moral code, maybe?
www.themoscowtimes.com
