Smarter Defenses, Same Good Judgment: How AI Can Help Protect Your Business

Screening Email Before Anyone Clicks

AI-written messages no longer carry the typos and clumsy phrasing people learned to watch for. AI-powered email filtering tools look past the wording. They study sender behavior, look-alike web addresses, risky links, and requests that break normal patterns, then quarantine or label suspicious messages before an employee ever sees them.

Try this: Ask your team to keep track of every suspicious email they receive for one week. The results may surprise you. That tally will show you what’s slipping through today.

Double-Checking Payment and Invoice Changes

A common scheme: a “vendor” emails new bank details right before a payment is due. The message looks routine, and when invoices arrive by the dozen, one small change is easy to miss.

This is where AI tools earn their keep. Invoice and payment review tools can read incoming invoices, pull out the key details, and compare them against your past history. They flag a changed account number, an unusual amount, a brand-new payee, or a request that doesn’t match your normal pattern. Some can also match invoices to purchase orders automatically, so your team reviews the exceptions instead of checking every line by hand.

A flag only helps if someone acts on it, so pair the tool with a few simple habits. Verify any payment change in person or by calling a number you already have on file, never one listed in the email. Requiring a second person to approve electronic payments, often called dual control, adds another layer. So does positive pay, a common bank service that compares checks presented for payment against the list of checks you actually issued.

See for yourself: If a longtime vendor emailed new payment instructions this afternoon, who on your team would pick up the phone before any money moved?

Spotting Logins That Don’t Look Right

Account takeover often starts with one stolen password. AI-driven identity and access monitoring learns what normal looks like for each user, including usual locations, devices, and hours, then flags a 3 a.m. login from another country or a sudden new email forwarding rule. Paired with multi-factor authentication (MFA) and a password manager, these tools make a stolen password far less useful.

One rule worth repeating to every employee: Legitimate businesses, including your bank, won’t call or email asking for your password or a one-time code. If someone does, contact them using a number you already have.

Make it a habit: Confirm MFA is turned on for every account that touches money or customer data, not just the ones that were easy to set up.

Keeping Devices and Software Protected

Ransomware, malicious software that locks your files until you pay, remains one of the most disruptive threats to smaller firms, and unpatched software has become a common way in. AI-driven endpoint protection watches how programs behave instead of waiting for a known virus, so it can stop warning signs like mass file encryption early. Automated patching and vulnerability prioritization tools help a busy team decide which updates matter most.

Spot-check it: Pick three company devices at random and see when each last installed an update.

Preparing Your Team for AI-Powered Scams

Deepfakes, AI-generated voice or video that imitates a real person, have turned “the owner called and told me to send the payment” into a real risk. AI-assisted security awareness training tools can run realistic phishing simulations and tailor short lessons to the mistakes each person actually makes. General AI writing tools can help with materials, too, as long as no sensitive details go in.

If you haven’t heard of phishing, it is a scam where criminals send emails or messages that look legitimate to trick someone into clicking a link, opening an attachment, or sharing a password.

Example prompt: “Draft a one-page reminder for our staff on how to spot phishing emails and what to do if they suspect one. Keep it friendly and under 300 words.”

Talk it over: Agree on a call-back step or code word your team uses before acting on any urgent money request made by phone or video.

Using AI Without Creating New Risks

Many teams already use AI tools, sometimes without a plan. Free public chatbots are great for drafting, but they aren’t the place for customer records, employee details, or account information.

Before adopting any AI tool, ask the vendor: Where is our data stored? Is it used to train your models? Is it encrypted? Who can access it, and is there an audit log? Will you put that in a written agreement? Then write a short policy listing approved tools and the information that never goes into them.

Set internal guardrails to limit what AI can access. AI should be configured to operate under a human-in-the-loop model, which means a person approves the action before the AI executes on behalf of an individual or the organization. This includes activities such as accessing confidential data, modifying records, sending communications, initiating transactions, or making system changes. Requiring explicit permission helps prevent unintended actions, reduces the risk of unauthorized access, and ensures accountability for decisions made using AI-powered tools.

Example prompt: “Create a simple one-page AI acceptable use policy for a 20-person business. Include approved uses, types of information employees should never enter, and who to ask with questions.”

Take inventory: Ask your team which AI tools they already use. The list may be bigger than you think.

A Few Words Before You Begin

Choose a single job with a predictable, repeatable pattern, like screening email or checking payment changes, and begin there. Watch what the tool catches and what it misses, get comfortable, and then decide what comes next.

This article was written by Adam Emberton, our Technical Program Lead – AI, Automation and Data