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Empowering Joint Operations Planning with Intelligentization

以智能化赋能联合作战筹划
PLA Daily (解放军报) 4 June 2026
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A PLA author identified as Yang Lan argues in what appears to be a military theory journal that joint operations planning must transition from 'human-led, machine-assisted' to deep 'human-machine integration,' and lays out a four-part framework covering data infrastructure, decision-making reform, system-of-systems integration, and security hardening. The article documents the PLA's current institutional framing of AI-enabled command: it treats data standardization across services and domains, human-machine collaborative training ('dual human-machine loop'), and flattened command structures as unsolved construction problems, not accomplished capabilities. The explicit acknowledgment that AI algorithms lack creativity, cannot grasp political intent, and are vulnerable to adversarial manipulation raises the question of how far actual intelligentized planning systems have progressed beyond the conceptual stage.

Empowering Joint Operations Planning with Intelligentization

■ Yang Lan

Introduction

Joint operations planning, as the nerve center for organizing and employing joint combat forces, directly determines the outcome of war through the degree to which it is scientific, precise, and efficient. At present, with the deep penetration of artificial intelligence technology into the military domain, joint operations planning is undergoing a systemic transformation from "human-led, machine-assisted" to "human-machine integration, mutually complementary" (人机融合、互为补充). This transformation has produced a major impact on the underlying logic and operational modes of joint operations planning. We must profoundly grasp the inherent laws of intelligentized warfare (智能化战争), empower joint operations planning with intelligentization (智能化), and accelerate the construction of a joint operations planning capability system suited to future intelligentized warfare.

Consolidating the Data Foundation, Laying the Groundwork for Intelligentized Digitization

Data is the core element of intelligentized warfare. Laying a solid data foundation is the necessary prerequisite for joint operations planning to shift from "experience-driven" to "data-driven." Under traditional forms of warfare, data was merely reference information that assisted commanders in judging the battlefield situation. In intelligentized warfare, however, data has become the "blood" and "skeleton" of the combat system, running through the entire process of joint operations planning: from battlefield situational awareness, analysis of operational objectives, and organization of combat forces, to the generation of operational plans and assessment of operational effects—every link is inseparable from data support. The completeness, accuracy, and timeliness of data directly determine the precision and speed of intelligentized planning. From this perspective, without high-quality data support, empowering joint operations planning with intelligentization becomes water without a source and a tree without roots.

At a deeper level, data is the foundation for constructing battlefield digital twins and the bridge for achieving resonance between the physical battlefield and the virtual battlefield. With the support of intelligentized technology, we can collect, process, and analyze massive volumes of battlefield data, constructing in digital space a virtual mirror image highly consistent with the physical battlefield, thereby achieving real-time mapping of the battlefield situation, simulation and deduction of the operational process, and prediction and forecasting of operational outcomes. This digital twin capability enables joint operations planning to break through the constraints of physical time and space, conducting thorough deduction and verification of all possible situations before combat, thereby greatly improving the scientific rigor and feasibility of planning. At the same time, data is also the "fuel" for algorithm training; only by possessing sufficiently rich battlefield data can intelligent algorithm models capable of adapting to complex and ever-changing battlefield environments be continuously refined.

Therefore, empowering joint operations planning with intelligentization requires adhering to a data-first construction philosophy. First, a unified data standards system must be established to standardize data formats, interfaces, and semantics, resolve the heterogeneity problem of multi-source data, and achieve interconnection, interoperability, and shared exchange of data across different services and branches, different domains, and different systems. Second, a data collection network with full-domain coverage and multi-source fusion must be constructed, comprehensively employing various reconnaissance and sensing means across land, sea, air, space, electromagnetic, and cyber domains to obtain in real time full-dimensional data on the battlefield environment, enemy forces, and friendly force situations, forming a data collection capability covering the full spatial and temporal dimensions of operations. Third, data governance capability must be strengthened; through technical means such as data cleansing, deduplication, verification, and fusion, the accuracy, consistency, and credibility of data must be improved to provide continuous and stable data support for empowering joint operations planning with intelligentization.

