Love, Luxury, and LLMs: How AI Is Reshaping Valentine’s Day Gifting and Why Brands Must Act Now

Valentine’s Day is more than a romantic milestone. For premium and luxury brands, it is the final crescendo of the holiday season, a high-intensity commercial moment defined by urgency, emotion, and high-value purchasing. 

Unlike everyday consumption, gifting is symbolic. It carries meaning, intention, and identity. And when it comes to premium gifts such as jewelry, leather goods, fragrances, and luxury accessories, the stakes are even higher. The gift is not just a product. It is a statement. 

This makes gifting one of the most powerful acquisition levers for premium brands. A well-chosen Valentine’s gift often introduces a new customer to a brand, sometimes for the first time, through an emotional and memorable experience. 

But the path to purchase is changing rapidly. 

During the 2025 to 2026 holiday season, the share of traffic to retailers’ websites coming from LLMs and gen AI engines was 7 times higher than the previous year, according to an Adobe study. AI is no longer a marginal touchpoint. It is becoming a front door to commerce. 

And that shift carries both opportunity and risk. 

In the era of AI-powered discovery, visibility alone is no longer enough. What matters is how brands are surfaced, framed, and recommended by LLMs. 

Luxury brands, in particular, face a structural vulnerability: counterfeiting. 

AI-led shopping journeys often begin broadly. A consumer might ask for “Valentine’s gift ideas under $1,000,” then refine their query to “similar to this brand but less expensive.” After just a few prompts, typically three to four iterations, counterfeit listings begin to surface. 

What is striking is that users are not explicitly asking for fake products most of the time. Many are simply looking for more affordable options. Yet instead of being directed to alternative brands or adjacent categories, they are easily  guided toward counterfeit versions of the same product. 

In other words, they are not sent to a different brand. They are sent to a cheaper version of the same brand. 

Guardrails do appear when users directly request counterfeit products. However, softer prompts such as “find a dupe,” “lookalike,” or uploading an image into an AI tool can lead to counterfeit listings and even supplier-level visibility. 

As AI reshapes discovery and gifting behaviors, luxury brands must rethink not only how they appear in AI environments, but how they are protected within them. This challenge applies particularly to well-established maisons with strong global recognition. 

Visibility without protection is no longer sufficient. 

Counterfeiting is definitely  not a niche issue. The OECD estimates that global counterfeit trade represents $467 billion, or 2.3 percent of total global imports. 

The digital ecosystem plays a central role. Many direct-to-consumer platforms, which LLMs draw from, host vast product catalogs with varying levels of moderation and seller verification. According to a February 2025 OnePoll study conducted with Red Points, 28 percent of consumers who purchased counterfeit products online used AI tools to assist their search. 

AI chat-based shopping amplifies existing risks for several structural reasons: 

• Sources are compressed and deprioritized in conversational outputs.
• Seller verification signals are subtle, inconsistent, or absent.
• Official URLs and authorization cues are easy to overlook in summarized responses.
• Answers are delivered with high confidence, even when underlying data quality is weak. 

AI models may aggregate information from polluted product feeds, SEO-optimized impostor sites, lightly moderated marketplaces, or one-off sellers with minimal vetting. Yet the output is presented in a clean, authoritative tone that signals trust. 

The interface feels reliable. The underlying ecosystem may not be. 

As AI becomes a primary layer of commerce, trust can no longer be assumed. It must be designed into the system. 

This means clearer warnings when sources are weak or unverified, stronger safeguards around “cheaper alternative” queries, and tighter collaboration between brands, platforms, and AI providers to prevent counterfeit acceleration within conversational commerce. 

For premium brands, especially during emotionally charged moments like Valentine’s Day, the risk is not only financial. It is symbolic. A counterfeit product undermines craftsmanship, heritage, and the emotional promise embedded in the gift itself. 

Protecting brand integrity in AI environments is not just a compliance issue. It is a strategic imperative. 

Valentine’s Day highlights a broader transformation. Gifting moments are increasingly mediated by AI. Discovery is conversational. Inspiration is algorithmic. Recommendations are synthesized in seconds. 

In this new paradigm, brands must evolve from traditional SEO and marketplace monitoring to a more advanced approach: 

• Understanding how they are represented across LLMs and AI assistants
• Identifying structural vulnerabilities in AI-led journeys
• Strengthening their digital footprint to ensure authoritative, verified signals dominate
• Designing protective mechanisms against counterfeit surfacing
• Preparing for agentic commerce, where AI systems act on behalf of consumers 

At Sia, we help brands navigate this new landscape by combining brand visibility strategy, data intelligence, and agentic commerce readiness. From AI exposure diagnostics to counterfeit risk mapping and governance frameworks, we work with premium and luxury brands to ensure they are not only visible in AI ecosystems, but protected and positioned to win. 

As we approach Valentine’s Day, the question for premium brands is no longer simply: “Are we visible?” 

It is: “Are we visible in the right way, in the right contexts, and protected where it matters most?” 

Because in the age of AI, love may be timeless, but discovery is being rewritten.