AI-Powered Scams: How Are Scammers Using AI, and How to Stay Safe

AI tools and model capabilities are improving with each new version. As a result, the level of sophistication and realism in scams is increasing. According to the FBI’s annual report, financial losses due to cybercrime exceeded $12.5 billion in 2023—just one indicator of the enormous impact of these attacks.

At the same time, the growing accessibility of AI platforms means that anyone with basic knowledge can quickly launch fraudulent campaigns. With various open-source libraries and cloud services, the entry barrier is lower, and the reach of these scams is expanding.

Common targets of AI scams

Anyone can be a target, but the most frequent ones include older adults, public officials, and businesses of all sizes. Here, the most vulnerable profiles are typically those with less digital experience and knowledge, especially those whose personal data is exposed—on social media, for example. In such cases, scammers use publicly available information to craft highly personalized attacks.

If we’re not careful, data from public records and social media can greatly facilitate identity theft and credential spoofing. The way to reduce these risks—which become even more dangerous when an AI is analyzing and using the data—is by reviewing our privacy settings on apps and services, and sharing information in a controlled way.

Types of AI scams

The range of AI-powered scams is extensive. Combining several techniques increases the success rate and makes it harder to defend against them using traditional detection and response methods. Scammers are increasingly using AI tools to generate convincing deepfakes, impersonate voices, and automate social engineering at scale, making their scams more persuasive and harder to detect. By leveraging these technologies, they can quickly tailor attacks to individual targets and mimic trusted sources with alarming accuracy. Let’s go through the main types of AI scams.

Voice cloning scams

Voice cloning scams use AI to mimic someone’s voice. This voice cloning makes it possible to create audio messages or conduct real-time calls that include personal details and present as urgent situations. This urgency, combined with the use of familiar voices, tricks the target quickly without raising immediate suspicion.

These scams often involve requests for bank transfers, the sharing of confidential data, or attempts to gain access to internal systems in companies. In these cases, verifying identity through independent channels and agreeing on specific security codewords in advance is essential to confirm the authenticity of the communication.

Additionally, spotting inconsistencies in audio quality or odd intonation patterns can help us distinguish synthetic calls from real ones—something to look out for even when the content seems urgent. Paying attention to unusual pauses or incoherent background noises gives us more tools to detect audio manipulation.

Deepfake scams

Some scams use deepfakes to create fake videos or conduct video calls while impersonating someone else. The high fidelity of facial movements and lip-syncing makes it very hard to tell them apart from real communications.

This type of fraud includes everything from transfer requests to the spread of false information or blackmail. In these cases, verifying unexpected requests through a separate channel that we have previously confirmed is key before taking any action.

We should also watch for signs like inconsistent lighting, rigid facial movements, and variations in image quality or detail. Observing subtle cues in gestures and shadows, as well as intonation, pauses, or overall sound, is the best way to assess the authenticity of a video or video call.

AI phishing

Phishing—deceptive emails—becomes much more convincing when supported by AI. AI can craft highly personalized emails that appear to come from trusted services or contacts. The automatic and rapid generation of error-free texts that closely mimic the style of real senders can easily fool recipients used to spotting spelling mistakes as red flags.

The most convincing attacks often reference recent real-world events or draw data from social profiles to appear more legitimate. Here, confirming both the sender and the URLs through an independent check is absolutely essential to rule out threats.

Staying alert to messages that seem unusually urgent is also crucial. Verifying information ourselves—for example, by calling the company using a number we find online (never the one in the message itself)—is the most effective thing we can do.

AI smishing

Similar to the previous section, smishing refers to phishing attempts via SMS. AI-generated text messages are presented as fake banking alerts, package delivery notifications, or company communications. Unlike emails, their brevity leaves us with far less information to assess.

To manage the risks, it’s crucial to be especially cautious with unknown senders and always use official channels to confirm any request.

Detecting inconsistencies in the sender’s details, tone, timing, and shortened suspicious links should help us identify even the most sophisticated smishing attempts.

AI vishing

This term covers scams that happen via phone calls or voicemail messages. These scams combine voice cloning with social engineering to extract sensitive information or request money transfers. The ability to conduct real-time synthetic calls using another person’s voice is something most people aren’t prepared for.

As in previous cases, it’s important to agree on verification keywords and/or confirm any requests through previously known and secure lines. Noticing unusual pauses or shifts in tone can also reveal a synthetic voice. Paying attention to vocal patterns and response timing is key to distinguishing real voices from artificially generated ones.

AI-powered financial fraud schemes

Lastly in this section, while we’re not talking about a specific scam method, but rather the target of many scams, it’s worth highlighting AI-driven financial fraud.

These schemes include fake investment opportunities, fraudulent loans, or unauthorized transfers. In these scenarios, the combination of emails, SMS, calls, and deepfakes to request payments exposes targets to multi-channel attacks that require heightened awareness.

Thanks to AI’s ability to analyze vast amounts of financial and personal data, these attacks are always tailored to the victim’s real profile—making it much harder to tell authentic from fake communications. In these cases, double-checking payment instructions via an official contact is crucial, along with other measures, to ensure transaction security.

How to recognize AI scams

Based on everything we’ve just discussed, recognizing the early signs of scams—AI-based or not—is absolutely vital for taking swift and effective action. Learning certain deceptive patterns, which can always be applied to new techniques, allows us to stay protected.

Signs of voice cloning and deepfake scams

The biggest red flag in voice cloning or deepfake scams is the very reason for the call. An urgent call demanding immediate action is always suspicious. Add to that unnatural facial movements in videos, strange pauses, changes in tone, or inconsistent visual textures—all should raise immediate concern. Lip-syncing and audio quality are also useful clues for spotting synthetic content.

Indicators of phishing and vishing attempts

In emails, phishing often reveals itself through altered links and unexpected senders. Emails will always come from unofficial sources and try to redirect the victim to an unofficial site—even if the name or address is only slightly different. While AI can make the rest of the email look very convincing, this is the one area where we can consistently spot the fraud.

Similarly, in vishing calls, urgent tones and the lack of usual context should alert us to potential scams—even if the voice sounds familiar.

Red flags in financial fraud schemes

Finally, in financial scams, the biggest red flags include unexpected invoices, requests for payment in cryptocurrency, and emails that look official but contain links to unofficial sites. Spotting inconsistencies in banking details or invoice formats is key to avoiding financial loss.

How to protect yourself from AI scams: Tips for safeguarding personal information

Limiting the personal information we post on social media or make publicly available online is the first and most important step. At the same time, privacy settings on each platform give us some control over our data.

Using strong passwords and always enabling two-factor authentication is also essential. Keeping our devices and apps up to date, and having good antivirus software like Avast, which helps detect and automatically respond to threats, is of course critically important too.

Reporting and responding to scams

Beyond protection, reporting incidents to official bodies helps identify attack patterns and strengthen collective security. While tools like Avast have their own detection systems and databases, it is always a good idea that we report fraud attempts to the competent authorities. A movement that allows the discovery of new attack vectors and improves the security of all those involved.

Conclusion: While AI makes scams harder to detect, we can stay safe

Now that AI can be used to launch more convincing scams, it’s more important than ever to maintain constant vigilance and have the right security measures in place to protect our data and communications.

Having reviewed the types of threats and how to detect and neutralize them, it’s clear that staying safe depends on good practices that keep us alert and prevent simple mistakes from putting us at risk. Once we understand that urgency is never a good advisor, protecting ourselves from AI scams is well within our reach.