AI Shopping

Example of AI Mode's dive deeper button

AI Mode: The Future of Shopping for Consumers & Businesses

New shopping information in AI Mode helps buyers connect more easily with shopping intent. It is about the query response to answer shopper’s questions.

Online shopping is undergoing a seismic shift, driven by artificial intelligence. I believe that Google’s ‘AI Mode’ is at the forefront of this transformation. AI fundamentally alters how consumers discover and purchase products. This presents both immense opportunities and urgent challenges for retailers.

This article will delve into what AI Mode means for your business and how you can adapt to thrive.

Table of Contents

What is AI Mode Shopping?

We all understand “shopping.” However, since the new term “AI Mode” is coined by Google, let’s look at how the tech giant describes it.

“This new Search mode expands what AI Overviews can do with more advanced reasoning, thinking and multimodal capabilities so you can get help with even your toughest questions. You (shoppers) can ask anything on your mind and get a helpful AI-powered response with the ability to go further with follow-up questions and helpful web links.” – Expanding AI Overviews and introducing AI Mode

Additionally, we have several new terms to grapple with to understand how AI Mode works. I will mention them here and cover them later in my article.

  • Query relevance
  • Passage generation
  • Query Fan-Out
  • Content chunks

New AI shopping methods offer benefits for both shoppers (easier, personalized) and retailers (new opportunities, increased purchase conversions). Commercial shopping intent is gaining a clearer distinction from informational search intents. Shoppers’ product-related questions can be answered in immediate search engine result pages (SERPs).

If Google can find its place in AI shopping transactions, we anticipate that the impact will be big. AI Mode is not only search. Comments from the tech giant signal that this is “transformed search.”

How Does AI Shopping Work?AI Mode shopping - ask anything button

AI shopping experiences use artificial intelligence to enhance and personalize the online shopping path to purchase. Its intent is to create more efficient and user-friendly shopping journeys.

Google explained that “Today we introduced our new shopping experience in AI Mode with inspiring visuals, smart guidance and reliable product data.” 1 The emphasis is mine. With many recent updates within Google Merchant Center Next, for example strict product image requirements, mean that Merchants are forced to provide clean and accurate data.

When your Merchant Center data feed is clean and accurate, this translates into better AI Shopping results for your products. It can be thought of as how Google’s AI helps understand your query and leads you to a purchase you’ll be happy with.

AI shopping mode features include:

  • Virtual try-on experiences. [1]
  • Product recommendations.
  • AI-powered assistants: They assist with product research and comparisons.
  • Price Tracking and Agentic Checkout: AI can monitor prices for specific items and automatically purchase them when they drop to your desired price, according to Google.
  • AI Shopping Guides: These guides give searchers curated information and product recommendations to help inform buying decisions.
  • Improved Search and Discovery: AI can improve the speed of your search to find the right products by understanding your query intent and displaying the most relevant results.

How AI-Powered Discovery is Changing eCommerce

AI tools can unlock time for high-value work AI can’t do, and accelerating your shopping results.

Google AI Shopping Assistants, ChatGPT, Perplexity, and Claude are rapidly transforming how information is consumed. These AI models eagerly crawl the open web, indexing every scrap of product data they can. This data is then often served back to shoppers as AI Overviews or LLM answers. It often means fewer clicks and citations – just the output.

The way consumers shop online is in transformation, driven by artificial intelligence. From AI-powered product recommendations to intelligent shopping agents, the future of e-commerce is now influenced by AI. It may be time to update your SEO AI strategy.

You can show up in a carousel of products, complete with return and shipping details, in stock notice, ratings and prices.

You may be wondering if this really matters to you as a retailer.

Why Does AI Shopping Matter for Retailers?

  1. Qualified clicks that are more likely to convert: While initial AI Overview might limit clicks, the “Dive deeper” button presents a new opportunity for engagement. As more shoppers embrace AI Mode, and dig deeper, they are likely more serious about their purchase intent.
  2. Opportunity for Brand & Product Mentions: Retailers want their products and brand to be the ones the AI mentions, cites, and recommends to shoppers.
  3. Being shoppers’ “go-to source”: It is no longer about simply ranking for a keyword. It is about being the authoritative source that the AI trusts and uses when displaying answers. If you are cited within AI Mode, even without an immediate click, you’re building brand authority and visibility.

Is AI shopping being widely adopted?

