Consumers increasingly use tools such as ChatGPT, Gemini, Claude, Perplexity, and Grok to decide where to shop, which products to buy, and which websites to trust. Instead of sorting through pages of search results, they receive direct answers and links within seconds.

According to Adobe Digital Insights, 38% of surveyed U.S. consumers had already used generative AI for online shopping, while 52% planned to use it for shopping in 2026. AI-driven traffic to U.S. retail sites also rose sharply as consumers adopted these tools.

This shift changes how consumers interact with brands online. Instead of comparing several search results, users may act on a single AI-generated answer. As a result, AI platforms are becoming important intermediaries between brands and customers.

Unfortunately, scammers are adapting to the same shift.

How Can a Phishing Site Appear in an AI Recommendation?

AI assistants often search, retrieve, summarize, or reference information from across the web. Therefore, a malicious website that creates enough convincing signals may sometimes appear relevant to an AI system.

This does not mean the AI platform itself has been compromised. Instead, attackers can exploit the wider information environment that AI tools use to discover and evaluate sources.

A June 2026 investigation by The Guardian, for example, documented cloned retail websites appearing in ChatGPT search results. Consumers reportedly assumed some stores were genuine partly because an AI tool had surfaced them.

Similarly, Forbes has reported on the rise of AI-assisted “ghost stores.” These sites can imitate legitimate retailers, use fabricated brand stories, and create convincing content that makes fraudulent businesses appear real.

For security leaders, the implication is important. Brand trust and customer safety must now extend into environments where AI can influence what consumers buy and which websites they visit.

When AI Becomes a Referral Source

Historically, consumers relied heavily on search engines to discover brands and products. In response, security and brand protection teams monitored search results, identified impersonation websites, detected phishing campaigns, and removed malicious content.

AI assistants change this model.

Rather than showing ten blue links, an AI assistant can provide one direct recommendation. A user may interpret that answer as a vetted recommendation, even when the underlying source has not received the level of verification the user assumes.

This creates a trust gap that scammers can exploit.

For example, a convincing phishing site may copy a brand’s logo, product images, website layout, pricing, and customer support language. It may also use a lookalike domain that appears legitimate at first glance.

If that site becomes discoverable through search, online content, advertising, or other sources, it can potentially enter the information ecosystem used by AI tools.

The result creates a dangerous combination:

• Consumers increasingly trust AI recommendations.
• Fraudsters understand how online information gets discovered.
• Generative AI helps attackers create realistic content quickly.
• Fake websites can gain visibility before the targeted organization detects them.

Therefore, organizations cannot treat AI discovery as separate from digital risk protection.

The Rise of AI-Powered Scam Tactics

Fraud has always followed consumer behavior.

When consumers moved to social media, scammers created fake profiles and malicious ads. When shoppers embraced online marketplaces, counterfeit sellers followed. As mobile apps became dominant, attackers launched rogue apps that copied trusted brands.

Now, consumers are adopting AI-assisted discovery.

At the same time, generative AI has lowered the cost of producing convincing scam content. Attackers can quickly create website copy, product descriptions, support pages, localized content, fake testimonials, images, and phishing pages.

As a result, one attacker can operate many sites or identities at once.

This makes isolated detection less effective. Security teams need to determine whether one phishing site belongs to a larger network of related domains, social accounts, advertisements, storefronts, or impersonation campaigns.

That shift from individual incidents to connected threat infrastructure is critical. It helps teams identify the operators and patterns behind the visible scam rather than treating each URL as a separate problem.

Why Phishing Sites Matter for CISOs

At first glance, fake stores and AI shopping scams may look like consumer or brand protection problems. However, they can also create direct cybersecurity and business risks.

According to the U.S. Federal Trade Commission, phishing scams often try to steal passwords, account information, financial details, and other sensitive information.

Similarly, the Cybersecurity and Infrastructure Security Agency identifies recognizing and reporting phishing as a core step for staying safe online.

When a customer falls victim to a phishing site impersonating a known brand, the impact can extend beyond one transaction.

Potential consequences include:

• Loss of customer trust
• Stolen login credentials
• Payment card fraud
• Higher customer support volumes
• Brand reputation damage
• Fraud investigations
• Regulatory exposure in some industries

In addition, victims may blame the company whose identity attackers copied rather than the criminal operating the scam.

That distinction matters. The malicious activity may happen outside the organization’s network, but the targeted brand still absorbs much of the reputational damage.

For CISOs, this means external phishing, brand impersonation, and digital fraud should form part of a broader external cybersecurity strategy.

