October brings plenty of fake monsters, but the ones showing up in your inbox are getting harder to recognize.
Artificial intelligence has given businesses useful new tools for writing, analyzing information, improving productivity and automating repetitive work. At the same time, the technology can also make scams look and sound more convincing.
An email can be polished and professional. A message can imitate someone’s normal writing style. A voice recording can sound familiar. Information copied into an AI tool can also create a security or privacy concern employees may not have considered.
The lesson is not that businesses should be afraid of AI. It is that some of the old ways we used to identify scams are becoming less reliable.
A Familiar Voice Does Not Always Prove Who Is Speaking
For years, hearing someone’s voice or seeing them on video provided a certain level of reassurance. AI is changing that.
It is becoming increasingly important not to rely solely on how realistic a message sounds or looks when the request involves something sensitive. Consider a phone call that appears to come from an executive asking an employee to make an urgent payment, or a voice message requesting confidential information.
The most useful question may no longer be, “Does this sound like them?”
Instead, ask, “Does this request follow our normal process?”
Employees should not have to become experts at detecting artificial voices or manipulated media. Good business processes provide a more reliable safeguard.
For example, payment changes might always be confirmed using a known contact method, and large financial transactions might require a second approval. These kinds of procedures continue to work even when impersonation becomes more convincing.
Professional-Looking Emails Can Still Be Phishing
One of the oldest pieces of phishing advice is to look for bad grammar and spelling mistakes. That advice has become much less useful.
Scam emails can now be polished, clear and professional. They may even sound perfectly normal.
That means employees need to evaluate more than the writing. Is the request normal for that person? Is there unusual urgency? Are you being asked to change payment information, provide sensitive information or sign in through an unfamiliar link?
Sometimes the strongest warning sign is not found in the wording. It is found in the context.
Imagine receiving an email that says a vendor recently changed banks and provides new instructions for future payments. The message is perfectly written, the signature looks right and the vendor’s name is correct.
None of those things prove the request is legitimate. The safest approach is still to verify the change independently before sending money.
Employees Need a Way to Verify Sensitive Requests
This is one of the most useful changes businesses can make as AI-powered scams become more convincing.
Instead of relying entirely on people’s ability to “spot the fake,” give them a verification process.
The exact process will vary from business to business, but it might include confirming banking changes verbally with a known contact, requiring a second approval for large payments, reporting unexpected MFA prompts and verifying unusual requests for sensitive information using another communication method.
These rules are useful whether AI is involved or not. Their advantage is that they continue working even as scams become more sophisticated.
AI Creates Another Risk: What Employees Put Into It
There is another side of AI security that has nothing to do with criminals impersonating people. It involves employees using AI themselves.
An employee may discover a tool that saves them 30 minutes of work. They upload a document and ask for a summary, paste in meeting notes and ask it to create an email, or submit a spreadsheet and ask the tool to identify patterns.
That can be incredibly useful. But businesses also need to think about what information is being entered into these tools.
Was customer information included? Financial data? Internal strategy? Employee details? Confidential documents?
Businesses should treat AI tools the same way they would any other application that receives company information. Before sensitive information is entered, someone should understand whether the tool is approved and what type of information employees are allowed to share with it.
“Shadow AI” Can Develop Quietly
When employees begin using technology that the business has not approved or reviewed, it is often described as Shadow IT. AI can create a similar problem.
Employees are not necessarily trying to bypass company rules. Often, they have simply found a tool that makes their job easier.
That is why an AI policy should go beyond simply saying, “Don’t use AI.”
Employees need practical guidance. Which tools are approved? What types of information can be entered? What information should never be entered? Does someone need to review AI-generated work? Who should employees ask if they want to try something new?
The clearer the rules are, the easier they are to follow.
AI Changes the Threat, but Good Security Habits Still Work
Cybersecurity conversations about AI can quickly become dramatic. Deepfakes, AI-powered phishing, automated attacks and fake voices are all legitimate concerns.
But businesses should not come away feeling powerless because it may be harder to tell what is real.
Many of the most useful defenses are still surprisingly practical: verify unusual requests, use strong authentication, have clear payment procedures, train employees, report suspicious activity quickly, control how sensitive information is shared and know which AI tools employees are allowed to use.
Most importantly, make it normal for someone to stop and ask, “Can we verify this before we do anything?”
That question may become increasingly valuable as AI-generated content becomes harder to distinguish from the real thing.
The goal is not to turn employees into AI detectives. It is to build processes that continue working even when the disguise gets better.