Asymmetric warfare is an important form of modern warfare, which relies on the asymmetry of power, technology, means, etc., breaks the conventional logic of confrontation, and achieves the strategic goal of defeating the strong with the weak and expanding with the small. With the rapid iteration of artificial intelligence technology, AI has reconstructed the winning mechanism of asymmetric warfare with its abilities of global perception, autonomous collaboration, etc., providing a new path for the weak to compensate for the technological gap and the strong to consolidate the system's winning ability. In this context, exploring the practical path of AI empowering asymmetric combat capabilities is of great significance for winning future battlefields. AI empowers global perception and clears the "battlefield fog" of asymmetric warfare. Good battlefield perception ability is a prerequisite for fighting asymmetric warfare well. Traditional reconnaissance methods are limited by factors such as manpower, equipment, and environment, and suffer from problems such as lagging information acquisition, limited coverage, and inefficient data processing, making it difficult to meet the requirements of precise discovery, rapid positioning, and real-time tracking in asymmetric warfare. AI breaks down the temporal and spatial barriers of traditional reconnaissance through multi-source data fusion, intelligent recognition and analysis, and comprehensive situational analysis. It constructs a multi-dimensional, all-weather, and time-domain perception system, which greatly clears the "battlefield fog" for asymmetric warfare. AI achieves multi-source heterogeneous data fusion and constructs a global perception network. The modern battlefield covers various fields such as land, sea, air, space, electricity, and the internet. The reconnaissance information obtained often comes from scattered sources and has different formats. Traditional processing methods are difficult to achieve effective integration and data analysis. With the help of AI, the practical effects of these two levels can be significantly improved. At the level of data integration, AI can rely on technologies such as big data and cloud computing to quickly integrate multidimensional battlefield data, transforming fragmented data into systematic and visualized battlefield situation maps. At the level of data analysis, AI can be used to strengthen the analysis of the inherent connections between different data, discover high-value intelligence hidden behind massive amounts of data, and even accurately identify the core nodes of enemy asymmetric operations, effectively dispelling the "battlefield fog" and achieving first enemy detection, first enemy warning, and first enemy strike. AI enhances the level of dynamic tracking intelligence and strengthens the ability of precise perception. In the information and intelligent warfare, unmanned combat equipment is constantly emerging, which has the characteristics of large quantity, scattered targets, strong concealment, and flexible mobility. Traditional perception methods are often difficult to detect in a timely manner. AI can rely on deep learning algorithms and other technologies to achieve precise recognition and continuous tracking of small, moving, and hidden targets. For example, in terms of perceiving low altitude drones, AI can quickly locate target positions, determine target attributes, predict action trajectories, and provide precise data support for subsequent strikes. At the same time, AI can also achieve autonomous collaborative scheduling of perception devices, dynamically adjust reconnaissance direction and focus according to the battlefield situation, ensure the real-time and effective perception information, and solve the problems of being unable to see, locate, and keep up with the enemy in asymmetric warfare. AI empowers intelligent decision-making and reshapes the "command logic" of asymmetric warfare. In asymmetric warfare, command systems often face fast-paced and confrontational battlefield environments, while traditional command models have shortcomings such as long decision-making cycles, weak adaptability, and inefficient resource allocation, making it difficult to adapt to future battlefield needs. To address this issue, AI can build a "human-machine collaborative" command and decision-making system through algorithm deduction, scheme optimization, autonomous scheduling, and other methods, effectively compressing response time, improving decision-making speed, optimizing resource allocation, reshaping the command logic of asymmetric warfare, and achieving victory through speed and intelligence. AI accelerates OODA cycle operation and seizes decision-making opportunities. The OODA cycle is one of the fundamental logics of modern warfare. Whoever can complete the OODA cycle faster in asymmetric warfare will be one hand ahead and one step ahead of the enemy. AI, supported by powerful computing power, can complete battlefield situation analysis, enemy intent analysis, and combat plan generation in milliseconds, compressing the traditional manual decision-making cycle of hours or even days to seconds. In the practice of asymmetric confrontation, AI can capture subtle changes in enemy combat actions in real time, quickly predict their tactical intentions, synchronously generate multiple response plans and evaluate the optimal solution, assist commanders in quickly issuing instructions, and form asymmetric advantages of making decisions faster than opponents and taking actions earlier than opponents. AI optimizes the dynamic allocation of combat resources and enhances collaborative efficiency. Asymmetric warfare emphasizes concentrating superior forces to strike the enemy's weak points, which requires precise allocation of various resources such as troops, firepower, and logistics. AI can achieve intelligent matching and dynamic scheduling of combat resources by building a dynamic task scheduling platform based on