As India gears up to host the AI Impact Summit in February of 2026, deliberations on defence modernisation through greater “intelligentization” and the enablement of AI warfighting are resonating across foreign militaries and conflict zones. Given India’s primary security challenge lies in confronting intelligentization in the Chinese People’s Liberation Army (PLA), a ready reckoner of what the largest standing force in the world is imbibing and training with, and what their challenges may be, is a must for policymakers and defence specialists alike.
The Chinese military and defence industry operate on the principle of military-civil fusion (MCF). And given that the general-purpose diffusion of AI has occurred rapidly in China’s civilian commercial domain, PLA officers and affiliated research institutes often pool their strengths to make intelligentization a reality. A classic example of this is university-affiliated researchers building “military LLMs” for OSINT and S&T intelligence, using DeepSeek‑based models to ingest multi‑INT (OSINT, HUMINT, SIGINT, GEOINT, TECHINT) and generate finished intelligence, recommendations, and early‑warning assessments for commanders.
Beyond just the use of AI in dogfighting and simulated attack, PLA concepts of “system-of-systems” warfare and “multi‑domain precision warfare” assume large‑scale AI use to integrate ISR and operational data during actual combat. Such autonomy may also be deployed to identify vulnerable nodes in an adversary’s system‑of‑systems, and recommend precision strike packages. Chinese research also highlights AI‑enabled electronic warfare (EW) that uses machine learning to classify complex Radio-Frequency (RF) environments and optimise jamming and deception in real time.
Despite the PLA’s experimental successes, however, there is a gap between demonstrated capabilities and inflated expectations regarding the deployment of military AI. In fact, PLA writings often treat AI as a shortcut to compensate for a lack of combat experience and doctrinal maturity. This may mask deeper “software” problems in training, jointness, and campaign design.
For example, despite having a massive standing army, an article in the PLA Daily assessing the use of ChatGPT in war, argued that in future information-driven intelligent warfare, while personnel on the battlefield will possess robust intelligence-gathering capabilities and near-real-time information perception. ChatGPT can be employed in basic tasks such as data analysis, decision support, and natural language processing. However, when grassroots actors act in a conflict situation, the extent of reliance on LLMs may, in an unchecked manner, supersede norms and training manuals developed in peacetime.
Finally, there is an internal debate on the extent of AI use in the military domain. Popular PLA scholars such as Wang Ronghui, who has previously been associated with the PLA Academy of Armored Forces Engineering, argue that even though “man-machine intelligent collaboration” enhances the efficiency of warfighting, it is humans who possess an advanced degree of initiative, thought and creativity that is needed to win. As the force wrangles with new realities of defence technology, its experimental advances in “intelligentized” warfare are unignorable in the face of an aggressive Chinese foreign and security policy, especially vis-à-vis India.