The authors of this slim volume set themselves a formidable task: rendering artificial intelligence comprehensible to peacebuilders while the technology evolves beneath their keyboards. Panic and Arthur deserve measured praise for translating machine learning, natural language processing, and computer vision through concrete applications such as VIEWS conflict prediction, Google Jigsaw's Perspective API, and satellite imagery analysis. At the same time,  their sensitivity to data colonialism demonstrates awareness of power dynamics. Yet, it is striking that a book completed in late 2023 anchors itself in task-specific architectures (fine-tuned classifiers, supervised models) even while discussing GPT-3/4 risks. This is not oversight but reveals the genre's inherent challenge: grounding analysis in principles that outlast specific technology; a challenge made acute by 2025's agentic AI systems that render even their forward-looking sections, artifacts of their moment. One would presume that recognizing colonial dynamics would yield frameworks for community-controlled governance, but these remain gestural. The book maps territory while leaving critical frontiers unexplored: culturally sensitive AI agents, validation under political volatility, data sovereignty mechanisms; all natural extensions that receive light treatment. Other reviewers of the book have noted that prediction capabilities are racing ahead of prevention mechanisms; this disconnect exposes a field limitation. Fortunately, the authors define peace positively as social trust and institutional resilience; unfortunately, operational examples gravitate toward conflict prediction, reflecting available tools rather than conceptual ambition. The forthcoming deployment of these technologies in active conflicts will test whether implementation frameworks can prioritize responsibility over capability while positioning communities as architects rather than data sources. This is a challenge this accessible introduction helps frame without resolving, demanding scholarly follow-up that ensures technical innovation submits to community sovereignty rather than extractive prediction.