Emphasizing Human-Machine Integration, Reshaping the Intelligentized Decision-Making Mode

In current intelligentized construction, artificial intelligence systems have already acquired comparatively powerful computational, storage, and learning capabilities, enabling rapid processing of massive data and generation of multiple operational plans, making them an indispensable force in joint operations planning under informatized and intelligentized conditions. But casting one's gaze toward the more distant future battlefield and the conduct of intelligentized warfare, artificial intelligence algorithms also have obvious limitations: they lack human creativity, imagination, and value judgment capability; they cannot understand the political nature of war and strategic intent; they cannot cope with unconventional situations and moral dilemmas that may arise in war; and they are ill-suited to adapt to the accelerating tempo and highly complex characteristics of future intelligentized warfare.

Therefore, in empowering joint operations planning with intelligentization, we cannot be satisfied merely with the "human-led, machine-assisted" decision-making mode in which human capability and machine capability are simply superimposed. Instead, we must pursue deep integration of human creative thinking and machine computational thinking, striving to realize a new decision-making mode of "human-machine integration, mutually complementary." Under the dominance of this mode, humans are responsible for determining operational objectives, formulating strategic plans, grasping the direction of war, and making final decisions; machines must understand human decision-making intent at a higher dimension and carry it through into processing data, generating plans, simulating deductions, and assessing effects—thereby both better leveraging the speed and precision advantages of machines and maximally unleashing the creativity and flexibility advantages of humans, achieving a multiplying effect of "1+1>2."

Reshaping the intelligentized decision-making mode for joint operations planning requires simultaneous effort on two fronts: personnel cultivation and technology research and development. In personnel cultivation, vigorous efforts must be made to develop composite military planning personnel who understand both military affairs and technology, to enhance the digital literacy and intelligent literacy (智能素养) of operational planning personnel at all levels, enabling them to skillfully employ intelligent planning tools, understand the logic and limitations of algorithms, and achieve efficient coordination with intelligent systems. In technology research and development, key breakthroughs must be made in human-machine interaction, knowledge graphs, reinforcement learning, and other critical technologies to enhance the autonomy and adaptability of intelligent systems, enabling them to better understand human intent and adapt to complex and ever-changing battlefield environments. At the same time, a "dual human-machine loop" (人机双回路) planning training mode can be established, treating intelligent systems as an important "partner" in human planning training; through normalized human-machine collaborative training, the degree of tacit coordination in human-machine integration and planning capability can be continuously improved, thereby enhancing the adaptability and decision-making level of joint operations planning in complex battlefield environments.

Deepening System-of-Systems Optimization, Enhancing Overall Intelligentized Effectiveness

The essence of joint operations is the confrontation of system against system. This determines that empowering joint operations planning with intelligentization is not the intelligentization of a single link or single domain, but rather the system-of-systems optimization (体系聚优) of all capabilities across the entire combat system. The effective generation of combat effectiveness depends on deep coordination among all combat elements and all combat systems. In previous joint operations planning, breaking down the information barriers and institutional and mechanistic obstacles among the various services and branches and domains, and achieving integrated employment of combat forces, has always been a goal we have pursued without letup. The development of intelligentized technology provides an excellent means and method for breaking down these barriers and obstacles, making it possible to better construct an intelligentized joint operations planning system that is fully domain-integrated and highly coordinated.

From the perspective of systems theory, the intelligentized joint operations planning system is a complex open system; its overall effectiveness does not come from the "stacking" of its component parts, but rather from the emergent effects produced by the synergistic interaction among the various elements within the system. From this perspective, only by achieving system-of-systems optimization can the advantages of intelligentized planning be fully realized, enabling precise scheduling of combat forces and precise control of combat actions, thereby forming overall combat effectiveness. Otherwise, intelligentized planning will become an "information island" (信息孤岛), unable to be converted into actual combat power. Therefore, the intelligentized joint operations planning system must be deeply bound to combat systems such as the command and control system, the reconnaissance and intelligence system, the fire strike system, and the integrated support system, achieving data interoperability, information sharing, process linkage, and functional complementarity to form an organic whole.

