AI Failure and Human Guardrails

These sources analyze the integration of artificial intelligence into military and industrial decision-making, with a specific focus on operational logistics and scheduling. While AI-driven systems offer superhuman speed in processing data and managing complex workflows, they face significant hurdles like automation bias, data scarcity, and myopic reasoning. Research highlights that Large Language Models (LLMs) often struggle with long-context utilization and procedural logic, necessitating hybrid frameworks that combine strategic human reflection with algorithmic execution. In the private sector, predictive analytics and smart scheduling are increasingly used to minimize operational bottlenecks and labor costs, outperforming traditional manual methods. Ultimately, the authors emphasize that while technology enhances situational awareness, responsible deployment requires continuous certification and the preservation of human judgment for high-stakes environments.