AI’s role in modern warfare has been transformed. It shifts focus from physical force to information dominance and rapid processing. By analyzing vast data, AI empowers commanders with real-time operational awareness for optimal decision-making. The study investigates AI’s application in the Ramadan War, proposing strategies for Iran to counter the US-Israel axis in this domain.
AI’s applications include autonomous systems, satellite imagery analysis, air defense optimization, logistics, and strategic decision support.
Six Operational Layers of AI in Warfare:
- ISR and Sensor Fusion
- Targeting, Target Generation, and Fire Cycle
- Command, Control, and Decision-Making
- Autonomous and Semi-Autonomous Systems
- Cognitive Operations, Deception, and Authenticity Crisis
- War Learning Cycle and Continuous Improvement
Strategic Implications for Iran Against the US and Israel Axis:
- Shifting Deterrence: Iran’s deterrence must evolve from hard power to rapid, AI-driven decision-making, prioritizing data governance, tool integration, and testable criteria.
- Risk of “Scalable Pressure” in Targeting and High-Density Attacks: Iran needs a data-driven, resilient defense architecture to counter increased targeting speed and operational density enabled by AI, avoiding information overload.
- Threat of “Generative Cognitive Operations” and Trust Instability: Iran must recognize and counter the threat of AI-driven fake news, which can create persistent ambiguity and erode public trust, impacting social cohesion and governance.
Proposed Executive Actions:
Based on AI’s operational advantages (reaction speed, data fusion, pattern recognition, scalability) and a cautionary approach against technological illusion, the following priority actions are recommended for effective AI governance in wartime:
- Establish a “Unified AI Governance Headquarters in War”: This HQ should produce: prioritized AI functional maps for defense, air defense, and media; common data standards and integrated system architectures.
- Launch a “Data Operations and Machine Vision Center for ISR and Warning”: This center’s mission is rapid fusion and analysis of visual, video, and signal data, pattern recognition for early threat warning, and generating a common operational picture for command. (Responsibility: General Staff of the Armed Forces).
- Develop and Implement an “Evaluation and Assurance Framework for Defensive AI Systems”: No AI-based defense system should be deployed without rigorous testing due to issues like ability to be explained, training data sensitivity, and model vulnerabilities.
- Create an “AI-Based Cognitive Defense and Network Analysis Program”: This program aims to identify coordinated waves, fake accounts, and dissemination patterns during crises using network analysis, multi-platform monitoring, and open-source data.
This study is conducted at Mtod Institute in 2026.
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