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Shopping is moving from searching for products to asking AI to find and buy them.
Google is now testing a new step in India. Selected users can reportedly see a Buy button for some Flipkart products inside Gemini and Google Search's AI Mode. The button opens a Flipkart-branded checkout flow without making users leave the AI interface. The early test covers a limited set of products and users, with a wider rollout reportedly planned for October.
But the direction is clear.
Google is moving AI shopping closer to the transaction.
The reported test connects three parts of the shopping journey:
AI search → product recommendation → checkout
Users can ask Gemini or AI Mode about products. Selected Flipkart listings may then show a Buy button.
When users tap it, they can enter a Flipkart checkout flow without leaving the AI experience. The test reportedly includes products such as smartphones, electronics, and mobile accessories.
This is different from traditional Google Search.
Before, Google mainly helped shoppers find products.
Now, AI can help shoppers discover, compare, decide, and start buying.
That is the bigger story.
In April, Google said its Shopping Graph contained more than 50 billion product listings, with about 2 billion listings updated every hour. Google also expanded shopping features in Gemini and AI Mode in India, including product listings, comparison tables, prices, reviews, and inventory information.
Then in May, Google introduced Universal Cart and expanded its work on agentic commerce.
Google also introduced the Universal Commerce Protocol (UCP). The protocol gives AI agents and businesses a common way to handle shopping tasks such as product discovery and checkout.
Google's goal is simple:
Make AI capable of handling more of the shopping journey.
Agentic commerce means AI can do more than recommend a product.
It can help complete the buying process.
For example, a shopper might ask:
Find me a lightweight laptop under ₹70,000 with good battery life.
An AI shopping agent could:
Understand the request.
Find matching products.
Compare prices and features.
Check availability.
Recommend suitable options.
Start checkout.
Complete the purchase when the user approves it.
This changes the role of search.
The user may no longer visit ten product pages before making a decision.
The AI could narrow the choices first.
This is where AI visibility becomes important.
In traditional search, brands compete for:
Search rankings
Clicks
Impressions
Website traffic
In AI shopping, brands also need to appear when an AI system recommends products.
That creates a new question:
Will AI recommend your product when a buyer asks what to purchase?
A brand could have a strong website and still miss an AI shopping journey if its products lack clear information, strong reviews, useful product data, or the signals AI systems use to compare products.
This is especially important for AEO and AI visibility.
Earlier, brands mainly asked:
"Does AI mention my brand?"
Now the question is becoming:
"Does AI recommend my product when someone is ready to buy?"
That is a much stronger business connection.
Google is also giving merchants new measurement tools. In July, Google announced AI Performance Insights for Merchant Center. The tool shows merchants how their products perform across AI surfaces such as AI Mode, AI Overviews, and the Gemini app.
Google said in September that AI Performance Insights had become generally available. It also published product-feed guidance for retailers preparing for AI-driven shopping.
This shows that AI visibility is becoming a measurable part of commerce.
Google's latest India marketing research adds another useful signal.
Google says Indian consumers who use AI features move across an average of 13 touchpoints before buying, compared with 5.5 touchpoints for non-AI users.
This matters because AI does not always replace the buying journey.
Instead, it can make the journey more complex.
A shopper may use AI to research a product, compare brands, check reviews, explore alternatives, and then buy.
Brands need visibility across those moments.
The rise of AI shopping changes what product optimization should include.
1. Make product information clear
AI needs useful product data.
Keep product names, specifications, prices, features, sizes, and availability clear and consistent.
2. Answer buyer questions
Do not only describe the product.
Answer questions buyers actually ask.
For example:
Is this laptop good for students?
Which phone has the best battery?
Is this shoe suitable for running?
Which product is better for travel?
This type of content gives AI more useful information to understand your product.
3. Strengthen product data
Keep your product feeds accurate.
Google's AI shopping systems depend heavily on product information, so missing or outdated data can reduce the quality of your product presence.
4. Build trust signals
AI shopping systems need to compare products.
Reviews, product details, expert information, pricing, availability, and brand reputation can all matter in that process.
5. Monitor AI recommendations
Traditional rank tracking is no longer enough.
Brands should track whether AI systems mention them, recommend them, cite their content, and include their products in buyer-focused answers.
SEO is not disappearing.
Instead, the search journey is expanding.
A customer may discover your brand through Google Search, AI Mode, Gemini, an AI recommendation, a product comparison, or an AI shopping agent.
That means brands need both search visibility and AI visibility.
The goal is not simply to rank a product page.
The goal is to make your product easy for search systems and AI systems to understand, compare, trust, and recommend.
Google's Flipkart test points to a larger change in online commerce.
Search engines used to send shoppers to websites.
AI systems can now help shoppers decide what to buy.
Agentic commerce takes the next step by helping them complete the purchase.
That creates a new path:
Search → AI answer → Recommendation → Decision → Transaction
For online brands, every step matters.
The brands that prepare early can measure how AI systems represent their products and where they lose visibility in the buying journey.
Is Google Gemini becoming a shopping agent?
Google is expanding Gemini and AI Mode with shopping and agentic commerce features. The reported Flipkart test in India takes this further by connecting selected product listings to checkout.
Can users buy Flipkart products through Gemini?
A limited test reportedly lets selected users start Flipkart checkout from a Buy button inside Gemini and AI Mode. Reports say Google plans a broader rollout in October.
What is agentic commerce?
Agentic commerce uses AI agents to help with shopping tasks such as finding products, comparing options, and completing purchases.
Why does AI shopping matter for brands?
AI can influence which products shoppers discover and consider. This makes AI visibility an important part of the modern buying journey.
How can brands prepare for AI shopping?
Keep product data accurate, answer buyer questions, build trust signals, improve product information, and monitor how AI systems mention and recommend your products.
The reported Flipkart test is small, but the direction is significant.
Google is building a shopping experience where AI can move from discovery to recommendation and eventually transaction.
For online brands, that changes the meaning of visibility.
Being visible in search is still important. But brands also need to understand how AI systems describe their products, compare them with competitors, and recommend them to buyers.
The future of AI commerce is not only about being found. Brands also need AI systems to recommend their products when buyers are ready to act.