Can AI Take Over on Its Own? A Practical Cybersecurity Answer

By Ken Barrett, Flint Tech Solutions

Conversations about AI and national security can make it sound as though a chatbot might suddenly wake up, decide what it wants, and start taking over systems. That picture misses the practical question businesses should ask: What has this AI system been allowed to access and do?

What gives AI the ability to act?

A chatbot answering a question cannot, by that exchange alone, operate your network. But a company can connect an AI model to email, files, software, or equipment and set it to keep working toward a goal. That creates an AI agent. It may plan steps, use tools, check results, and continue without a person approving every action.

Think of it like giving a capable new employee a task and a set of keys. The task matters, but the keys determine what the employee can actually touch. With an AI agent, those “keys” are accounts, permissions, connected tools, and network access. A broad instruction can lead to many actions the person never spelled out. An agent can also make mistakes or be misled by malicious material it reads. It does not need a human-like desire to do damage.

Permissions matter, but they are not a perfect guarantee: software vulnerabilities and insecure integrations can also expose systems. Responsibility belongs to the people and organizations building, deploying, and operating AI, and safety requires ongoing testing.

Five safeguards for business owners

That is why I take AI security seriously without telling business owners to fear the technology itself. We should use AI to help people work faster and serve customers better. We should also apply the cybersecurity discipline we already know:

1. Give each agent only the access its job requires. Avoid broad administrator privileges and shared accounts.

2. Require a person to approve consequential actions. Start with actions that could affect money, sensitive data, customers, or critical systems.

3. Keep sensitive systems separated. Do not connect an experimental agent directly to production equipment or every company application.

4. Log and review what the agent does. You should be able to see which identity acted, what tool it used, and what changed.

5. Test and limit the workflow. Start with a narrow task, check its results, and expand access only after it proves reliable.

For example, an AI assistant that summarizes maintenance alerts is one thing. Giving it permission to change equipment settings across every customer site is a very different decision. The model may be the same; the risk changes with the authority we give it.

Use AI confidently and responsibly

My view: AI offers enormous opportunity. Our responsibility is to build and use it with clear goals, limited access, accountable people, and checks that match the consequences. We do not need panic. We need good governance and good cybersecurity.

If your organization is considering AI tools or agents, request an AI discovery conversation with Flint Tech Solutions. We can help assess the use case, the data involved, and the right security boundaries before you put it to work.

Further reading

• NIST: Software and AI Agent Identity and Authorization

• NIST: Why Agentic AI Needs a Strong Identity Foundation

• NIST: Securing AI Agent Systems