US INDO-PACIFIC COMMAND
Beyond defensive architecture, INDOPACOM is integrating AI and machine learning into cyber defence strategies. These technologies analyse vast amounts of network traffic in realtime to detect anomalies and identify sophisticated threats that might evade traditional signature-based defences. The goal is to enable responses at machine speed, crucial for staying ahead of cyber threats.
The focus on cyber resilience – the ability of systems to withstand attacks, continue essential functions and recover quickly – has become a cornerstone of INDOPACOM’ s approach. This involves integrating cybersecurity into mission assurance planning, hardening critical systems and developing rapid recovery capabilities.
AI systems enhance INDOPACOM decision-making capabilities In an environment as data-saturated as the Indo-Pacific, processing information and making decisions faster than adversaries has become a strategic imperative. INDOPACOM Commander Admiral Samuel Paparo has stated that future conflicts will be won by those who can“ see, understand, decide and act faster” – a recognition that has placed AI at the centre of the command’ s technology strategy.
This approach aligns with the Department of Defense’ s 2023 Data, Analytics and AI Adoption Strategy, which prioritises accelerating AI adoption to achieve“ enduring decision advantage”. The strategy balances technological advancement with ethical considerations, emphasising responsible AI development and deployment.
AI applications within INDOPACOM span multiple operational domains. Intelligence analysis has been transformed through algorithms that sift through massive data streams from diverse sensors – satellites, drones, unmanned surface vessels, underwater vehicles and traditional platforms – identifying patterns and flagging potential threats in near realtime. Techniques like algorithm fusion and sensor-data fusion help reconcile potentially conflicting information from multiple sources to generate more comprehensive operational pictures.
Companies like Ultra Intelligence & Communications have deployed systems such as ADSI RAIN™ to help intelligence analysts identify difficultto-detect activities. The system uses machine learning models to nominate events of interest within seconds, allowing human analysts to focus their expertise on verification and decisionmaking rather than raw data processing.
Decision support tools represent another growth area. The Defense Innovation Unit’ s Thunderforge programme uses AI agents and large language models for wargaming, simulating scenarios, and refining courses of action for commanders at INDOPACOM and European Command. Similarly, the Defense Information Systems Agency has experimentally deployed a generative AI chatbot on classified networks within INDOPACOM
www. pacom. mil 11