AI tools now write the phishing email, build the storefront, clone the voice on the phone call, and generate the video of an executive endorsing something they never touched. For brands, that fraud shows up in places a marketing or legal team wouldn’t normally think to monitor, from chatbot shopping results to a “livestream” that never happened.
TL;DR
- AI-powered scams use generative AI to create convincing text, images, audio, video, websites, product listings and fake reviews at scale.
- For brands, the biggest risks are AI phishing, executive impersonation, deepfake endorsements, AI-generated fake websites, fake social accounts, scam ads and counterfeit listings surfaced through AI shopping tools.
- ChatGPT and other AI assistants are becoming product discovery channels, which creates a new surface where cloned sites and infringing listings can reach shoppers.
- Deepfake video and voice impersonation now affects executives, founders, influencers and public figures, not only celebrities and politicians.
- Brands need employee training, customer education, registered IP rights, and continuous monitoring across AI discovery surfaces, social video, marketplaces, ads and the open web.
What are AI-powered scams?
AI-powered scams are fraud schemes that use generative AI to make deception faster, cheaper and more convincing. Instead of manually writing phishing emails, editing images, building fake websites or producing fake videos, scammers can use AI tools to generate those assets at scale.
For brands, the most common AI-powered scams include AI-written phishing, fake customer support messages, cloned executive voices, deepfake endorsements, AI-generated fake websites, fake reviews, fake social accounts, scam ads and counterfeit listings surfaced through AI shopping tools.
| AI scam type | How AI changes it | Brand risk |
| AI phishing | Generates polished emails, messages and fake support scripts | Credential theft, payment fraud, employee impersonation |
| Deepfake impersonation | Clones voices and faces for videos, calls and ads | Executive fraud, fake endorsements, reputational damage |
| AI fake websites | Builds polished storefronts and copied product pages faster | Lost sales, customer data theft, brand confusion |
| AI shopping scams | Surfaces fake or cloned links through AI discovery tools | Shoppers are redirected to fraudulent sites or listings |
| Fake reviews and social proof | Generates reviews, comments and urgency messaging | Fake stores look more credible than they are |
| Counterfeit listings | Produces titles, descriptions, images and localized copy at scale | More infringing listings across marketplaces and search |
How AI is changing the scam landscape
Fraud used to take manual effort: writing a believable email, recording a convincing voice message, building a website that looked legitimate, or creating enough fake reviews to make a new store feel real.
Generative AI collapses much of that effort into a prompt.
The FBI’s 2025 Internet Crime Report included AI-related complaints for the first time. It recorded 22,364 AI-related complaints, with reported losses of nearly $893 million.
F-Secure’s 2026 scam research also found that 89% of scammers’ AI use focuses on improving the quality of their bait, using AI-generated messages, images, audio and video to make scams harder to detect.
For brands, the risk is not only that scams are more convincing. It is that they appear across more channels, in more formats and at a speed manual monitoring cannot match.
AI-generated phishing and employee impersonation
AI makes phishing easier to personalize.
A scammer can use public information from LinkedIn, press releases, podcasts, earnings calls or company websites to create messages that sound like a real executive, supplier, partner or customer. Those messages can target employees with requests for payments, credentials, files or system access.
The same problem now extends beyond text. Voice cloning and deepfake video make it harder for employees to rely on instinct. A call that sounds like a CFO, a video that looks like a founder, or a message written in a colleague’s tone is no longer proof of identity.
For brands, the defense needs to be process-based:
- Verify payment or credential requests through a second channel.
- Use known phone numbers, not numbers included in the suspicious message.
- Require second approval for bank detail changes, invoices and wire transfers.
- Train teams that convincing language, voice or video does not prove legitimacy.
- Give employees a simple way to report suspected impersonation.
AI phishing is not only an IT issue. It can quickly become a brand, legal and finance issue if scammers impersonate executives, customer support teams, distributors or vendors.
AI shopping and discovery scams
ChatGPT and other AI assistants are becoming places where shoppers ask for product recommendations before they visit a search engine, marketplace or retailer website.
OpenAI describes shopping research in ChatGPT as an interactive product discovery experience that can use merchant product data, publicly available product information and other retail sources. OpenAI has also expanded the Agentic Commerce Protocol to support product discovery in ChatGPT, including visual shopping results, side-by-side product comparisons and merchant product feeds.
That creates a new risk for brands. If a fake website, counterfeit listing or impersonating social page is indexed or surfaced in an AI recommendation flow, a shopper may trust it because it came through an assistant.
