But as these agents gain more access and autonomy, an important question emerges: How do organisations ensure that AI agents do only what they are authorised to do?
Unlike traditional software, AI agents can make decisions based on changing inputs and context. An agent connected to internal applications or sensitive business data may unintentionally expose information, misuse a tool or follow malicious instructions hidden within the content it processes.
This is where Guardian Agents are gaining attention. As highlighted in ET CISO's coverage of AI safety in corporate networks, organisations need stronger ways to monitor autonomous AI and manage the risks that come with it.
- Risk: Helping determine whether an agent should be permitted to access a resource or execute a particular action.
- Supporting investigation: Maintaining useful records of agent activity and security decisions so teams can investigate incidents and understand what happened.
Microsoft's Project Perception is one example of the broader industry effort to use specialised AI capabilities to improve security monitoring and threat response. However, monitoring alone is not enough. Guardian Agents must operate alongside established security controls, with clearly defined permissions and appropriate human oversight.
The Trevonix perspective: Start with identity
At Trevonix, we believe one of the most important questions in AI security is often overlooked: What identity is the agent operating under, and what is it allowed to access?
An AI agent is not just another application feature. When it can retrieve information, invoke APIs or perform actions across enterprise systems, it effectively becomes another identity within the organisation's digital environment.
That identity needs an owner, a defined purpose and permissions that reflect its actual responsibilities.
This is where Identity and Access Management (IAM) becomes particularly relevant. Privileged Access Management (PAM) can help protect elevated access, while Non-Human Identity Security can help organisations manage the service accounts, API credentials and machine identities that AI agents depend on.
The principle of least privilege is equally important. An agent that summarises documents should not automatically have permission to modify records, create new accounts or access unrelated confidential information.
Access should be limited to what the agent needs, and sensitive actions should require stronger controls where appropriate.
Guardian Agents can complement these measures by monitoring activity and helping identify when an agent's behaviour or access requests warrant further scrutiny.
The distinction matters: monitoring helps identify risk, while identity controls determine what an agent is permitted to do in the first place. Enterprises need both.
Moving towards a more secure agentic enterprise
Securing AI agents does not necessarily mean slowing down adoption. It means putting the right controls in place before autonomous systems become deeply embedded in business operations.
Organisations should start by identifying the AI agents operating across their environments, documenting their owners and reviewing the permissions and credentials they use. They should also establish clear policies for sensitive actions, maintain audit trails and determine when human approval is required.
Security teams need to consider how agents interact with other agents, external tools and enterprise applications. A seemingly low-risk agent can create a much larger exposure when it inherits excessive permissions or connects to systems containing sensitive data.
These controls should evolve as agents gain new capabilities and their roles change.
Conclusion
AI agents are creating new opportunities for enterprise automation, but they are also changing how organisations need to think about access, trust and accountability.
Guardian Agents can help provide greater oversight, but they cannot replace sound identity governance, access controls or clear security policies.
At Trevonix, we see identity security as a critical foundation for responsible AI adoption. By combining least privilege, Non-Human Identity Security, PAM and Zero Trust with effective monitoring, organisations can give AI agents the access they need without granting them unnecessary authority.
Ultimately, the objective is not simply to monitor AI agents. It is to ensure that every agent has a clear purpose, operates within defined boundaries and remains accountable for the actions it takes.
Because in an enterprise where AI can act independently, knowing what an agent can do is just as important as knowing what it is designed to do.
Sources
- ET CISO: Ensuring cybersecurity: The crucial role of Guardian Agents for AI safety in corporate networks
- Microsoft Security: Project Perception and AI-powered cybersecurity
