Ukraine Is Progressing Toward AI-Enabled Autonomous Warfare

AI-enabled autonomous warfare is no longer a science-faction fantasy, nor even a future vision: it is now, for Ukraine, an explicit, achievable strategic goal.

This focus is driven by necessity: there are fewer Ukrainians than Russians and their lives are more precious to their government than are Russian soldiers to theirs. Ukraine has developed drones to the point where they can be reconfigured in multiple ways as flexible and scalable assets. Their increasing sophistication, lower cost and effectiveness makes them an ever more useful weapon. Training for operators can now be conducted in less than a day. The hold up now, as it is for much AI deployment, has to do with hold-ups in bringing AI utility to the necessary level. The next major goal is expanding the focus from single drones to swarms. JL

Kateryna Bondar reports in the Center for Strategic and International Studies:

The Ukrainian military’s objective is to remove warfighters from direct combat and replace them with autonomous systems. This reflects the need to conserve human force. (But) AI has not (yet) reached the required level of development. Ukraine is developing standalone AI-driven software integrated across platforms to expand battlefield autonomy. Adding an (IED) and sensors to an FPV platform can transform it into a kamikaze drone; a bomber; an intelligence system. This modular approach makes FPV drones a flexible, scalable asset. AI-enabled systems reduces human limitations and allows locking on to targets 2 km away. Autonomous navigation makes drones strikes three to four times more likely to succeed. 

On the battlefield I did not see a single Ukrainian soldier. Only drones. I saw them [Ukrainian soldiers] only when I surrendered. Only drones, and there are lots and lots of them. Guys, don’t come. It’s a drone war.

— Surrendered Russian soldier

 

Executive Summary

This paper examines how Ukraine is advancing AI-driven unmanned systems to reduce direct warfighter involvement while enhancing combat effectiveness. Although fully autonomous warfare remains an aspiration, significant progress has already been made in partial autonomy—particularly for aerial systems—while human oversight remains critical in engagement decisions. 