Adoption of AI shopping “adoption” requires both consumer behavior and retailer implementation. “71% of consumers want generative AI integrated into their shopping experiences, according to Cap Gemini. [2]

Google AI Mode now processes 480 trillion tokens/month—a 4,948% YoY increase. These numbers are significant and will grow exponentially.

These numbers represent a seismic shift in how search results are generated and consumed. For retailers, this means that if your content isn’t optimized for AI’s deep understanding and synthesis, you may lose sales. Your products and brand risk becoming virtually invisible within AI-powered shopping experiences.

If your content isn’t meticulously optimized for AI’s deep understanding and synthesis, your products and brand risk losing not just clicks, but also crucial visibility. You need authority and presence within these dominant AI-powered shopping experiences.

Shoppers are getting direct answers, not just lists of links to websites. This occurs on the search page. It’s imperative for retailers to be the source of those answers. It’s a new competitive space that surfaces retailers who are the trusted input for those AI answers. A comprehensive marketing plan with AI measurement is essential to track these new forms of engagement and refine your strategy for maximum effectiveness.

Whether you sell shoes, custom kids art, or worry about medical device sales, you need question answering content that is understood by AI Mode.

So, Google is definitely committed to its AI endeavors. But do searchers use it?

Do Shoppers Prefer AI Shopping?

Google says shoppers are liking this. People can click on the “Dive deeper in AI Mode” button to learn more. This ‘dive deeper’ button, often seen in AI Overviews, allows you to explore the AI’s answer in more detail, accessing additional insights or related products that the initial summary might not cover.

When shoppers click on the “Dive deeper in AI Mode” button, they are taken from the condensed, summarized AI Overview (which appears directly on the main search results page) into a more conversational, interactive AI experience. The AI tech giant offers a further explanation.

“Our new AI Mode shopping experience brings together Gemini capabilities with our Shopping Graph to help you browse for inspiration, think through considerations and narrow down products. The Shopping Graph now has more than 50 billion product listings.

Keep an eye out for a price drop notification and, if you’re ready to buy, just confirm the purchase details and tap “buy for me”. Behind the scenes, we’ll add the item to your cart on the merchant’s site and securely complete the checkout on your behalf with Google Pay. This agentic checkout feature will be rolling out in the coming months to product listings in the U.S. ” – Shop with AI Mode, use AI to buy and try clothes on yourself virtually

Additional benefits of AI shopping:

  • Personalized Shopping Experiences: AI can tailor the shopping experience to your individual preferences and needs.
  • Time-Saving: AI can help you find the right products quickly and easily, saving you time and effort.
  • Informed Decision-Making: AI-powered tools can provide you with the information you need to make informed purchase decisions.
  • Convenience: Features like virtual try-on and agentic checkout make shopping more convenient and accessible.

Let’s look closer at the top benefit – ease.

AI integrates into multiple online shopping platforms:

  • Google Shopping Results: Offers AI-powered product recommendations, virtual try-on, and price tracking features.
  • Amazon Marketplace: Provides AI Shopping Guides, AI-powered product summaries, and Rufus, an AI-powered shopping assistant.
  • Perplexity: Offers a Buy with Pro feature that allows users to check out seamlessly on the platform for select products.
  • Shopdev: Provides AI shopping assistant tools for e-commerce businesses.

AI Shopping Intends to Make Purchase Journeys Effortless

The new era of Google AI Mode means new eCommerce business opportunities.

People can ask, learn, and discover anything. AI shopping assistants are rapidly transforming the retail landscape, aiming to make the entire purchase journey more effortless for consumers.

The days of carefully picking through many traditional SERP blue links are behind us. Now people can shop by talking naturally, multisearch started with a product image, or simply circling what they see. With the reasoning power of AI Mode built into Search, people can ask their most complex and nuanced product questions. Search intelligence to helps consumers truly ask anything, like what the cost of returning a product is.

“People can ask, learn, and discover anything.

The days of carefully picking our keywords to search are behind us. Now people can search by talking naturally, with images, or simply circling what they see. With the reasoning power of our Gemini models built into Search, people can ask their most complex and nuanced questions, and Search can understand them.

The only way to win in the new era of Search is with AI-powered campaigns.

