About this book:

*Economics of AI Militarization* examines the transition of artificial intelligence from laboratory research to a core requirement for modern national defense. The book frames the "defense–AI economy" as a complex stack—comprised of sensors, data pipelines, semiconductors, and software—where traditional procurement models often fail to account for rapid iteration and high life-cycle costs. It argues that sustainable advantage is not achieved through "cheap" autonomy, but through disciplined investments in an industrial base that prioritizes modular open systems, data rights, and secure compute infrastructure to avoid the economic traps of vendor lock-in and "pilot purgatory."

The text details the specific cost drivers of militarized AI, emphasizing that data curation, talent recruitment, and continuous testing (TEVV) are primary budget items rather than secondary considerations. By applying economic principles such as "real options" and scenario planning, the author suggests that defense leaders can manage the inherent uncertainty of R&D. The book also highlights the "hidden costs of quality," noting that inadequate investments in cybersecurity and model security can lead to catastrophic operational failures that far outweigh initial savings. Procurement strategies like Other Transaction Authorities (OTAs) and agile acquisition are presented as essential tools for bridging the "valley of death" between experimental prototypes and programs of record.

Beyond domestic policy, the book explores the geopolitical and ethical dimensions of AI, including the impact of export controls, international alliances, and the political economy of "killer robots." It posits that deterrence in the AI era relies on projecting technological superiority while maintaining "explainable" systems to prevent unintended escalation. The author advocates for a "responsible AI" framework, where legal and ethical compliance is engineered into the system design to maintain social license and international legitimacy.

The book concludes with a pragmatic "playbook" for defense decision-makers. This strategy centers on prioritizing mission-driven use cases over technological fads, cultivating a diverse industrial base of non-traditional vendors, and treating human capital as a strategic asset. By shifting from a hardware-centric "buy once" mentality to a software-centric "continuous sustainment" model, the book argues that nations can convert AI from a source of escalating budgetary complexity into a resilient, cost-effective engine of national security.

What You'll Find Inside:

• The AI stack—semiconductors, sensors, data, compute, and software—creates distinct cost drivers and bottlenecks that must be understood to avoid wasteful investment.
• Procurement must evolve from rigid PPBE cycles to agile, modular, outcome‑based models (OTAs, MOSA) that align payments with mission value and prevent vendor lock‑in.
• Data rights, governance, continuous retraining, TEVV, and cybersecurity dominate long‑term lifecycle costs and determine the strategic value of AI systems.
• Talent pipelines, red‑team resilience, and flexible budgeting that treats R&D as real options are critical for maintaining adaptability in uncertain threat environments.
• Sustainable advantage stems from tying AI to clear mission needs, fostering a competitive industrial base, and embedding ethical, legal, and interoperability considerations from the outset.

Who's It For:

This book is designed for defense acquisition officials, program managers, military planners, budget analysts, and policymakers responsible for AI strategy and procurement. It also serves industry partners, academic researchers, and innovation ecosystem actors who need to understand the economic realities, incentives, and risk‑management frameworks that shape militarized AI development and sustainment.