About this book:

*Case Studies in Autonomous Operations* provides a comprehensive analysis of the real-world performance of artificial intelligence and autonomous systems in modern military conflicts. Moving beyond theoretical hype, the book examines the practical successes and failures of technologies such as drone swarms, loitering munitions, and undersea UUVs. Through a series of detailed case studies, the text illustrates how environmental harshness, adversarial interference, and organizational friction test the limits of AI, emphasizing that mission success often depends more on resilient data architectures and human-machine teaming than on individual algorithms.

The book explores the technical challenges inherent in deploying AI at the "tactical edge," particularly in contested environments where communications and GPS are denied. It details the critical importance of "Edge AI" for intelligence processing, the necessity of autonomous navigation when "comms go dark," and the persistent threat of adversarial deception, including jamming and spoofing. Chapters on target recognition in urban settings and the acceleration of the "kill chain" highlight the risks of automation bias and the potential for catastrophic false positives, underscoring the need for "Explainable AI" and robust human oversight to maintain ethical and legal standards.

Furthermore, the text addresses the logistical and strategic infrastructure required to sustain autonomous warfare. It covers the "sim-to-real gap" in AI training, the complexities of predictive maintenance for large-scale robot fleets, and the hurdles of data-sharing within international coalitions. By examining "counter-autonomy" tactics like digital decoys and deepfake information operations, the author demonstrates that the battlefield is increasingly a contest of algorithmic wits. The book concludes by advocating for rigorous wargaming and "red teaming" to expose system vulnerabilities, ensuring that autonomous operations are integrated into military doctrine responsibly and effectively.

What You'll Find Inside:

• The critical balance between autonomous capabilities and human oversight in military operations
• Challenges of deploying AI systems in electromagnetically contested environments with jamming and spoofing
• The importance of data quality, diverse training sets, and bridging the sim-to-real gap for reliable AI performance
• Ethical and legal considerations for autonomous weapons systems, including rules of engagement and accountability
• Applications across domains (air, land, sea, space, cyber) with specific systems like swarms, loitering munitions, and UUVs

Who's It For:

The book is written for military practitioners - commanders, operators, engineers, analysts, acquisition professionals, and policymakers who must make consequential decisions about AI-enabled autonomous systems under uncertainty. It provides real-world case studies to help these professionals understand what works, what fails, and why in modern military operations involving autonomous systems.