The new era of Google Search means new business opportunities.” – What AI-powered discovery in Google Search means for your marketing

Actionable Tips for Retailers

Adapting to AI Search involves gaining content prominence in AI chatbots

Updating your SEO AI strategy may include actions like:

  1. Optimize for AI Overviews and LLM Answers: Focus on creating highly structured, concise, and authoritative content on your product landing pages. This aids AI models to easily process and present as direct answers to buyers’ questions. Currently, it may mean fewer immediate clicks to your site. However, it is key to the shopper’s journey.
  2. Prioritize Product Data Quality: Clean, accurate, and richly detailed product data (images, descriptions, attributes) becomes paramount. Meeting Google Merchant Center Next strict requirements equals clean data.
  3. Embrace ‘Content Chunks’: Design your product pages and informational content with clear, digestible ‘chunks’ of information that AI can easily extract and use for passage generation.
  4. Product schema markup: Add ecommerce schema markup types to reinforce meaning and data clarity. This is especially helpful for similar products.
  5. Strategize to gain product knowledge graphs:“AI Mode” and product knowledge graphs work together in a highly synergistic way.

In fact, AI-fed product knowledge graphs are a foundational element that significantly empowers and enhances AI Mode’s capabilities in delivering intelligent shopping experiences.

Contact us today for a personalized consultation on optimizing your content for AI Mode
651-206-2410

Tips for Creating Citable Content Chunks

  • Use concise, distinguishable and descriptive headings and product descriptions.
  • Make it skimmable and memorable by using bullet points or numbered lists when losing product benefits or uses.
  • Maintain 2–4 sentences per paragraph.
  • AI Mode doesn’t need your full page. It uses individual paragraphs that answer a specific question. Each chunk of text should meet a specific purpose.

This is a ton of work for retailers. So, we need to look at some benefits.

Benefits: why citable content matters to you

Turning on document chunking when creating a data store indexes your data in chunks, allowing for more relevant search results and facilitating Retrieval-Augmented Generation (RAG) systems.

In Google’s “AI Mode,” query relevance surpasses simply matching keywords. It’s about deeply understanding purchase intent and providing comprehensive, summarized answers, versus a list of links.

Is Google AI Mode Revolutionizing Search?

While it may seem revolutionary to search, fundamentally it builds upon previous algorithm revisions. By assessing emerging Google patents, Search Generative Experience (SGE), Featured Snippets, Relation Extraction, Gemini models, Search Lab, and AI Mode in the United States, I find that the core principles are the same.

When you enter text for a query, or speak it, Google AI Mode retrieves and augments results based on the most important passages within the retrieved documents. The way consumers shop online is transforming, driven by artificial intelligence. From AI-powered product recommendations to intelligent shopping agents, the future of e-commerce is now influenced by AI.

The progression is revolutionary for some domains. However, if you’ve earned good brand entity trust, been visible in Featured Snippets, People Also Ask (PAA), AI Overviews, or People Also Search For (PASF), your ability to gain AI Mode rankings may follow.

I believe the emerging difference in AI Mode is “term weighting” and passage generation. Technical terms can be challenging, here’s how this works. Google calculates the importance of words (terms) within a document and across the entire index. This importance is called “term weight.”

In the big picture, while the technology is constantly evolving and becoming more sophisticated, Google’s AI search is a natural progression of its existing systems, rather than a complete reinvention.

“As with any early-stage AI product, AI Mode doesn’t always get it right. For example, in some cases AI Mode may misinterpret web content or miss context, as can happen with any automated system in Search. When this does happen, we encourage you to give feedback through thumbs up / thumbs down so we can continuously improve.”- Get AI-powered responses with AI Mode in Google Search

   

Two main things occur when you ask Google a question using its “AI Mode”:

   

  1. It (intends to) understand your question deeply: It breaks down your sentence into key parts to figure out what you’re really asking.
  2. It finds the most relevant, trusted, and helpful information: It then uses that understanding to pull out the best chunks from all its cataloged information. We call this “query relevance.”

Google Search has frequently shown the searcher the number of searches for a query and highlighted important parts of web pages. Largely, this is how it’s always worked and is not new. AI Mode is better at “relevance”, a key factor in providing a good search experience.

  1. Beginning: Query Augmentation is where Google’s AI Mode starts.
  2. End: And in the end, You don’t get results for your exact query; you get results for the query that Google processes.

According to Andrea Volpini of Wordlift, “Google AI Mode retrieves and synthesizes content at the chunk level—not the page.” [3]

How is Query Relevance in AI Mode Fundamental to AI Shopping?

