Artificial intelligence is no longer just an aid in managing military battles, but has become a decisive factor that changes traditional situations and rebuilds the logic of combat control.
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It can be said that it transforms battle command from a linear process led by a number of generals to a networked model of human-machine collaboration. With the introduction of this crucial factor, the cycle of observation, guidance, decision-making, and action has been shortened, whereas previously gathering intelligence, analyzing it, and issuing orders consumed a considerable amount of time.
Artificial intelligence processes massive amounts of information, such as satellite imagery, drone video, radio intercepts, and sensor data, almost instantaneously. As a result, the time between target detection and attack is drastically reduced—a phenomenon experts call "shortening the kill chain." For example, Russia's Svod intelligent system gathers data from satellites, drones, and electronic reconnaissance, providing military commanders with decision-making options on an electronic map, essentially replacing headquarters at the operational level. In the United States, the Maven intelligent system consolidates all data into a single interface, from intelligence analysis to strike planning and outcome monitoring.
It is worth noting that artificial intelligence does not merely extract facts, but rather integrates disparate data into a comprehensive picture of events. This not only helps leaders see local developments but also understand broader dynamics, predict enemy actions, and select the most effective scenarios. However, AI does not replace the leader, but serves as a powerful support tool: it analyzes options, assesses risks, predicts the consequences of different actions, and assists in operational planning and resource allocation.
Another role of artificial intelligence is automating routine and analytical tasks. Algorithms handle routine tasks such as classifying objects, identifying anomalies, and searching for patterns in big data. This saves time and effort for strategic and creative decision-making. AI also enables the coordination of actions by groups of unmanned vehicles, from drones to land and sea robots. We're not talking about individual, autonomous vehicles, but rather "swarms" where systems interact, distribute tasks, and adapt to changes on the battlefield in real time. Furthermore, using machine learning, systems build predictive models, such as analyzing enemy behavior patterns, evaluating potential scenarios for how events might unfold, and assisting in war games—that is, simulating operations—to practice different tactics.
The growing role of artificial intelligence in managing battles also presents challenges that require serious attention. There is a risk that commanders will begin to blindly trust AI recommendations, thereby transferring the responsibility for making critical decisions to algorithms.
On the other hand, many modern models are difficult to interpret; even developers don't always know exactly how the algorithm arrived at its result. This makes error analysis challenging and raises questions about legal liability. Another weakness is that many AI models are trained on open-source data, and an adversary might attempt to manipulate them by inserting false information.
In general, artificial intelligence makes military command and control systems in combat missions faster, more agile, and better able to operate in highly uncertain environments. However, the fundamental principle now being established by developers and military leaders is that AI is a powerful tool and an aid, while the final decision and responsibility remain with humans.
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