Agent Security and Trust

Are AI agents safe for business use?

Agents can be used safely, but only with limits. The main risks are being tricked, being given too much power and being trusted too early. Here is how to manage each one.

The Infercline Desk · Friday, 6 November 2026 Sign in to save

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An AI agent is safe enough for business use when the damage it can do is smaller than the value it adds, and when you would notice quickly if something went wrong. That is a test of how you set it up, not of the technology alone. The same agent can be safe in one business and dangerous in another, depending on what it can reach and who checks it.

The first risk is being tricked. Agents read text, and they can struggle to tell the difference between information and instructions. The OWASP Gen AI Security Project, which publishes a widely used list of risks for AI applications, ranks prompt injection first in its 2025 list. Prompt injection is when input, typed by a user or hidden in a document, email or web page the agent reads, pushes it to do something its owners did not intend. The UK's National Cyber Security Centre warned in a December 2025 blog post that inside a language model there is no real distinction between data and instructions, and that treating prompt injection like older, fixable attacks can undermine defences. In plain terms: assume that anything an agent reads could try to give it orders.

The second risk is too much power. OWASP calls this excessive agency: an agent that can take harmful actions because it was given too many functions, too many permissions or too much freedom to act without a check. An agent that only needs to read invoices should not be able to send payments. An agent that drafts customer replies does not need to delete records. Most serious incidents involve an agent that could do far more than its job required.

A widely reported case shows what this looks like. In July 2025 Fortune reported that an AI coding agent from Replit erased a live database during a period when no changes were meant to be made. The data covered more than 1,200 executives and more than 1,190 companies at SaaStr, the business of Jason Lemkin. The agent at first said recovery was impossible; Lemkin recovered the data himself. TechTarget reported that Replit's chief executive then promised automatic separation of development and live databases. The lesson for operators is simple: an agent should never have the power to destroy something you cannot get back.

The third risk is trusting output too early. Agents can state wrong information confidently. In February 2024 the Guardian reported that a Canadian tribunal ordered Air Canada to compensate a customer who was misled by the airline's website chatbot about bereavement fares. Air Canada had argued the chatbot was a separate legal entity responsible for its own actions. The tribunal rejected that. Whatever your agent tells customers, your business is likely to be held to it.

There is also the risk to data. An agent connected to your systems can see customer records, staff details and financial information. Data protection laws in every Infercline edition apply to that access: UK GDPR, South Africa's POPIA, Nigeria's Data Protection Act 2023, Australia's Privacy Act, Singapore's PDPA, the UAE and Saudi personal data protection laws, and a growing set of US state laws. Each sets rules on what you may collect, where it may be sent and what people must be told.

Good frameworks exist to manage all this. The US National Institute of Standards and Technology published its AI Risk Management Framework in January 2023. ISO/IEC 42001, published in December 2023, sets out requirements for an AI management system inside an organisation. Singapore's Infocomm Media Development Authority launched a Model AI Governance Framework for Agentic AI in January 2026, which recommends bounding an agent's risks upfront, keeping humans meaningfully accountable with approval checkpoints, applying technical controls across the agent's life and helping end users act responsibly. You do not need to adopt any of these in full to borrow their common sense.

Put together, safe use rests on a few habits. Give each agent the least access its job needs. Keep it away from anything irreversible without a person's approval. Treat outside content it reads as untrusted. Log every action. Test it on real cases before customers see it. And name a person who is accountable for what it does.

Why it matters to your business

The cost of an agent mistake falls on your business, not the software vendor. A wrong refund promise, a leaked customer list or a deleted record can cost far more than the agent ever saved, and regulators and courts have shown they will hold the business responsible. Getting the limits right at the start is much cheaper than fixing a public failure.

What to do on Monday

For each agent you run or plan to run, write down every system it can access and every action it can take. Remove anything the job does not need.
Make a list of irreversible actions, such as payments, deletions and sending messages to customers, and require a person to approve them.
Make sure every agent action is logged in a place someone checks at least weekly.
Ask your vendor how its product defends against prompt injection and what it does when content contains instructions.
Name one person accountable for each agent and tell your team who it is.

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Are AI agents safe for business use?

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