An AI agent is only useful if it can reach your systems and data - and that is precisely what makes it a security question. Where a chatbot mostly reads, an agent acts: it can send, change and delete. Before you deploy one, you need clear answers on access, data and accountability.
Access: least privilege, always
Give an agent the narrowest access that lets it do its job, and no more. If it chases invoices, it does not need access to payroll. Scope permissions tightly, prefer read-only where you can, and put spend or action limits on anything that touches money. Over-permissioned agents are the most common avoidable risk.
Data: know what leaves the building
If your agent uses a third-party AI service, understand what data is sent, where it is processed, whether it is used for training, and how long it is kept. For regulated or personal data, this is not optional - it is a compliance question. Our questions to ask before buying AI tools is a useful starting checklist.
Accountability: who owns the agent's actions?
An agent acting under your business's name creates obligations under your business's name. You need:
- An audit trail - a full log of every action and its trigger
- A named owner - a person responsible for the agent's behaviour
- Clear boundaries - defined tasks it may and may not perform
Do not forget the human attack surface
Agents can be manipulated through the very inputs they process - a cleverly worded email or document nudging them to act badly. Treat untrusted input with the same caution you would give a suspicious link, and keep approval gates on anything irreversible, as we cover in what happens when an AI agent gets it wrong.
The bottom line
The value of an agent and its risk come from the same place: its ability to act. Managing that safely - access, data, accountability - is a discipline, and the focus of the AI Risk Management and Security course at London School of Business UK. Enquire today.