At the practical level, a system-of-systems construction approach can be adhered to in reconstructing the technical system and organizational system of joint operations planning. At the technical level, a unified intelligent cloud platform must be built to provide powerful computing, storage, and algorithm services to planning nodes at all levels; edge computing nodes must be deployed to achieve real-time processing of battlefield data and local decision-making; and a fully domain-interconnected communications network must be constructed to ensure the free flow of information among all planning nodes. At the organizational level, a flattened planning and command structure must be established to reduce command echelons, delegate decision-making authority, and grant frontline planning nodes greater autonomy; modular planning teams must be formed, flexibly organized according to different operational tasks to achieve cross-domain, cross-departmental collaborative planning, striving to achieve "distributed deployment, centralized management and control, networked coordination" (分布式部署、集中式管控、网络化协同)—both fully leveraging the initiative and creativity of each planning node and ensuring unified command and coordination of the entire planning system.

Fortifying the Security Line, Ensuring Reliable Intelligentized Operation

While intelligentization brings enormous effectiveness improvements to joint operations planning, it also brings unprecedented security risks. In the process of empowering joint operations planning with intelligentization, the planning system is highly dependent on data, algorithms, and networks, and faces multi-dimensional, multi-layered security threats. For example, data, as the core resource of intelligentized planning, once stolen, tampered with, or destroyed by the enemy, will cause distortion of the battlefield situation, erroneous decisions, and may even cause the paralysis of the entire combat system. Algorithms, as the core engine of intelligentized planning, carry the risk of having backdoors implanted by the enemy or being subjected to algorithmic deception. Networks are the operational carrier of the intelligentized planning system; cyber attacks are characterized by strong concealment, great destructive power, and rapid propagation speed, and can cause serious damage to the intelligentized planning system in a short period of time.

We must clearly recognize that security and development are two sides of the same coin: development without security is unsustainable, and security without development is stagnation. The higher the degree of intelligentization, the higher the requirements for security, and the greater the risk and hidden danger posed by security vulnerabilities. Only by fortifying the security line can the reliable operation of the intelligentized joint operations planning system be ensured. Therefore, empowering joint operations planning with intelligentization must adhere to the principle of equal emphasis on development and security, integrating security protection throughout the entire process of construction.

Specifically, first, data security protection must be strengthened by establishing and improving a tiered and classified data protection system to ensure the security of data at every link of collection, transmission, storage, and use. Second, algorithm security management must be reinforced by establishing algorithm review and evaluation mechanisms to conduct rigorous review and testing of the security, reliability, and interpretability of algorithms, preventing algorithms from being exploited or attacked by the enemy. Finally, network security protection capability must be enhanced by constructing a network security system of active defense and defense-in-depth, improving the capability to monitor, provide early warning of, and respond to cyber attacks, and strengthening network survivability—thereby avoiding risks amid the intelligentization wave and firmly grasping the initiative on the future battlefield.