battlefield situation, combat objectives, resource inventory, etc. Specifically, at the tactical level, AI can coordinate the coordinated actions of unmanned equipment, manned combat units, and firepower strike platforms, and allocate reconnaissance, strike, and support tasks reasonably; At the strategic level, AI can simulate and deduce the combat effectiveness of different resource allocation schemes, providing data support for the strategic layout of asymmetric warfare. AI empowers unmanned strikes and innovates asymmetric combat "strike mode". The traditional manned combat mode of firepower strikes has problems such as high risk of personnel casualties, high equipment costs, and limited combat radius, while asymmetric combat strives to achieve low-cost and high damage strike effects. AI promotes the development of autonomous, clustered, and intelligent unmanned combat equipment, builds an unmanned led, cluster coordinated, and precise destructive strike system, and innovates the firepower strike mode of asymmetric warfare. AI driven unmanned cluster combat, establishing low-cost asymmetric strike advantages. Intelligent unmanned equipment such as drone swarms, unmanned combat vehicle clusters, and unmanned ship formations can rely on AI swarm intelligence algorithms to achieve autonomous collaboration, autonomous decision-making, and autonomous strikes. Compared with traditional high-end weapon platforms, this has the advantages of low cost, large quantity, and strong concealment. Based on this, vulnerable parties can deploy low-cost AI unmanned clusters on a large scale to carry out saturation strikes on enemy high-end air defense systems, armored clusters, and command centers, offsetting technological advantages with numerical advantages and breaking the enemy's equipment generation gap suppression. AI empowers precise and intelligent strikes, achieving "point and shoot" tactical breakthroughs. In an ideal state, asymmetric warfare can quickly strike key nodes of the enemy's combat system, paralyze their combat capabilities, and achieve victory in battle at the fastest speed possible. In traditional warfare, precision strikes often rely on the infrared radiation emitted by enemy heat sources. In the era of information and intelligence, AI can further enhance its ability to identify and lock targets, empowering missile, patrol missile, intelligent ammunition and other strike equipment to accurately strike key targets such as enemy command centers, communication hubs, logistics supply lines, and air defense radars. In addition, in complex electromagnetic interference and harsh natural environments, AI can autonomously correct the strike trajectory, avoid defense interception, and ensure strike effectiveness. At the same time, AI can evaluate the effectiveness of strikes, quickly determine the degree of target damage, and decide whether to carry out a second strike to achieve asymmetric combat objectives. AI empowers the system to break through and provide intelligent support, improving the "sustained combat power" of asymmetric warfare. The victory or defeat of asymmetric warfare not only depends on the effectiveness of a single strike, but also on the continuous breaking of the enemy's combat system and the stable support of our own logistics support. In response to the characteristics of long-term confrontation, precise consumption, and flexible mobility in asymmetric warfare, AI can locate the weaknesses of enemy systems, intelligently plan breakthrough paths, dynamically optimize support links, and achieve efficient breakthrough of enemy combat systems and stable improvement of our own sustained combat capabilities, becoming an important support for fighting asymmetric warfare well. AI accurately locates system weaknesses and achieves efficient system breakthrough. Based on global perception data and algorithm modeling, AI can perform correlation analysis on various combat elements of the enemy, accurately identify weak nodes and related links in command and control, intelligence reconnaissance, firepower strikes, logistics support, etc., and construct a digital twin model of the enemy's combat system. And based on this, simulate the effects of different attack plans, plan the optimal attack path, and quickly paralyze the enemy's overall combat capability by hitting a point, paralyzing a piece, and destroying the whole situation. Compared to traditional combat methods, AI driven systems are more targeted and efficient in breaking down targets, achieving maximum combat effectiveness at the minimum cost, and in line with the combat principle of "winning with skill" in asymmetric warfare. AI builds an intelligent logistics support system to support sustained asymmetric confrontation. Asymmetric warfare often presents the characteristics of dispersed battlefield, frequent mobility, and irregular consumption, which puts extremely high demands on the timeliness, accuracy, and flexibility of logistics support. AI can integrate data on material warehousing, transportation routes, battlefield consumption, etc. to build an intelligent logistics scheduling platform, achieving full process intelligent support for demand prediction, precise delivery, and dynamic adjustment. Specifically, firstly, AI can accurately predict the degree of material consumption based on battlefield data, plan supply plans in advance, and avoid delayed support or resource waste. Secondly, AI can optimize transportation path planning, avoid enemy fire interception and complex terrain obstacles, and achieve safe and efficient distribution of logistics materials. Finally, AI can also perform real-time status monitoring and fault prediction on equipment, carry out maintenance and upkeep in advance, ensure that combat equipment is always in good condition, provide solid support for long-term and sustained confrontation in asymmetric warfare, and greatly enhance the survival and sustained combat capabilities of troops on the battlefield. (New Society)