Strategy

How AI Shopping Assistants Are Reshaping E-commerce

The first step of shopping is moving from the search box to the chat window. The assistant no longer just recommends; it completes the purchase inside itself.

AI shopping assistants are the new front door of shopping: the user describes a need in conversation, and the assistant does the comparing and, increasingly, the buying. Industry measurement shows the speed of the shift clearly: AI use in product discovery grew up to forty-fold within a year, and one in three shoppers now uses AI to find products. For an e-commerce brand, this means the first step of traffic is moving from the search box to the chat window.

Where does assistant shopping stand today?

Three big moves define the picture. ChatGPT embedded checkout directly into the conversation and processes tens of millions of shopping queries daily. Amazon added automatic buying to its own assistant. Perplexity pushes forward with an AI browser that can shop. At the same time, boundary wars have begun: large marketplaces block rival assistant crawlers, and the disputes have reached the courts.

AI usage in product discovery100 endeks20222023202420252026Illustrative index
Illustrative trajectory of AI use in product discovery: from marginal behavior to mainstream in a few years.

What is agentic commerce?

Agentic commerce means the assistant does not stop at recommending: it picks the product, builds the cart and completes payment on the user's behalf. The critical consequence: the user may never see the brand's website. Your product page, promo banners and cross-sell flows are out of the loop; the data you send the assistant becomes your shop window.

The four steps of assistant shopping1Asks aquestionDescribes theneed to theassistant2AssistantcomparesGathers productsfrom sources3RecommendsA few productsarrive withreasons4CompletespurchaseCheckout endsinside theassistant
The four steps of assistant shopping: question, comparison, recommendation and in-chat checkout.

What decides visibility inside assistants?

When assistants pick results, they look at data quality rather than an ad auction. Five factors stand out, and all are in your control.

  • Product data: a clean feed with accurate price, stock and attributes; dirty data means invisibility to an assistant.
  • Own-site health: a fast, crawlable store serving structured data.
  • Quotable content: pages with clear definitions, comparisons and concrete numbers; assistants draw on these when composing answers.
  • Reviews and ratings: carry visible weight as trust signals in assistant recommendations.
  • Price competitiveness: because the assistant does the comparing, price gaps become instantly visible.
What decides visibility in assistants78 %Cleanproduct data64 %Strong ownstore47 %Quotablecontent33 %Solidreviews21 %CompetitivepriceIllustrative index
Illustrative weight of the factors deciding assistant visibility; product data leads.

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What changes for the advertiser?

Three shifts are already visible. First, part of discovery traffic is moving to assistants; the shift that started with informational queries is expanding into product searches. Second, with purchases that end without a click, last-click measurement goes blind; the assistant-driven share of sales needs its own tracking. Third, assistant platforms are starting to build their own promotion models; brands that move early learn that inventory while it is cheap. We covered the parallel shift on the search side in our AI Overviews piece.

How do brands prepare now?

  1. Perfect the feed: price, stock and identifier errors cost double in the assistant era; feed optimization is step one.
  2. Build quotable content: question-form headings, clear definitions and concrete numbers; the method is in our GEO guide.
  3. Strengthen your own store: reduce marketplace dependence; your own storefront is the channel where assistant access does not get shut off.
  4. Measure assistant traffic separately: track assistant-driven visits and sales as their own segment; let its growth rate steer your investment decisions.
~40x
year-over-year growth of AI use in product discovery (industry measurement)
1 in 3
shoppers now using AI to find products
In-chat checkout
the defining step of agentic commerce

Is panic required?

No. Assistant commerce is growing fast but still makes up a small slice of total e-commerce; search, social and marketplaces are not going anywhere. The right posture is not shifting budget in panic but making your data readable to assistants and measuring the share regularly. That preparation is cheap, and when the assistant share grows, it puts the prepared ahead.

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Frequently asked questions

How do my products show up in an AI assistant?
Assistants compose results from clean feed data, crawlable site content, reviews and price comparison. Strengthening those signals is the main path today; some assistant platforms have also begun announcing their own promotion models.
Can I measure sales that happen through an assistant?
Partly. Assistant traffic can usually be identified by referral source; for purchases that end inside the chat, the signal is limited. Tracking assistant-driven visits as a separate segment and reporting its share per period is the most practical approach today.
I sell on a marketplace, why invest in my own site?
Because some marketplaces block assistant crawlers, what appears in assistants is often the data of independent stores. Your own site is the one shop window you control in the assistant era.
What if assistants show wrong or outdated information?
Fix the source: assistants feed on your site and your feed. Keeping price and stock current and publishing clear, dated information on product pages reduces wrong displays.
How should this change my ad budget?
For now, add measurement rather than shifting budget: track the assistant-driven share of traffic and decide on its growth trend. Feed and content preparation costs little and should happen now.

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