Artificial Intelligence in Production: Practical Engineering Beyond Theory

This monograph addresses the engineering challenges of deploying and operating AI systems in real-world environments. It focuses on data infrastructure for production AI, model deployment constraints, reliability and observability, human–AI interaction, scaling AI in enterprise settings, security and robustness, and economic impact. The book shifts the emphasis from model-centric thinking to system-oriented design, offering actionable frameworks for building resilient, maintainable, and cost-effective industrial AI systems.