Will AI Chat Merge with the Search Bar? Amazon's Rufus Experiment Could Reshape Product Discovery

[Ebrun Original] On May 9, according to foreign media reports, Amazon is currently testing a new method of integrating AI into its search function: embedding artificial intelligence directly into the main website search bar, rather than confining it to a separate AI assistant portal.

Currently, some consumers are no longer seeing just the traditional product listings when searching for items. Instead, an AI-generated summary and explanation now appears at the top of the search results. This means users can gain a "conversational shopping guide" experience directly within the main search flow, without needing to enter the dedicated AI shopping assistant, Rufus, interface.

This new attempt, referred to as a "hybrid mode," is seen as Amazon rethinking the relationship between search functionality and AI.

Since launching the AI shopping assistant Rufus in 2024, Amazon has kept it relatively separate from the main search bar: traditional search handles quick product retrieval, while Rufus handles Q&A-style shopping consultation. However, this boundary is now beginning to blur.

Amanda Doerr, Vice President of Amazon's Core Shopping Business, confirmed that the company is researching precisely when to direct consumers to Rufus and when to retain the traditional search results page.

From Amazon's perspective, traditional search and conversational AI are inherently suited for different types of shopping needs.

For example, when a consumer searches for "milk," they are more inclined to quickly get product results and complete the purchase; in this case, efficient, low-distraction traditional search remains most effective. But if a user poses an open-ended question like "how to choose hiking boots suitable for long-distance trekking," conversational AI holds the advantage, as it can perform tasks like understanding needs, explaining parameters, filtering products, and summarizing recommendations.

Amanda Doerr stated that any related adjustments will be implemented gradually, with different strategies for various search scenarios, rather than a sudden, comprehensive switch.

This change has already garnered significant industry attention. If Rufus truly merges with the main search entry point in the future, Amazon's product discovery mechanism could undergo a fundamental restructuring.

For a long time, the core logic of e-commerce search has essentially been "massive display"—platforms show a large number of similar products, leaving consumers to screen, compare, and decide for themselves. However, AI-powered search could change this model. In the future, consumers might no longer face a full page of visually similar, spec-close products, but a smaller number of "curated results" that better match their personal needs.

Noted e-commerce analyst Kaziuk?nas observed that many of Amazon's current AI-generated shopping results often display only about three core products, accompanied by a few alternative options—a method that is clearly more "focused" compared to the traditional search model that exposes hundreds of SKUs at once.

This change holds clear appeal for both consumers and the platform.

On one hand, more selective results could alleviate the long-standing "choice paralysis" problem consumers face on e-commerce platforms, reducing time spent on repeated price comparisons and browsing, thereby shortening the purchase path and improving conversion rates.

On the other hand, for the platform, AI could further strengthen its control within the shopping decision chain—consumers are no longer just searching for products but are directly accepting the "recommended answers" provided by the platform.

However, whether AI search can truly become the default mode still faces several practical obstacles.

The first is a technical issue. The response time for AI-generated results is typically significantly longer than for traditional searches. In high-frequency shopping scenarios, consumers often lack the patience to wait for complex reasoning processes that can take over ten seconds. For a large number of users with clear goals and a pursuit of efficiency, they may not be willing to abandon the highly familiar traditional search experience.

Secondly, a greater challenge comes from the business model itself.

If AI results display fewer products, the number of ad exposure slots the platform can offer will also decrease proportionally. This touches upon one of Amazon's core commercial interests.

Data shows that nearly 70% of Amazon's U.S. advertising revenue this year comes from search ads. In the past, advertisers competed for higher positions on the search results page; but in the era of AI search, the competitive logic could evolve into who can get into the AI's final "recommended answer."

This means the advertising system, traffic distribution mechanism, and brand exposure rules could all be redefined.

In fact, looking across the entire U.S. e-commerce industry, Amazon is not alone in betting on AI to reshape search behavior.

Walmart's AI shopping assistant, Sparky, is also seen as a similar trend. In July last year, Walmart's U.S. CTO stated that Sparky's future "multimodal interface" could ultimately replace traditional search methods.

Finally, a key factor is whether overseas consumers are truly willing to trust AI recommendations.

According to a survey by EMARKETER and Publicis Commerce in January of this year, among U.S. AI users, 52.4% said they trust product recommendations provided by AI assistants or chatbots. However, when expanding the scope to the broader public, market attitudes remain significantly cautious.

According to a Quinnipiac University survey, only 21% of U.S. adults said they trust AI-generated information "most of the time" or "almost all the time"; in contrast, 27% said they "almost never" trust such content.

For sellers and brands, the impact of AI search could be more direct.

Industry insiders point out that although Amazon's current tests are still in the early stages, they could likely "pose significant challenges for sellers in the future."

"Even if Amazon adds sponsored product placements or brand prompts to AI results in the future, under the overarching trend of reduced overall exposure slots, competitive pressure among brands will only increase," said one seller. "We not only need to optimize product pages for Rufus but must also start adapting to a new environment with fewer organic exposure opportunities."

Although Amazon is unlikely to suddenly and completely switch to an AI search model in the short term, as consumers gradually become accustomed to using AI tools, brands already need to start developing strategies to enhance their visibility within Rufus.

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