Infrastructure Management Agents
AI systems manage cloud infrastructure, network configurations, and operational technology, making decisions that affect system availability, security, and performance.
What happens today
Enterprise AI agents increasingly manage critical infrastructure. They scale computing resources, adjust network configurations, deploy software updates, and respond to security incidents. These systems operate with significant autonomy because the speed and complexity of modern infrastructure often exceeds human capacity to manage directly. When an AI agent makes a mistake—taking down a production system, creating a security vulnerability, or causing a data breach—the consequences can be severe and widespread.
Where accountability breaks down
Infrastructure failures often trigger a blame game. The operations team says the AI made an autonomous decision. The AI vendor says the system was configured incorrectly. The security team says they were not consulted. Meanwhile, customers experience outages, data is compromised, and no one takes clear responsibility for preventing the next incident. The complexity of these systems makes it easy for everyone to point fingers elsewhere.
How human-mapped liability would change incentives
Human-mapped liability requires that infrastructure AI systems have designated human owners who are accountable for their behavior. This owner must understand what the system can do, ensure appropriate safeguards are in place, and take responsibility when things go wrong. This creates incentives for proper testing, monitoring, and incident response procedures. It also ensures that someone with authority is paying attention to what these powerful systems are doing.