For years, Amazon’s search engine has been a marvel of scale but not always one of understanding. Sellers have long optimized listings to match exact keywords, only to see irrelevant search results dominate shopper queries. One of the biggest issues? Amazon couldn’t grasp what customers didn’t want.
If a shopper searched for “no laces,” they’d often be shown lace-up shoes anyway. Why? Because traditional search engines, including Amazon’s older system, simply weren’t built to handle language the way humans use it—especially when it came to negation.
But now, that’s changing.
Amazon’s AI Is Now Rewriting the Rules of Search
Amazon has quietly rolled out a major upgrade to its search engine, powered by large language models (LLMs). According to a recent Amazon Science release, the company’s AI now interprets and rewrites customer queries using smarter, benefit-driven language.
So what does this look like in practice?
If a customer types in “no glare,” the AI now understands that they likely mean “anti-glare.” A search for “no cords” transforms into “wireless,” and “not sticky” might be interpreted as “quick-dry” or “residue-free.” Instead of simply scanning listings for keywords, Amazon’s AI is trying to understand customer intent—and reframe queries to match it.
This isn’t just a technical enhancement. It’s a fundamental shift in how Amazon matches search input with product listings. And for sellers, it opens up both new opportunities and new responsibilities.
What This Means for Your Listings
The key takeaway is simple but powerful: Your product listings must speak the same language as Amazon’s new AI.
If your titles, bullets, or backend search terms are filled with negative phrasing—“no mess,” “not sticky,” “no noise”—you might be missing out. These phrases may no longer match rewritten queries in the same way.
Instead, Amazon is prioritizing listings that articulate the positive version of the benefit. Think:
Anti-smudge” instead of “no fingerprints
Odor-resistant” instead of “doesn’t smell
Slip-on” instead of “no laces
In early testing, Amazon found that this approach resulted in up to 15% more relevant search matches—a significant jump that could drive major increases in impressions, clicks, and conversions for sellers who adjust their content accordingly.
Why This Shift Matters
The change reflects a broader evolution in e-commerce: moving from keyword matching to intent matching. Customers don’t always use perfect, product-friendly language in their searches. They describe problems. They say what they want to avoid. They use natural, conversational phrases.
Amazon’s new AI is finally catching up to that reality. And that means sellers need to do the same.
If your listing still says, “Doesn’t leave residue,” but the rewritten search is looking for “residue-free,” you may be skipped entirely. Vague, generic phrases like “great quality” or “easy to use” also won’t cut it anymore. Amazon’s AI is looking for specific features that map to intent-driven rewrites.
How I’m Adapting (And What I Recommend)
When I first read about this update, my immediate reaction was: this changes everything—but not in a scary way.
This is a rare opportunity to get ahead of the curve.
I’ve already started reviewing my top-performing ASINs with a fresh eye, looking specifically for any phrases that include “no,” “not,” or similar negations. I’m replacing those with affirmative, benefit-driven language that aligns with how Amazon is now rewriting customer queries.
For example, one product listing previously highlighted “no-slip grip.” That’s now “anti-slip grip.” Another that said “no noise” now emphasizes “quiet operation.”
These changes might seem small, but they’re strategically significant. Because if Amazon’s AI is searching differently, our listings need to reflect that shift—or risk falling off the radar entirely.
Final Thoughts: This Is a Wake-Up Call (In a Good Way)
Amazon’s AI is evolving—and it’s becoming more human. That’s great news for shoppers, but only if sellers keep up.
This isn’t just about optimizing for a machine. It’s about communicating value in a way that feels natural, intuitive, and useful to your actual audience.
It’s also a reminder that search behavior is no longer static. As the algorithms grow smarter, we must write smarter too. That means ditching vague, outdated language and embracing specific, benefit-led messaging that anticipates how Amazon interprets customer needs.
So, if you’re still optimizing your listings like it’s 2022, it’s time to stop. Amazon’s search engine has evolved. Your copy should too.
Audit your listings. Think like your customer. And most importantly—write like Amazon’s AI now reads.