AI assistants can surface product links from a mix of web content, merchant feeds, integrations and search-like retrieval systems. Fraudsters will try to manipulate whichever discovery surface gives them reach.
Common risks include:
- Cloned retailer websites appearing as shopping sources
- Counterfeit marketplace listings surfaced through AI recommendations
- Source links pointing to impersonating websites or social pages
- Fake product pages optimized around the same terms as the genuine brand
- AI-generated descriptions and reviews making fraudulent listings look credible
For shoppers, the safest behavior is still basic verification: check the domain, avoid unfamiliar checkout pages, compare pricing against official channels, and use the brand’s website or verified retailer list when in doubt.
For brands, AI shopping adds a new monitoring layer. It is not enough to know what appears on marketplaces and search engines. Teams also need to know what AI assistants surface when shoppers ask for their products.
Deepfake video and voice impersonation
Convincing deepfake video was once mostly associated with politicians and global celebrities. That has changed.
Executives, founders, athletes, artists, influencers and public figures with a trusted audience can all become targets. A scammer does not need the whole internet to believe the fake. They only need enough of the right audience to click, invest, buy or share.
A typical deepfake scam might show a recognizable person:
- Endorsing an investment platform
- Promoting a health or beauty product
- Announcing a fake giveaway
- Appearing in a fake livestream
- Asking employees or partners to take urgent action
- Giving credibility to a fraudulent landing page
The Arup case showed how serious deepfake-enabled impersonation can become in a corporate context: an employee was deceived into transferring roughly $25 million after a video call where other participants appeared to be company leaders.
For brands, deepfake scams are difficult because they are video-native. Traditional monitoring often relies on text: titles, captions, seller names, hashtags, domains, or product descriptions. Deepfake campaigns may rotate creatives, use disposable ad accounts, and disappear before a manual review process catches up.
AI-generated fake websites, listings, and reviews
Fake websites are not new. What AI changes is the speed and polish.
A scammer can generate product copy, FAQs, checkout pages, privacy policies, customer reviews and localized versions of the same fake store much faster than before. They can also create product images, urgency banners, discount messaging, and fake social proof that make the site look more established than it is. In a survey of 2,000 U.S. counterfeit buyers, 58% of unintentional fake website buyers fell for polished design, branded imagery, and convincing product descriptions.
Fake reviews are part of the same problem. The US Federal Trade Commission’s final rule on fake reviews and testimonials specifically addresses reviews that misrepresent that they were written by someone who does not exist, including AI-generated fake reviews.
For brands, the warning signs usually include:
- Lookalike domains
- Prices that are far below normal retail
- Copied product photos and descriptions
- Reviews that appeared in a short time window
- Social ads pointing to unfamiliar checkout pages
- Missing company information or unclear returns policies
- Payment flows that redirect away from the expected site
AI can also help scammers create counterfeit listings at scale. Product titles, marketplace descriptions, image variations and translated copy can be generated quickly, making it easier to launch the same abuse across countries and platforms.
For more detail on removing fraudulent sites, see Red Points’ guides on how to take down a fake website.
The business risk for brands
AI-powered scams create more than direct financial loss.
A customer who buys from a fake website may blame the brand. A shopper who sees a deepfake endorsement may believe the company approved the promotion. An employee who receives a cloned executive voice may treat it as urgent and legitimate. A counterfeit listing surfaced through an AI assistant may look safer than an unknown marketplace result because the recommendation feels curated.
The result is a wider trust problem:
- Customers become less confident in official brand communications.
- Support teams handle complaints from people who never bought from the real brand.
- Legal teams spend more time gathering evidence and filing reports.
- Marketing teams lose control of how products and executives appear online.
- Fraud teams have to connect activity across websites, social media, marketplaces, ads and AI discovery tools.
The harder it becomes to tell real from fake, the more important it becomes for brands to monitor proactively.
How to protect your brand from AI-powered scams
Educate customers directly
Give customers a simple way to verify official channels.
Publish guidance on your website that explains:
- Your official domains
- Authorized retailers
- Verified social accounts
- What your customer support team will never ask for
- How to report a suspicious site, ad, listing or message
This helps customers check before they pay and gives your support team a clear resource to share when questions come in.
Train employees to verify, not guess
Employees should not be expected to detect every AI-generated voice, video or email by sight or sound.
Use process instead:
- Require callback verification for payment requests.
- Use a second approver for bank detail changes.
- Treat urgent credential requests as suspicious.
- Report impersonation attempts quickly.
- Keep executive contact details and approval workflows up to date.
The goal is not to make employees deepfake experts. It is to make sure one convincing message cannot bypass internal controls.
