World War AI by Kai London
Artificial intelligence has become an object of national strategy as well as commercial strategy. Compute, models, data, talent, standards and regulation are all now contested — and enterprises building on AI inherit the consequences. World War AI sets out what that competition consists of and how to make durable technology decisions inside it.
What the book covers
The inputs that matter
Compute, energy, data, model weights and specialist talent — where concentration sits and why it shapes what enterprises can build.
Divergent regulation
How the EU AI Act, sectoral rules and voluntary frameworks such as the NIST AI RMF and ISO/IEC 42001 create different obligations across markets.
Standards as strategy
Why standards-setting is itself a form of competition, and how procurement and architecture choices follow from it.
Security of the AI stack
Model supply chain, weights and artefact integrity, evaluation and red-teaming, and the assurance a board should expect.
Sovereignty and portability
Residency, jurisdiction and exit: designing AI systems that can be moved, replaced or degraded gracefully.
Board-level AI strategy
Reasoning about concentration risk, vendor dependence and regulatory exposure without committing to a single forecast.
The analysis is descriptive and even-handed. It does not take a political side, attribute activity to named states or actors, or present speculation as intelligence.
Who it is for
Boards, CIOs and CTOs, CISOs, heads of AI and data, and strategy and policy teams making multi-year commitments to AI platforms and suppliers.
About the author
Professor Kai London — CISSP, CISM.
An internationally recognised cybersecurity executive, board advisor and Founder & CEO of Quantum AI Systems Security LLC, writing at the convergence of AI, governance and operational resilience. Honorary Professor and Researcher at UCL.