BrandShield’s External Cybersecurity solution focuses on threats that operate beyond the traditional corporate perimeter, including phishing sites, malicious domains, executive impersonation, fake ads, rogue mobile apps, and other external threats.

Expanding Digital Risk Protection Into AI Platforms

Traditional digital monitoring developed around a web dominated by search engines, websites, social platforms, and marketplaces.

Those channels still matter. However, AI assistants now add another layer.

Organizations increasingly need to understand how their brands, products, executives, and digital assets appear within AI-generated answers.

This is especially important when an AI answer references a phishing site, fake store, counterfeit seller, or other malicious source.

BrandShield AI Platforms Protection extends digital risk monitoring into AI-generated discovery. It identifies harmful or infringing sources surfaced in responses across platforms including ChatGPT, Gemini, Perplexity, and Grok.

Rather than relying only on customer reports, organizations can look for:

• Phishing sites impersonating their brand
• Fraudulent or lookalike domains
• AI references to malicious websites
• Counterfeit product listings
• Fake online stores
• Executive impersonation
• Unauthorized sellers
• Related scam infrastructure

In other words, organizations need visibility at the point where consumers discover a threat, not only after they become victims.

From Phishing Site Detection to Threat Investigation

Detection is only the first step.

After identifying a malicious website, security teams need to understand what sits behind it.

For example, one phishing site may share infrastructure, content, registration information, images, analytics identifiers, or other signals with dozens of additional threats.

Modern digital risk protection can help connect those signals.

BrandShield uses AI-powered analysis and clustering to identify relationships across external threats. Its approach helps organizations examine domains, websites, social accounts, marketplaces, and other sources as parts of broader campaigns rather than unrelated incidents.

More information about this approach is available on BrandShield’s AI-powered digital risk protection page.

This context allows teams to prioritize threats based on risk. For example, a dormant lookalike domain may deserve less urgent attention than an active phishing site that an AI assistant or search engine is already surfacing to potential customers.

Therefore, exposure should become part of risk prioritization.

How Should Organizations Respond?

Organizations should expand external threat monitoring to reflect the channels their customers now use.

First, teams should monitor domains and websites for brand impersonation, typosquatting, cloned content, and phishing activity.

Second, they should examine other channels connected to those threats. These can include social profiles, paid advertisements, mobile apps, marketplaces, and AI-generated recommendations.

Third, teams should connect related incidents. A cluster of malicious assets may indicate a coordinated campaign rather than several independent threats.

Finally, organizations need a clear enforcement process. Finding a phishing site has limited value if the organization cannot investigate, prioritize, report, block, or pursue removal quickly.

BrandShield’s broader online brand protection platform combines monitoring, analysis, risk prioritization, and enforcement across external digital channels.

The Future of Brand Protection Includes AI

AI assistants represent one of the largest changes in online discovery since the rise of search engines.

For consumers, they reduce the effort required to research products and businesses. For brands, they create a new customer touchpoint. However, they also create another path through which malicious sources can gain visibility.

The underlying threats remain familiar. Attackers still use phishing sites, counterfeit stores, impersonation, deceptive advertisements, and malicious domains.

What has changed is how consumers can reach those threats.

Therefore, organizations should not treat AI platforms as an isolated security category. They should view AI discovery as part of the broader digital environment in which phishing and impersonation campaigns operate.

The key question is no longer whether attackers will try to exploit AI-assisted discovery.

It is whether organizations can detect a malicious source before customers trust it.

Because the next phishing site targeting your customers may not appear first in an email or Google search. It may be recommended by an AI assistant.

FAQ: Phishing Sites and AI Recommendations

What is a phishing site?

A phishing site is a fraudulent website that imitates a trusted company or service to steal passwords, financial information, personal data, or money. Attackers often use copied branding and lookalike domains to make the site appear legitimate.

Can AI assistants recommend phishing sites?

AI assistants can sometimes surface or reference malicious websites when those sites appear relevant within the information sources available to the system. Reports in 2026 documented cloned retail sites appearing in AI-assisted shopping results.

Why are phishing sites becoming harder to detect?

Generative AI allows attackers to create realistic website copy, images, product descriptions, localization, and other content quickly. As a result, fraudulent sites can look increasingly similar to legitimate businesses.

How can companies detect phishing sites impersonating their brand?

Companies can monitor newly registered domains, website content, search results, social media, paid advertisements, marketplaces, mobile apps, and AI platforms. Connecting related threat signals can also reveal larger phishing networks.

How does AI platform protection fit into digital risk protection?

AI platform protection adds visibility into harmful sources that AI assistants reference or recommend. It complements monitoring across websites, domains, social media, marketplaces, advertising, mobile apps, and other external channels.