Basically, AI shopping aims to make your online shopping experience as intuitive, efficient, and personalized as possible. Depending on the product type, it may exceed the benefits of in-person shopping. To achieve this, AI systems need to understand what you’re looking for.

They try to do this even if your initial query is vague or uses natural language instead of traditional product keywords. This is where query relevance comes in.

AI Mode understands purchase intent (beyond keywords) by using:

  • Natural Language Processing (NLP): AI’s NLP capabilities analyze the meaning behind your words. It doesn’t just look for exact keyword matches.
    Contextual Understanding: The AI considers the context of your query. “Summer wedding dress” implies certain styles, fabrics, and formality levels that “casual summer dress” would not.
    Matching Queries to Products (Semantic Search):
    1. Beyond Lexical Matching: Traditional search engines often rely on lexical matching – finding pages with the exact words in your query. AI shopping goes further with semantic search. This means it understands the meaning of your query and matches it to products that have similar meanings, even if the exact words aren’t present in the product description.
    2. Feature and Attribute Extraction: The AI extracts key features and attributes from your query (e.g., “modern,” “A-line,” “running shoes”). It then matches these attributes to the rich metadata associated with products in its catalog.
  • Personalization and User History:
    Learning Your Preferences: As you interact with an AI shopping system, it learns your preferences. This includes your browser history, purchase history, and even stated style preferences.
    Refining Relevance: This personal data is used to refine query relevance. If you’ve previously bought eco-friendly products, an AI might prioritize eco-friendly options when you search for “new kitchenware,” even if you didn’t explicitly mention it in your query.
  • Ranking and Recommendations:
    Relevance Scoring: Once the AI has identified a set of potentially relevant products, it assigns a relevance score to each. This score is based on how well the product’s attributes, descriptions, and user reviews align with the query and your personal profile.
    Dynamic Ranking: The most relevant products are then ranked highest in the search results or recommendations. This dynamic ranking is crucial for ensuring you see what you’re most likely to buy.
    Explicit Feedback: AI shopping systems often incorporate explicit feedback mechanisms (e.g., “Was this helpful?”, “Thumbs up/down”). This involves iterative improvement and feedback loops.
    Implicit Feedback: They also learn from implicit feedback, such as which products you click on, add to your cart, or ultimately purchase.
    Continuous Learning: This continuous feedback loop allows the AI to constantly improve its understanding of query relevance. The intent is to gain more accurate and satisfying results over time.

“In essence, query relevance in AI mode is the engine that drives effective AI shopping. SEO is no longer just about technical savviness. It is no longer just about ranking content. SEO is marketing.” – Jeannie Hill, owner of Hill Web Marketing

AI Mode Anticipates Shopper Needs

By employing the above abilities, AI Mode shows products the shopper might not have explicitly thought of searching for.

Shoppers favor whatever saves them time and effort. In my experience, now there is less sifting through irrelevant results. I experienced a very efficient shopping journey finding a pair of sandals to match my outfit. Formerly there was less query relevance, unless I use filtering. AI shopping would only be a bit more advanced keyword search, failing to deliver on its promise of a truly intelligent and helpful retail experience.

Google has tested preferences and learned what people search for and how.

The main difference now includes the AI process called “passage generation.”

“Passage Generation” plays a crucial role in finding answers to product-related questions, particularly within the context of Retrieval Augmented Generation (RAG) systems.

Think of it like this:

Previously, Google looked at entire web pages to find answers. Now, with passage generation, it’s even better at identifying the most relevant sentences or paragraphs (passages) from those pages. AI-generated answers are provided by organizing themes, contexts, and topics in a hierarchical way, almost like creating an outline of information. Then, it uses complex calculations (“term-weight calculations”) to determine which words and phrases are most important to your query and where to find them within different documents.

Both the shopper and the retailer can leverage AI technologies to make online shopping easier, more efficient, and tailored to individual customer needs.

What this means for shoppers:

For you, the shopper, you gain a more personalized, efficient, and ultimately satisfying journey to finding exactly what you need – every time you shop.

What this means for retailers:

For forward-thinking, agile retailers, embrace AI Mode, because it is already here. It’s an imperative to ensure your products are discoverable, your brand is recognizable, and your business thrives in the evolving landscape of AI-powered commerce. Begin by auditing your product data quality, optimizing for content chunks, and refining your overall SEO strategy to gain AI mentions and visibility.

