Cybersecurity has entered an era in which the distinction between an external attack and an internal compromise is becoming increasingly difficult to maintain. For years, organizations built security programs around a relatively straightforward model: defend the perimeter, protect the network, secure endpoints, educate employees, and respond when an attacker gets through. That model was already under pressure from cloud computing, remote work, mobile devices, software supply chains, and the Internet of Things. Artificial intelligence is now accelerating that transformation and changing the economics of both offense and defense.

The emerging threat is not simply an AI-powered hacker breaking through a firewall. It is a much more complicated ecosystem in which artificial intelligence can observe, personalize, automate, and accelerate attacks against identities, employees, applications, vendors, and business processes. An employee has a certain level of authority. An application has another. An autonomous AI agent could potentially combine access to multiple systems and perform a sequence of actions much faster than a human. An AI assistant that can read a database is one thing. An AI agent that can read the database, modify records, send emails, access financial systems, communicate with external services, and initiate transactions is entirely different.

The principle of least privilege therefore needs to extend to machines. AI agents should have only the permissions necessary to perform their assigned functions. Sensitive information should be segmented. High-impact actions should require appropriate human approval. Agent activity should be logged and monitored, and organizations should maintain the ability to revoke access quickly.