{"id":13812,"date":"2026-07-16T16:31:49","date_gmt":"2026-07-16T14:31:49","guid":{"rendered":"https:\/\/www.rivistaeco.com\/?p=13812"},"modified":"2026-07-16T16:31:49","modified_gmt":"2026-07-16T14:31:49","slug":"kyivs-leadership-in-military-ai","status":"publish","type":"post","link":"https:\/\/www.rivistaeco.com\/en\/2026\/07\/16\/kyivs-leadership-in-military-ai\/","title":{"rendered":"Kyiv’s Leadership in Military AI"},"content":{"rendered":"

Artificial intelligence is rapidly redefining modern warfare by transforming the way battlefield data are collected, analysed, and used. Within Europe, one country is testing AI-based defence systems under real combat conditions: Ukraine. From drones to logistics, experience has shown that these technologies can improve decision-making, precision, and operational effectiveness in military operations. The other side of the coin is that their growing autonomy from human guidance and control raises important ethical and strategic questions, particularly when critical decisions are involved. Ultimately, the lesson from Kyiv is clear: technological superiority matters, but it is not enough unless it is supported by battlefield data and operational experience capable of “training” artificial intelligence.<\/em><\/p>\n

 <\/p>\n

The use of artificial intelligence in defence is not a new phenomenon. Since 2017, the United States has employed machine-learning techniques to analyse drone and satellite imagery as part of Project Maven. Other countries\u2014including the United Kingdom, France, and China\u2014have likewise been developing military AI strategies and programmes for years.<\/p>\n

Ukraine, however, is a different case. Today, no other country can claim comparable experience in testing AI-based systems under the conditions of high-intensity warfare. This is a decisive advantage because the effectiveness of artificial intelligence depends to a great extent on data and operational feedback. Even a substantial technological lead cannot replace the contribution of real-world battlefield data, which remain the essential foundation for the successful development and deployment of these technologies.<\/p>\n

Filtering the “Noise” of Information Overload Through AI<\/strong><\/h3>\n

Modern warfare generates enormous quantities of data: streams from drones, satellites, intercepted communications, radar systems, and acoustic sensors. Today’s battlefield is often described as “transparent” because it is simultaneously monitored by multiple systems producing thousands of hours of video every day. Most of this information, however, is little more than noise and must be filtered before it becomes genuinely useful. This is precisely where artificial intelligence comes into play.<\/p>\n

AI systems are capable of analysing video feeds, identifying equipment, processing communications, and integrating information drawn from multiple sources. Some algorithms classify enemy vehicles in drone footage; others interpret satellite radar imagery or analyse intercepted communications. The objective is not simply to collect information, but to make it immediately usable by commanders, thereby strengthening command-and-control systems.<\/p>\n

Within this context, Delta, the battlefield ecosystem developed by Ukraine, represents one of the world’s most advanced digital battlefield platforms. It enables information to be visualised and shared while supporting operational planning. Within Delta, the Avengers AI module detects around 12,000 objects every week, while Clarity identifies and maps indicators of enemy activity, reducing analysts’ workload by as much as 90 percent. A faster intelligence cycle shortens the time between identifying a target and making an operational decision.<\/p>\n

Despite these advances, artificial intelligence still remains limited in several crucial aspects of military decision-making.<\/p>\n

Automatic Target Recognition<\/strong>\u00a0<\/strong><\/h3>\n

In Ukraine, the most visible application of artificial intelligence in defence concerns uncrewed systems. AI-powered software can detect, classify, and track targets, enabling drone sensors to distinguish whether an object is a vehicle, a person, or a piece of military equipment. The most advanced systems can even continue tracking a target after it has temporarily disappeared behind an obstacle.<\/p>\n

This process is known as Automatic Target Recognition (ATR). On a complex and constantly evolving battlefield, operators must contend with camouflage, decoys, poor visibility, and electronic interference. In such an environment, artificial intelligence can reduce the scope for human error and help maintain focus on the most relevant targets. It also enables drones to operate effectively even when time is limited or communications are unstable. AI-enabled reconnaissance drones, for example, can identify enemy equipment and automatically transmit its coordinates to command centres. Systems such as Saker represent a further step forward by combining aerial platforms with software capable of recognising and recording targets, including camouflaged ones. In other words, the most advanced solutions have evolved beyond simply locking onto a “point” and are now capable of classifying and prioritising targets.<\/p>\n

Despite this progress, these systems still suffer from significant limitations. Artificial intelligence performs extremely well when assigned specific tasks\u2014such as identifying a tank in an image or keeping a drone on course\u2014but encounters greater difficulties in managing complex decision chains that extend from target detection to target engagement. For this reason, many applications combine artificial intelligence with more traditional algorithmic approaches: AI performs highly specialised functions, while other components of the system remain responsible for verification, validation, and execution.<\/p>\n

The Future Belongs to Autonomous Navigation<\/strong><\/h3>\n

Ukraine also stands out in another crucial field: autonomous navigation. Technologies such as Bavovna AI, Skynode, and Vermeer illustrate the remarkable progress achieved in this area.<\/p>\n

Russia’s extensive use of electronic warfare has made GPS signals and communications increasingly unreliable near the front line. Under these conditions, drones may lose satellite positioning or their connection with the operator, becoming vulnerable to jamming or spoofing attacks.<\/p>\n

It is precisely in such scenarios that autonomous navigation becomes decisive. Thanks to onboard cameras, sensors, and visual navigation systems, drones can estimate their own position, avoid obstacles, and maintain their course even without external inputs, completing the final phase of their approach with little or no human intervention. This capability is particularly valuable during the “last mile” of an attack, when a drone is most exposed and vulnerable to electronic warfare.<\/p>\n