Structured, strategic “content chunking” is important

Well-structured, easy-to-consume content is a long-standing SEO best practice. It ensures your product information is easily understood and highlighted by AI. It helps people use multisearch for AI-powered shopping answers.

Today, we are calling it “content chunks” or “content in chunks.” You might wonder how we got here.

This is a descriptive term that is actually drawn from Google itself.

Several Google patents mention or incorporate the concept of “content chunks” or related terms like “chunks of media” or “content blocks”. These patents relate to various aspects of data handling and delivery. My assessment is that the meaning and application of “content chunks” is dependent on context.

Google patents that relate to AI Mode “content chunks”:

  1. US20100235472A1 Smooth, stateless client media streaming [4]
    “The client requests uniform chunks of media from the server that include a portion of the media. The adaptive streaming system requests portions of a media file or of a live streaming event in small-sized chunks each having a distinguished URL.”
  2. US20160034549A1 – Hierarchical Chunking of Objects in a Distributed Storage [5]
    “An object is received, which comprises one or more chunks. Each chunk comprises one or more storage blocks. The blocks for a single chunk are stored in a single journal. Global metadata for the object is stored, which includes a list of chunks for the object. Local metadata for the chunk is stored, which includes a block list identifying each block of the plurality of blocks.”
  3. US10623785B2 – Streaming manifest quality control [6]
    “A method that receives a manifest for plural encoded representations of a single content stream, each representation fragmented into plural chunks, each representation comprising a different quality level, the manifest listing a plurality of representations, each representation comprising the plural chunks.” – 2020, active

Chunking for LLMs is the process of simplifying large blocks of text into smaller, semantically coherent segments. Foremost, this makes it easier for readers to consume. Secondly, LLMs are more likely to process/catalog, retrieve, and reference your content.

How do Query Fan-Outs Work in AI Shopping?

Instead of the traditional single-search process for your exact query, AI Mode’s “query fan-out” technique breaks down a complex or nuanced shopping question. This will likely result in multiple, simultaneous sub-queries. These sub-queries intend to uncover various facets of your intent.

In the background, it gathers a comprehensive set of information from a vast data landscape, including Google’s Shopping Graph.

Example I tried:

I asked AI Mode to “help me find summer athletic women’s wear” AI Mode won’t just search for “women’s athletic wear.” Instead, it initiates a query fan-out, running several simultaneous searches to figure out what I want. Google AI Mode asks many questions, just like you can “Ask anything.”

What color?

What size?

What kind of purchase “journey” that I’m interested in – pickleball?

Basically, query fan-out is the intelligence behind AI Mode’s ability to act like sophisticated shopping assistants. The searcher gains more than a simple product listing. AI Mode shoppers see curated recommendations and comprehensive buying guidance. The platform relies on a deep understanding of complex shopper needs.

AI Shopping Intends to Make Search Effortless

“People can ask, learn, and discover anything.

The days of carefully picking our keywords to search are behind us. Now people can search by talking naturally, with images, or simply circling what they see. With the reasoning power of our Gemini models built into Search, people can ask their most complex and nuanced questions, and Search can understand them and help them discover more of the webSearch is going beyond information to intelligence to help you truly ask anything.

New era of Google Search means new business opportunities.” – What AI-powered discovery in Google Search means for your marketing

Put Your Products Front and Center in AI-Powered Shopping Experiences

Need strategic guidance to adapt to AI’s impact on search?

It is key to watch the adoption and impact of AI Mode along with the reach of Google Images, Videos, Question Answer SERPs and informational “chunks” that reach searchers eyeballs. The exponential growth of AI processing means that the window for adaptation is now.

Before your competitors do, call 651-206-2410 to fine-tune your AI Marketing Strategy for Business Growth

Resources:

[1] May 2025, https://blog.google/products/shopping/google-shopping-ai-mode-virtual-try-on-update/

[2] Jan 2025, https://www.capgemini.com/news/press-releases/71-of-consumers-want-generative-ai-integrated-into-their-shopping-experiences/

[3] June 2025, https://x.com/cyberandy/status/1930995322563518629

[4] 2013, active, https://patents.google.com/patent/US20100235472A1/en

[5] 2016, active, https://patents.google.com/patent/US20160034549A1/en

[6] 2020, active, https://patents.google.com/patent/US10623785B2/en