Original Chinese
以智能化赋能联合作战筹划 ■杨 斓 引 言 联合作战筹划作为组织运用联合作战力量的中枢,其科学化、精准化、高效化程度,直接决定着战争的胜负走向。当前,随着人工智能技术在军事领域的深度渗透,联合作战筹划正经历从“人为主导、机器辅助”向“人机融合、互为补充”的系统性转变,这对联合作战筹划的底层逻辑、运行方式等产生了重大影响。我们必须深刻把握智能化战争的内在规律,以智能化赋能联合作战筹划,加快构建与未来智能化战争相适应的联合作战筹划能力体系。 夯实数据底座,筑牢智能化数字根基 数据是智能化战争的核心要素,筑牢数据根基是联合作战筹划从“经验驱动”向“数据驱动”转变的必要前提。在传统战争形态下,数据只是辅助指挥员判断战场态势的参考信息。而在智能化战争中,数据已成为作战体系的“血液”和“骨骼”,贯穿于联合作战筹划的全过程:从战场态势感知、作战目标分析、作战力量编组到作战方案生成、作战效果评估,每一个环节都离不开数据的支撑。数据的完整性、准确性、时效性,直接决定了智能化筹划的精度和速度。从这个角度讲,没有高质量的数据支撑,以智能化赋能联合作战筹划就会成为无源之水、无本之木。 从更深层次看,数据是构建战场数字孪生的基础,是实现物理战场与虚拟战场同频共振的桥梁。在智能化技术加持下,我们可以对海量战场数据进行采集、处理和分析,在数字空间构建起与物理战场高度一致的虚拟镜像,实现对战场态势的实时映射、对作战过程的模拟推演和对作战结果的预测预判。这种数字孪生能力,使得联合作战筹划能够突破物理时空的限制,在战前就对各种可能出现的情况进行充分的推演和验证,从而大幅提高筹划的科学性和可行性。同时,数据也是算法训练的“燃料”,只有拥有足够丰富的战场数据,才能不断完善能够适应复杂多变战场环境的智能算法模型。 因此,以智能化赋能联合作战筹划,必须坚持数据先行的建设理念。一是要建立统一的数据标准体系,规范数据的格式、接口和语义,解决多源数据异构性问题,实现不同军兵种、不同领域、不同系统之间数据的互联互通和共享交换。二是要构建全域覆盖、多源融合的数据采集网络,综合运用陆、海、空、天、电、网等各类侦察感知手段,实时获取战场环境、敌方兵力、我方态势等全维度数据,形成覆盖作战全空间、全时域的数据采集能力。三是要加强数据治理能力建设,通过数据清洗、去重、校验、融合等技术手段,提高数据的准确性、一致性和可信度,为智能化赋能联合作战筹划提供持续稳定的数据支撑。 注重人机融合,重塑智能化决策模式 在当前的智能化建设中,人工智能系统已经具备了比较强大的计算能力、存储能力和学习能力,能够快速处理海量数据,生成多种作战方案,成为信息化智能化条件下联合作战筹划不可或缺的重要力量。但将目光投射到更遥远的未来战场,运筹智能化战争,人工智能算法也存在着明显的局限性,它缺乏人类的创造性、想象力和价值判断能力,无法理解战争的政治本质和战略意图,无法应对战争中可能出现的非常规情况和道德困境,难以适应未来智能化战争节奏加快、高度复杂的特点。 因此,以智能化赋能联合作战筹划,我们不能仅仅满足于人类能力与机器能力简单叠加的“人为主导、机器辅助”决策模式,而应追求人的创造性思维与机器的计算性思维的深度融合,力求实现“人机融合、互为补充”的新型决策模式。在这种模式的主导下,人类负责确定作战目标、制定战略规划、把握战争方向、作出最终决策;机器则需要在更高维度上理解人类的决策意志,并将其贯彻到处理数据、生成方案、模拟推演、评估效果等各环节,从而既更好发挥机器的速度和精度优势,又最大程度激发人的创造性和灵活性优势,实现“1+1>2”的倍增效应。 重塑联合作战筹划智能化决策模式,必须从人才培养和技术研发两个方面同时发力。在人才培养方面,要大力培养既懂军事又懂技术的复合型军事筹划人才,提升各级作战筹划人员的数字素养和智能素养,使其能够熟练运用智能筹划工具,理解算法的逻辑和局限,与智能系统达成高效协同。