Key Findings

1. The Ukrainian military’s objective is to remove warfighters from direct combat and replace them with autonomous unmanned systems. This goal reflects the need to conserve a limited human force and overcome vulnerabilities such as fatigue, stress, and the limited capacity to process and fuse large amounts of data from various sources and sensors. Although not yet formalized into a written strategy, this vision unifies Ukraine’s military and defense industry around the adoption, acquisition, and rapid deployment of advanced technologies—including AI-enabled capabilities—and the expansion of unmanned systems.
2. Autonomy—defined by the U.S. military as a system’s ability to accomplish goals independently or with minimal supervision in complex and unpredictable environments—is not yet present on the battlefield in the war in Ukraine. The primary reason for this is that the necessary technology—AI in particular—has not reached the required level of development. Additionally, Ukraine has no formal legislative or policy definition for “autonomy” or “autonomous weapons systems.” As a result, the Ukrainian military uses the term “autonomous systems” interchangeably with “unmanned systems,” or platforms equipped with basic autonomous functions such as navigation or targeting.
3. The current deployment of AI is partial in scope, enhancing certain functions and addressing some operational challenges rather than enabling full system autonomy. AI is a foundational technology for transitioning from automated to autonomous systems, or systems that can decide how to achieve a goal rather than merely execute human-programmed algorithms. AI significantly enhances specific functions, such as drone footage analysis and target recognition, target tracking, and autonomous navigation, including last-mile navigation and sound and text analysis for intelligence extraction, where AI replaces 99 percent of human labor. While such systems may operate without direct human control, they typically do not perform the entire process of finding, selecting, and engaging targets independently.
4. Ukrainian forces have widely adopted small and medium first-person-view (FPV) drones as platforms that may be quickly adapted for diverse missions through modular design and interchangeable equipment. Unlike the United States, Ukraine categorizes drones based on structural configuration, payload capacity, and propeller diameter. Initially, 7 inch FPV drones were common due to their ease of assembly, but growing operational demands have shifted preferences toward 9–10 inch quadcopters capable of carrying heavier payloads and achieving longer ranges. Adding an improvised explosive device (IED), an IED release mechanism, various sensors, or signal relaying equipment to the same FPV platform can transform it into a kamikaze drone; a bomber; an intelligence, surveillance, and reconnaissance (ISR) system; or a relay node. This modular approach, which allows for quick adaptation to diverse missions by swapping components, makes FPV drones a flexible and scalable asset on the front line.
5. Ukraine’s defense industry is developing standalone AI-driven software that can be integrated across various platforms to expand battlefield autonomy. This software enables key autonomous functions such as environmental perception, target recognition, and navigation, including last-mile approach to the target. It comes in standalone modules, consisting of compact chips with embedded software and sometimes cameras. These modules can be integrated into a range of platforms, from small FPV drones and long-range-strike drones to turrets mounted on unmanned ground vehicles. As a result, companies are focusing on developing separate autonomous functions while ensuring their compatibility across multiple platforms and unmanned systems.
6. The Ukrainian defense industry is pursuing an approach of training small AI models on small datasets rather than developing large, all-encompassing models. This approach enables fast and efficient onboard processing on the limited computing power of small and inexpensive chips, which can be quickly updated, retrained, and upgraded to adapt to changing battlefield conditions. These datasets can be collected through a company’s battlefield operations or open-source data from social media. Military authorities can filter out highly relevant datasets from the Ministry of Defence’s broader military dataset and allow companies to train their models in a protected military environment.
7. Delegating target recognition to AI-enabled automatic target recognition (ATR) systems onboard unmanned platforms reduces human limitations and allows locking on to targets up to 2 km away. By automating equipment identification and object detection, drones ease the burden on frontline personnel affected by fatigue, stress, or skill variability. Advancements have extended target recognition ranges from 300 meters to an average of 1 km in combat and to up to 2 km in optimal conditions. AI-powered software also counters decoys and camouflage, which can deceive the human eye. As adversaries refine their evasion tactics, AI-enabled ATR models require continuous, real-world data updates to maintain accuracy and adapt to evolving battlefield conditions.
8. Autonomous navigation makes drones strikes three to four times more likely to succeed. By removing the need for constant manual control and stable communications—both of which are vulnerable to electronic warfare and lack of operator skills—drones enabled with autonomous navigation raise the target engagement success rate from around 10 to 20 percent to around 70 to 80 percent. Although the striking precision is not very high, when Ukrainian forces expect it to be in “reasonable radius” rather than a specific point on a target, autonomous navigation reduces demand on the skill level of the operator and makes weapons systems with AI-enabled navigation accessible to a larger number of warfighters.
9. The adoption of drones equipped with AI-enabled autonomous navigation capabilities is driving a marked decrease in overall strike costs by minimizing both drone losses and repeated mission attempts. As a result of more efficient mission execution, these systems can often achieve objectives using just one or two drones per target rather than eight or nine. Furthermore, the integration of fully autonomous flight—from takeoff through mission execution to landing—makes systems reusable and reduces the need for frequent equipment replenishment.
10. Ukrainian engineers are increasingly leveraging open-source technologies and existing computer vision models to accelerate research and development while keeping costs low. By integrating readily available software solutions—including open-source computer vision frameworks—developers can rapidly create and deploy autonomous functions. This approach is particularly advantageous for “attritable,” or expendable, platforms, where the benefits of minimizing both per-unit and development costs often outweigh those of highly customized solutions. Additionally, open-source components facilitate faster prototyping, ongoing updates, and a collaborative development environment that draws on global research—all of which help maintain an agile edge in modern conflict scenarios.
11. Encrypting onboard AI software enables Ukraine to preserve its technological edge by making autonomous systems difficult to reverse engineer. Although adversaries can replicate hardware designs in a matter of weeks, sophisticated encryption in AI-enabled software significantly slows down their efforts to develop equivalent systems. This secure software advantage allows Ukrainian forces to maintain a lead in drone autonomy. By investing in robust encryption protocols, Ukraine not only shields its critical algorithms and data but also establishes a strategic deterrent against immediate duplication, reinforcing the enduring value of high-tech innovation in modern warfare.
12. Training to operate unmanned systems equipped with autonomous features can now be completed in as little as 30 minutes to one day, substantially broadening access to these weapons systems. What once required extensive flight hours now requires only a few hours, enabling a wider pool of soldiers to develop the necessary skills with minimal specialized expertise. As self-guided systems become more prevalent, drone training programs increasingly integrate autonomous targeting and navigation into their curricula. Recognizing this shift, institutions that educate drone operators equip learners to handle both manual and AI-assisted functionalities, often mastering autonomous modes in under a day. This accelerated learning curve expands the pool of qualified operators and bolsters overall operational readiness.
13. Ukrainian authorities are expediting the formal adoption and procurement of software and modules equipped with autonomous capabilities. Key initiatives include codifying these autonomous modules in alignment with NATO standards and integrating them into official military service, which helps to scale acquisition. By classifying these modules as distinct components and establishing clear guidelines for their integration and use, the Ukrainian military is speeding up procurement and deployment timelines. In 2024, Ukrainian forces began purchasing 10,000 AI-enhanced drones—a preliminary yet significant step toward broader adoption of advanced autonomous systems. Although this figure represents only a fraction of the nearly 2 million drones built by Ukraine in 2024, it shows Ukraine’s growing commitment to increasingly autonomous and capable platforms.
14. Ukrainian military authorities increasingly require all unmanned and reconnaissance systems to integrate with situational awareness and fire-correction platforms, aiming to establish a common operating picture in real time. To meet this demand, manufacturers must ensure their systems can feed data seamlessly into shared situational awareness and command and control environments. Even foreign suppliers recognize this imperative. For instance, Skydio’s drones are linked with the Ministry of Defence’s Delta system. The same may be said of the Ukrainian acoustic reconnaissance system Zvook and the text analysis tool Griselda, which provides intelligence from group chats and intercepted Russian communications. By unifying these capabilities, Ukrainian forces create a comprehensive, real-time operational picture that spans domestic and international technology providers.
15. Two major challenges lie ahead for AI-enabled autonomy: extending these capabilities to ground, sea, and undersea platforms and enabling swarming for aerial systems. Although aerial drones have led the way in autonomous operations, adapting similar functionalities for multidomain use requires overcoming more complex technical and environmental hurdles. While the potential for integrating autonomous navigation into ground systems is significant, practical implementation remains largely unexplored by Ukrainian defense companies. In the aerial domain, swarming is currently in a stage of small-scale experiments; however, fully realized swarms—where drones communicate, make decisions, and adapt in concert—have yet to be developed. Achieving such sophisticated coordination will demand substantial advancements in AI algorithms, communication protocols, and real-time decisionmaking capabilities.
16. Human oversight remains pivotal—particularly for engagement decisions—reflecting a human-in-the-loop approach that could shift toward higher-level supervision in the future while still maintaining human control of the system. Although Ukrainian forces aim to expand autonomy wherever it can enhance operational effectiveness, engagement decisions remain squarely in the human domain. Current human-in-the-loop practices allow operators to override autonomous functions, ensuring critical ethical and strategic judgments remain under human control. This approach lays a foundation for broader autonomy in the future—but with sustained human involvement at pivotal junctures where the stakes are highest.