Autonomous artificial intelligence agents and AI models themselves are no longer part of isolated experiments but are now integrated into the core business processes of enterprises. They connect to databases, business applications, cloud platforms, internal APIs, and third-party services, bringing real value to the business.
However, this creates a serious security problem: what happens if an AI system gains access to more organizational information than it needs? The risk is not that the model will give an incorrect answer, but that the application, agent, or connected AI tool could be compromised, manipulated, or misconfigured, using its access to reach confidential systems, disclose data, or initiate unintended actions.
As AI becomes more autonomous and capable, companies must consider not only the functionality of the models but also the places they can connect to.
How AI Agents Become Privileged Corporate Applications
Many companies use AI services that interact with critical infrastructure and sensitive information. These systems are capable of extracting customer records, querying financial databases, generating software code, initiating workflows, and calling external services. In essence, this makes them another class of privileged applications.
Unlike traditional applications, which have clearly defined network requirements, clear ownership, and approval processes, AI environments are evolving much faster. New tools, plugins, and integrations appear within days, often without a full understanding of the connectivity they require. The consequence is overly broad access, unrestricted outbound communication, and unnecessary exposure between AI workloads and sensitive business systems.
If an AI agent is compromised—whether through prompt injection, malicious content, or a vulnerable third-party integration—the extent of the damage is determined by this excessive level of connectivity. The problem is not that the model went outside the network; the problem is that it was initially granted access to systems it should never have been able to reach.
Controlling Risks Through Connectivity Management
A secure AI strategy requires implementing connectivity management: there must be a clear understanding of all systems that the AI workload can communicate with, including internal applications, databases, cloud services, development platforms, and third-party APIs. Each such connection must be verified against a simple question: is it necessary? — and limited to its intended business purpose.
This implies that security and infrastructure teams must map AI application dependencies, assess the risk of each proposed connection, and ensure the principle of least privilege is applied. Instead of allowing an AI service to access the entire internal network and the internet in general, organizations can restrict it only to the specific applications, services, ports, and endpoints it needs. If the workload behaves unexpectedly or is compromised, the damage remains localized.
Securing Connections with Third Parties
The danger is not that an AI agent might encounter malicious instructions through a third-party source or plugin. The danger is that these instructions could reach an agent that has already been provided with powerful tools, credentials, and access to corporate systems.
The Open Worldwide Application Security Project (OWASP) classifies 'excessive agency' as one of the main risks in applications built on large language models, linking it to three primary causes: unnecessary functionality, unnecessary permissions, and unnecessary autonomy.
Most AI implementations rely on external providers of models, Software as a Service platforms, plugins, data sources, and APIs. These dependencies provide functionality but also expand the attack surface.
Protecting the model itself is not enough. Organizations must manage the entire environment around it—its identity, permissions, tools, APIs, applications, and network connections. The AI agent should only be able to access what is necessary to perform its job, and security teams must be able to see, justify, and continuously re-verify every such connection. AI changes the way applications work, but it does not change the principle of least privilege; it only increases the cost of ignoring this principle.