在技术研发方面,要重点突破人机交互、知识图谱、强化学习等关键技术,提升智能系统的自主性和适应性,使其能够更好地理解人的意图,适应复杂多变的战场环境。同时,还可以建立“人机双回路”的筹划训练模式,将智能系统作为人类筹划训练的重要“伙伴”,通过常态化的人机协同训练,不断提升人机融合的默契度和筹划能力,从而提高联合作战筹划在复杂战场环境下的适应能力和决策水平。 深化体系聚优,提升智能化整体效能 联合作战的本质是体系与体系的对抗,这决定了以智能化赋能联合作战筹划不是单一环节、单一领域的智能化,而是整个作战体系各项能力的体系聚优。作战效能的有效发挥依赖于各作战要素、各作战系统之间的深度协同。在以往的联合作战筹划中,打破各军兵种、各领域之间的信息壁垒和体制机制障碍,实现作战力量的一体化运用,一直是我们不懈追求的目标。而智能化技术的发展,为打破这些壁垒和障碍提供了绝佳的手段和方式,使得更好构建全域一体、高度协同的智能化联合作战筹划体系成为可能。 从体系论的角度看,智能化联合作战筹划体系是一个复杂的开放系统,其整体效能并非来自各组成部分的“叠罗汉”,而是来自系统内部各要素之间协同作用产生的涌现效应。从这个角度讲,只有实现了体系聚优,才能充分发挥智能化筹划的优势,实现对作战力量的精准调度和对作战行动的精确控制,从而形成整体作战效能。否则,智能化筹划就会成为 “信息孤岛”,无法转化为实际的战斗力。因此,智能化联合作战筹划体系必须与指挥控制体系、侦察情报体系、火力打击体系、综合保障体系等作战体系深度绑定,实现数据互通、信息共享、流程衔接和功能互补,形成一个有机整体。 在实践层面,可以坚持体系化建设思路,重构联合作战筹划的技术体系和组织体系。在技术层面,要建设统一的智能云平台,为各级筹划节点提供强大的计算、存储和算法服务;要部署边缘计算节点,实现战场数据的实时处理和本地决策;要构建全域互联的通信网络,保障各个筹划节点之间的信息畅通。在组织层面,要建立扁平化的筹划指挥体制,减少指挥层级,下放决策权限,赋予一线筹划节点更大的自主权;要组建模块化的筹划团队,根据不同的作战任务灵活编组,实现跨领域、跨部门的协同筹划,力求做到“分布式部署、集中式管控、网络化协同”,既充分发挥各个筹划节点的主动性和创造性,又要确保整个筹划体系的统一指挥和协调一致。 筑牢安全防线,保障智能化可靠运行 智能化在为联合作战筹划带来巨大效能提升的同时,也带来了前所未有的安全风险。在以智能化赋能联合作战筹划过程中,筹划体系高度依赖于数据、算法和网络,面临着多维度、多层次的安全威胁。例如,数据作为智能化筹划的核心资源,一旦被敌方窃取、篡改或破坏,将会导致战场态势失真、决策失误,甚至造成整个作战体系的瘫痪;算法作为智能化筹划的核心引擎,存在着被敌方植入后门、进行算法欺骗的风险;网络是智能化筹划体系的运行载体,网络攻击具有隐蔽性强、破坏力大、扩散速度快等特点,能够在短时间内对智能化筹划体系造成严重破坏。 我们必须清醒认识到,安全与发展是一体两面的,没有安全的发展是不可持续的,没有发展的安全是停滞不前的。智能化程度越高,对安全的要求就越高,安全漏洞带来的风险隐患也就越大。只有筑牢安全防线,才能确保智能化联合作战筹划体系的可靠运行。因此,以智能化赋能联合作战筹划必须坚持发展与安全并重的原则,把安全防护贯穿于建设的全过程。 具体而言,首先要加强数据安全防护,建立健全数据分级分类保护制度,确保数据在采集、传输、存储、使用等各个环节的安全。其次,要强化算法安全管理,建立算法审查和评估机制,对算法的安全性、可靠性和可解释性进行严格的审查和测试,防止算法被敌方利用或攻击。最后,要提升网络安全防护能力,构建主动防御、纵深防御的网络安全体系,提高对网络攻击的监测、预警和处置能力,强化网络的抗毁性,从而在智能化浪潮中规避风险,牢牢掌握未来战场主动权。