Register and organize your IP rights
Registered trademarks, copyrights, and other IP rights give brands a stronger basis for takedown requests.
Keep rights documentation, brand assets, authorized domains, official social accounts, and distributor information organized. When a fake website, counterfeit listing, impersonating account or deepfake video appears, clear evidence speeds up reporting and enforcement.
Monitor beyond marketplaces and search
AI-powered scams do not stay in one channel.
Brands should monitor:
- Marketplaces
- Search results
- Social platforms
- Paid ads
- Standalone websites
- Lookalike domains
- AI shopping and discovery surfaces
- Video platforms
- Fake reviews and social proof
For broader protection planning, see Red Points’ complete guide to brand protection and guide to online marketplace monitoring.
How Red Points protects brands across AI channels
Brand protection built for marketplaces and search engines does not automatically cover AI assistants or AI-generated video. Red Points has launched dedicated services to help brands address those new surfaces.
AI Commerce Protection
Red Points’ AI Commerce Protection monitors ChatGPT, Claude, Gemini and Perplexity as a product discovery channel. It identifies infringing product listings, redirected marketplace links, and source links that point to impersonating websites or social pages surfaced through AI engines’ shopping and discovery experience.
Detection is prompt-based and built around each brand’s product information, genuine indicators, fake indicators, protected domains, and other relevant signals. Confirmed incidents are reported to the engine and to the underlying platform or website.
Deepfake Protection
Red Points’ Deepfake Protection detects and removes AI-generated videos that impersonate executives and public figures across major social and video platforms.
The service combines discovery agents with facial recognition, voice recognition, and language models that help verify both identity and intent before enforcement. This is designed for video-led scams where text-based monitoring is not enough.
Broader enforcement
AI-powered scams often connect several channels at once. A deepfake ad may send viewers to a fake website. A fake website may link to counterfeit listings. A counterfeit listing may be surfaced through an AI shopping tool.
Red Points helps brands connect these signals across marketplaces, social platforms, domains, ads, websites, and AI discovery surfaces. Red Points validates potential infringements before enforcement, using the brand’s IP rights, evidence, approved rules, and known authorized sellers or distributors to avoid acting on legitimate activity.
Request a demo to see how Red Points can help detect and remove AI-powered brand abuse.
Frequently Asked Questions on AI-powered scams
What are AI-powered scams?
AI-powered scams use generative AI tools to make fraud faster, more convincing and harder to detect. They can include AI-written phishing, cloned voices, deepfake videos, fake websites, fake reviews, fake social accounts, counterfeit listings and scams surfaced through AI shopping assistants.
How do scammers use ChatGPT to run scams?
Scammers can use ChatGPT and other AI tools to write phishing content, generate website copy, create product descriptions and scale fake listings. The newer risk is discovery: if a fraudulent website or listing is surfaced through an AI shopping result, shoppers may treat it as more trustworthy than a random search result.
Is it safe to buy something ChatGPT recommends?
Treat AI shopping recommendations the same way you would treat any unfamiliar online store. Check the domain, compare the price against official channels, review the seller, and avoid entering payment details on a site that does not clearly belong to the brand or a trusted retailer.
Why are executives and influencers being targeted by deepfake videos?
Scammers target people whose audience already trusts them. That can include executives, founders, athletes, creators, influencers and public figures. A fake endorsement or fake video message can drive clicks, payments or credential theft before the target knows it exists.
How can I tell if a website is an AI-generated fake?
Look for a domain that does not match the official brand, unusually steep discounts, copied product images, vague company details, recent or repetitive reviews, unexpected payment redirects and policies that look generic or inconsistent.
Does registering a trademark help against AI-generated fakes?
Yes. Registration gives brands a clearer legal basis to request removal from marketplaces, hosting providers, social platforms, domain registrars and other services where fake listings, fake websites or impersonating content appears.
How does Red Points detect AI shopping fraud on ChatGPT?
Red Points uses prompt-based detection built around each brand’s products, genuine indicators, fake indicators, protected domains and relevant keywords. It looks for infringing listings, redirected marketplace links and source links that point to impersonating websites or social pages surfaced through ChatGPT.
How does Red Points detect deepfake videos?
Red Points combines discovery agents with facial recognition, voice recognition and language models to identify videos that appear to impersonate protected executives or public figures. Confirmed cases can then be actioned through the relevant platform enforcement route.
What is the best way for brands to prevent AI-powered scams?
The best approach is layered: educate customers, train employees to verify suspicious requests, keep IP rights and evidence organized, monitor across marketplaces, social, ads, websites, domains and AI discovery tools, and act quickly when impersonation or infringement appears.