Looking ahead, onboard intelligence and the ability to operate independently of GPS will become essential for the development of drone swarms, in which multiple units must coordinate autonomously within the same operational environment.<\/p>\n

AI Beyond the Battlefield<\/strong><\/h3>\n

Artificial intelligence is not used only on the battlefield during wartime. It is also playing an increasingly important role in logistics: it can forecast demand, plan supply routes, manage ammunition and fuel inventories, and support maintenance operations. These functions may be less visible than the operational use of drones, but they are fundamental to sustaining prolonged conflicts because they reduce shortages and waste while accelerating deliveries to frontline units.<\/p>\n

There is also the issue of cybersecurity. Ukrainian military and civilian infrastructure is constantly exposed to cyber threats, and AI-based tools make it possible to detect suspicious activity, identify new forms of attack, and respond more rapidly. In this sense, artificial intelligence is not merely a weapon but also a protective layer for command systems and communications. AI can also be used to create realistic simulations and operational scenarios, allowing soldiers to train their decision-making skills under conditions that replicate the battlefield as closely as possible.<\/p>\n

Where Military Technology Is Heading<\/strong><\/h3>\n

Whereas in the past the development of military AI was constrained by the scarcity of real battlefield data, the situation has now changed: artificial intelligence is increasingly being used to filter, analyse, and organise vast quantities of information. Crucial decisions, however, still remain in human hands.<\/p>\n

The next stage may prove more complex. As artificial intelligence processes ever larger volumes of data, it also generates an increasing number of options, alerts, and recommendations that commanders may be unable to evaluate quickly enough. It is therefore likely that some phases of the decision-making process will gradually be delegated to machines, while the most sensitive choices remain under human supervision. This evolution presents both opportunities and risks. Greater autonomy can reduce risks to soldiers, accelerate operations, and improve effectiveness in environments where communications are disrupted. On the other hand, removing human beings from decisions concerning the use of force raises significant legal and ethical questions: who bears responsibility in the event of an error? And what degree of human oversight can truly be considered sufficient?<\/p>\n

For the time being, a layered approach continues to prevail, under which ultimate responsibility for the use of lethal force remains with human operators. This principle may evolve as technological reliability improves, but the overall trajectory clearly points toward progressively greater autonomy.<\/p>\n

The future of military AI will also depend on the ability to overcome major technical challenges, particularly those relating to integration and interoperability. Today, drone manufacturers employ a wide variety of sensors and onboard systems, each requiring dedicated guidance solutions\u2014an important limitation. It is therefore no coincidence that many companies are moving toward fully integrated systems, developing hardware and software together from the earliest stages of design.<\/p>\n

The Investment Challenge<\/strong><\/h3>\n

A sector capable of developing so rapidly and effectively has inevitably attracted the attention of investors. It is therefore hardly surprising that a substantial share of venture capital directed toward Ukraine’s defence industry has flowed into companies specialising in artificial intelligence. This reflects the growing conviction that AI-based defence technologies may represent one of Ukraine’s principal competitive advantages.<\/p>\n

Foreign investors, however, generally favour joint ventures and minority equity stakes rather than outright acquisitions. This enables them to gain access to technologies already tested in combat while limiting their exposure to risk. For Ukrainian firms, these partnerships provide capital, manufacturing capacity, access to international markets, and more structured governance models. Nevertheless, Ukraine continues to operate within a wartime economy, where future risks and returns remain exceptionally difficult to assess. Unsurprisingly, investors therefore continue to adopt cautious valuations.<\/p>\n

Development is further constrained by export restrictions, including limitations on technology transfers, which have so far hindered the expansion of production and the generation of revenues in international markets. Yet the situation is beginning to change. Ukraine now appears to be moving toward a model of controlled exports, based on selective authorisations under government supervision. If implemented carefully, this approach could enhance the country’s attractiveness to investors without undermining the priority of supplying its own armed forces.<\/p>\n

This could prove to be a decisive turning point, particularly for companies developing AI tools that are not legally classified as weapons but are integrated into drone systems. Until now, these firms have largely been excluded from international markets, significantly limiting their growth prospects.<\/p>\n

The Ukrainian Lesson<\/strong><\/h3>\n

Artificial intelligence is spreading rapidly throughout the Ukrainian armed forces, following a trajectory toward increasingly autonomous systems. For the moment, its principal applications concern detection, classification, navigation, and coordination, while the most sensitive decisions remain in the hands of human operators. Yet even this partial autonomy is far from insignificant. If an AI-enabled system allows a low-cost interceptor to destroy a far more expensive Shahed drone, it creates an economic asymmetry that penalises the adversary, even when that adversary possesses greater overall resources.<\/p>\n

In Ukraine’s case, the country’s competitive advantage derives primarily from the data collected directly on the battlefield. Other countries may possess more advanced technological ecosystems, but they find it difficult to train defence AI systems with the same degree of realism in the absence of actual operational conditions: combat, electronic warfare, operator feedback, and the systematic analysis of failures. Within this context, initiatives such as Brave1 Dataroom, developed in partnership with Palantir Technologies, play a crucial role. They transform wartime experience into a resource for training and testing AI models, beginning with data collected from drone-interceptor operations.<\/p>\n

For partner countries, the choice has now become essentially practical: either invest in Ukrainian AI solutions that have already been tested in combat, or find ways to test their own systems directly in Ukraine by making use of battlefield data. In an environment where cost asymmetry is becoming increasingly decisive, it is no longer sufficient merely to observe events or rely exclusively on technologies validated in laboratory conditions.<\/p>\n

 <\/p>\n

Olena Bilousova is Head of Defence Research at the KSE Institute in Kyiv. Her areas of expertise include Ukraine’s defence industry, military technologies, defence financing, and the Russian military-industrial complex, as well as the sanctions imposed upon it.<\/em><\/p>\n

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