As more businesses deploy AI agents to handle internal tasks, customer operations and software workflows, security teams are being warned about a practical problem: an agent may operate with legitimate credentials while still taking actions beyond what the organisation intended. The issue is not necessarily a traditional account compromise, but a control gap between having access and using that access appropriately.

The source article reports on guidance from Token Security, which argues that organisations need agent-specific security policies so that AI systems can be limited to clearly defined actions without removing their usefulness. The warning is especially relevant for companies connecting AI agents to SaaS platforms, internal tools, cloud environments and business data.

What happened

According to the report, AI agents can use valid credentials to perform actions outside their assigned scope. That means standard identity and access management controls may not always be enough if an agent is technically authorised to reach a system but is not sufficiently restricted in what it should do once inside.

The article cites Token Security's position that organisations should apply policies designed specifically for AI agents. The aim is to preserve automation benefits while preventing agents from carrying out unintended or excessive actions across connected systems.

This is not the same as a conventional external breach. Instead, it reflects a newer security challenge created by autonomous or semi-autonomous software acting on behalf of a user, a team or a business process.

Why it matters for European businesses

Many European SMEs and digital teams are experimenting with AI agents for support, sales operations, reporting, internal administration, software development and marketing tasks. In practice, these agents are often linked to email, CRM systems, e-commerce tools, cloud storage, ticketing platforms and finance software.

If an agent has broad permissions, the business risk can include unauthorised changes, unintended data exposure, excessive automation actions or operational errors that are difficult to trace. Because the credentials may be valid, these incidents may not be blocked by traditional perimeter security controls.

For European organisations, the issue also connects to broader governance and compliance concerns. Where AI agents can access personal data, customer records or sensitive internal systems, companies may need stronger oversight, logging and approval processes. This is particularly important in regulated sectors and in businesses that must demonstrate accountable handling of data and system access.

The story is also relevant because AI adoption is moving from simple chat interfaces to operational automation. As soon as an AI system can take action inside business software, identity security becomes a core part of AI risk management.

Who may be affected

• SMEs adopting AI automation for routine operations, internal support or workflow execution
• IT and security teams managing identity, SaaS permissions and cloud access
• E-commerce businesses using AI agents for product updates, order handling or customer service workflows
• Marketing teams connecting AI tools to CRM, analytics, content systems or campaign platforms
• Regulated businesses where auditability, access restrictions and data handling controls are critical

What companies should consider

• Review where AI agents have action-taking permissions across CRM, ERP, email, cloud, support and e-commerce systems
• Apply least-privilege access so agents only receive the minimum permissions needed for a defined task
• Separate agent identities from human identities to improve visibility, control and audit trails
• Define task-level policies where possible, not just system-level access, so agents are restricted in what actions they can perform
• Require approvals for higher-risk actions such as payment changes, user administration, bulk exports or deletion of records
• Monitor logs and anomalies to detect unusual agent behaviour, excessive requests or actions outside expected workflows
• Assess AI-connected SaaS tools as part of security reviews, especially when third-party services receive broad API access

For businesses moving from AI experimentation to real operational use, the main lesson is clear: giving an AI agent valid access is not enough on its own. Companies also need controls that define what the agent is allowed to do, how its actions are monitored and where human oversight remains necessary.