China is moving deliberately to make artificial intelligence a structural advantage for the People’s Liberation Army. Xi Jinping’s 2022 party report signalled the political priority: the PLA must grasp the character of informatized and intelligent warfare and accelerate the development of unmanned, intelligent combat capabilities.
That political direction sits on top of a longer term national strategy. Beijing’s 2017 New Generation Artificial Intelligence Development Plan established explicit national goals for AI through 2025 and 2030, spanning civilian industry, research, and national security. The plan treats AI as a strategic technology and lays out a “1 plus N” architecture of national projects to push China toward leadership in swarm intelligence, autonomous control, and hybrid intelligence.
Those political and policy drivers are translating into concrete military modernization. The U.S. Department of Defense’s 2023 assessment and related briefings describe a PLA that is integrating advanced sensors, machine learning, and faster data fusion across command, control, intelligence, surveillance, reconnaissance, electronic warfare, and strike functions. Beijing has adapted doctrine and exercises to test concepts that rely on enhanced automation and AI-enabled decision support rather than only incremental hardware upgrades.
Two implementation features deserve emphasis. First, military civilian fusion is not a slogan. Chinese authorities are systematically encouraging civilian firms and research institutes to supply dual use AI systems to the PLA and to participate in defense-oriented procurement and testing. Public analyses of PLA procurement patterns show growing activity by nontraditional and civilian vendors alongside state-owned incumbents. That widens the supplier base and shortens the path from commercial innovation to military use.
Second, unmanned and swarming systems have become a testing ground for AI-enabled operations. Open reporting through 2023 and into early 2024 documented Chinese programs and demonstrations that emphasize autonomous coordination, distributed sensing, and resilience to jamming or attrition. Journalistic reporting and military documentaries highlighted experimental ‘‘self-repairing’’ swarm concepts and new cluster or modular drones that can reconfigure in flight or deploy in numbers to saturate defenses. These developments mirror the wider global trend where swarms are seen as a way to shift combat dynamics by trading mass and autonomy for individual platform sophistication.
These strengths are real. China combines a large domestic market for AI, a thriving commercial AI sector, state-directed financing, and mechanisms to marshal civilian science and industry for national security ends. That combination can accelerate deployments and create operational concepts that blur the line between commercial and military capability. It also makes China a laboratory for doctrines that are built around sensor fusion, predictive logistics, and human-machine teaming at scale.
But capability and operational readiness are not the same as seamless integration. Public analysis and reporting through early 2024 also underscore important constraints. First, advanced microelectronics remain a bottleneck for high-end autonomy that can operate at long range and under contested electromagnetic conditions. Second, scaling autonomy from laboratory demonstrations to resilient, fielded systems requires robust software engineering, secure communications, and extensive operational testing under realistic electronic attack and sensor-degraded conditions. Third, organizational and training reforms needed to change command and control habits take time. The PLA has prioritized those reforms, but they are incomplete and uneven across services.
Strategically, China’s AI push changes the contested balances in several ways. On a regional level, lower cost autonomous systems and enhanced ISR reduce the threshold for coercive operations short of large scale force projection. On operational timelines, faster sensing to shooter loops compresses decision windows and raises the premium on AI-aided command support. For alliance networks and export controls, it creates incentives for partners to harden communications, cross-domain redundancy, and coalition data-sharing practices. Finally, it raises proliferation risks as dual use software and swarm tactics diffuse to nonstate and third party actors.
Policy responses should be calibrated and long term. First, Western and regional planners need to accelerate investments in resilient sensor networks, resilient command architectures, and counter-swarm capabilities so that AI-enabled saturation attacks do not become decisive by default. Second, coalition-level norms and transparency measures remain essential. The 2023 diplomatic effort on responsible military AI use signalled appetite for norms, but political consensus on limits and verification is thin and will not substitute for capability. Third, supply chain and export control policies should target chokepoints that enable the most consequential leaps in autonomy while minimizing harm to legitimate civilian commerce and research. Fourth, sustained attention to doctrine, training, and experimentation will be as important as procurement in determining whether AI improves or degrades actual combat performance.
China’s effort is deliberate and well resourced. That does not mean every demonstration will scale or that operational surprises are impossible. But the PLA is placing AI at the center of a multi decade modernization drive that links doctrine, procurement, personnel, and industry policy. Western planners and partners should assume this integration will continue to accelerate and design deterrence and resilience measures that anticipate, rather than simply react to, the shape of AI assisted conflict.
If the strategic lesson of recent years holds, technology alone does not determine outcomes. Doctrine, logistics, training, and human judgment still matter. The PLA is betting that AI can reshape those domains in its favour. The choice for others is whether to meet that bet with coherent policy, interoperable capability, and resilient institutions that preserve decision advantage under pressure.