AI agents can do more than write emails or summarize documents. They can access files, update customer records, communicate with vendors, manage schedules, and trigger actions across connected business platforms.
That creates efficiency, but it also creates a security problem. An AI agent may be given access similar to an employee without the same judgment, accountability, or ability to recognize when something feels wrong.
The solution is not to avoid AI. It is to limit what the agent can access, keep people involved in important decisions, and prepare for the possibility that the technology may fail or behave unexpectedly.
Why can AI agents create more risk than regular AI tools?
A regular AI assistant typically provides an answer for a person to review. An AI agent may be able to take the next step by itself.
For example, an agent could read an email, retrieve a customer record, prepare a response, and send it without waiting for an employee. It may also update files, schedule appointments, or interact with financial platforms.
The NSA’s April 2026 joint guidance explains that agentic AI introduces risks because it can operate autonomously across interconnected tools and data sources. The guidance highlights excessive privileges, unexpected behavior, increased system complexity, and unclear accountability as major concerns. (NSA)
A mistake is more serious when the AI can act on it. An inaccurate response can be corrected. An inaccurate payment, deleted file, exposed record, or external message may be much harder to reverse.
Businesses may give an AI agent broad permissions because it makes setup easier. An agent connected to an administrator account may be able to reach more information and perform more actions than its job requires.
This can turn one compromised account or manipulated instruction into a much larger incident.
An agent that schedules appointments may need customer names, contact details, and calendar access. It probably does not need employee records, payment information, confidential contracts, or permission to change security settings.
The NSA warns that overprivileged agents can increase the damage caused by a single compromise. It recommends incremental deployment, explicit accountability, ongoing monitoring, and human oversight. (NSA)
The safer approach is to give the agent its own identity and only the permissions needed for one defined task. Start with read-only access when possible. Add permission to change, send, approve, or delete information only when the business has tested and approved the process.
People should remain involved when an action is difficult to reverse, affects another person, or creates a legal, financial, or security consequence.
Human approval should generally be required before an AI agent can:
Send or approve a payment
Change vendor banking information
Delete important records
Change user access or security settings
Send contracts or legally binding messages
Share confidential information externally
Publish statements on behalf of the business
The approval should happen before the action is completed. The reviewer should be able to see what the agent plans to do, which records will be affected, and what information will be shared.
Human review does not remove the value of automation. The agent can still collect information, prepare the work, and recommend an action. A person simply remains responsible for the final decision.
An AI agent should not operate invisibly. The business should be able to see what it accessed, what it attempted, and what it changed.
Activity records should capture the agent’s identity, the systems it used, the actions it attempted, the information it transferred, and the employee who approved any sensitive action.
Alerts should be created for behavior outside the normal process. This may include accessing an unfamiliar system, retrieving unusually large amounts of data, sending an unexpected number of messages, or repeatedly requesting additional permissions.
Monitoring is only useful when someone is responsible for reviewing the alerts. The business should also have a way to pause the agent, remove its access, and investigate its recent activity.
Start by defining the agent’s boundaries before connecting it to business systems.
The business should document:
What task the agent is allowed to complete
What information it can access
What actions it can perform
Which decisions require employee approval
How its activity will be reviewed
How quickly its access can be removed
Data boundaries are especially important. An AI agent should not be allowed to search every email, folder, or customer record simply because the platform supports it.
Separate general business information from sensitive records. Restrict access to only the files, mailboxes, applications, and customer fields required for the task. Credentials, payment information, employee records, and confidential documents should remain outside the agent’s reach unless there is a clear business need and an appropriate control.
NIST recommends managing AI risks across the full lifecycle of a system, including its design, deployment, use, monitoring, and eventual removal. It also recommends ongoing evaluations rather than treating the original approval as the end of the review process. (NIST Publications)
Before depending on an AI agent, review both the vendor and the process the agent will perform.
Ask the vendor how business data is stored, whether it is used to improve AI models, which third parties can access it, and how information can be deleted or exported. Confirm whether permissions can be limited by user, folder, record, or action.
Businesses should also plan for downtime. An AI agent may stop working because of a service outage, expired credentials, a failed integration, or a vendor issue.
A practical continuity plan should identify:
Who takes over when the agent is unavailable
Which tasks can continue manually
How incomplete work will be found
How customer requests will be handled
How the agent can be disconnected safely
How business data can be recovered or exported
Replacing a human task without creating a fallback process can leave the business dependent on a service it does not fully control.
