The People’s Liberation Army (PLA) is rapidly advancing the integration of generative artificial intelligence (AI) technologies into its military intelligence operations, aiming to boost operational efficiency, accuracy, and decision-making capability across the force.
Drawing on both domestic and foreign technological advances, the PLA and China’s defense industry are actively adapting and engineering large language models (LLMs) to address the specialized requirements of military intelligence a sector where the speed, scale, and quality of information processing are of strategic importance.
Generative AI Tools Advance Chinese Military Analysis
Recent analyses of PLA media, patent filings, and academic research indicate that generative AI tools are being deployed to process and analyze vast volumes of intelligence data, generate actionable intelligence products, automate response generation, facilitate early warning systems, and provide tailored recommendations for field commanders.
The PLA’s drive towards intelligentization is evidenced by its adoption of LLMs such as DeepSeek, with indications that proprietary and open-source models from both domestic sources (including Tsinghua University and Alibaba Cloud) and Western developers (Meta, OpenAI, BigScience) are being leveraged and specialized for defense applications.
Patent filings from late 2024 demonstrate that PLA-affiliated institutes are prioritizing the fusion of diverse intelligence sources including OSINT, HUMINT, SIGINT, GEOINT, and TECHINT to comprehensively train military LLMs capable of supporting every phase of the intelligence cycle.
While the PLA recognizes the transformative potential of AI in intelligence improving everything from data integration and battlefield situational awareness to strategic planning and simulation training Chinese defense scholars and official military publications cautiously note the inherent limitations and risks of generative AI in this context.
Balancing Opportunities
Issues such as hallucinations in LLM outputs, lack of relevant corpora, data reliability, value bias, and the ‘black box’ nature of advanced AI models are viewed as potential pitfalls that could distort or degrade intelligence analysis.
Moreover, there are concerns that over-reliance on ideologically aligned or biased models could erode the objectivity vital to high-quality military intelligence. Importantly, the integration of generative AI is seen as a double-edged sword.
The PLA Daily and affiliated researchers acknowledge that adversarial actors could use similar AI tools to produce highly convincing deepfakes and disinformation, complicating open-source intelligence gathering and raising the stakes in the information domain.
PLA analysts are also closely monitoring US military efforts to operationalize generative AI, seeking to learn from American best practices and technological safeguards, especially in areas like OSINT and command and control systems.
To mitigate risks, PLA researchers advocate for iterative, hybrid workflows that combine human and AI analysis, combined with robust validation and traceability mechanisms for AI-generated outputs.
According to Insikt Group Report, these efforts are complemented by calls for the incremental introduction of generative AI in intelligence, continuous assessment of its operational effectiveness, and the parallel development of specialized military corpora to improve model performance and reliability.
In summary, the PLA’s commitment to integrating generative AI into its intelligence apparatus is redefining Chinese military information operations.
The force is positioning itself at the forefront of the global AI-driven intelligence revolution, but it remains keenly aware of the need to balance technological ambition with stringent operational security and analytic rigor.
The coming years will reveal whether the PLA’s sophisticated approach to AI-enabled intelligence delivers the anticipated qualitative edge while avoiding the strategic vulnerabilities that rapid innovation can bring.
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