What Google's New AI Mode Means for e-Commerce Retailers

Normally I’d begin a post like this with a joke. You know. Have some overeducated cinephile fun at the expense of other breathless panicked takes on the subject at hand, by starting with a dire movie monologue paraphrase. Something like: My life fades. The vision dims. All that remains are memories. I remember a time of chaos, ruined dreams, this wasted land. But most of all, I remember … Well, I remember the last six to eleven times tech bros promised to "transform everything" with some “revolutionary something” or other, that then just never quite materialized.

In other words, A) I am a big fan of 1981’s The Road Warrior, and B) When Google announced AI Mode at I/O 2025 with that kind of marketing language, my first instinct was a generationally stereotypical eye-roll reserved for yet another promise to have just “fundamentally” upended the search experience, in ways that would radically change how consumers discover what they buy.

So I’m honestly a bit disappointed to have to shift right into Digital Marketing Professional with over a decade of experience mode here, to tell you that this time, the technological innovation we’re gonna discuss might actually warrant, at least some of the usually overwrought hyperbole.

You see, Google's AI Mode really may represent a fundamental change in the way we search and shop online. Not just one more step in the long evolution of search, but a conversational e-commerce interface that could reshape how consumers discover, evaluate, and purchase goods online. And unlike previous AI shopping experiments, AI Mode's integration with Google's Shopping Graph suggests that the infrastructure exists to genuinely make it useful if not popular.

That means that this isn't just another search algorithm update to optimize for. It's a potential restructuring of the discovery-to-purchase pipeline that has powered online retail for over two decades now.

What Do Online Retailers Need to Know About Google’s AI Mode?

Until now, using a search engine meant thinking like that search engine to get good results. You had to translate your complex needs into simple keyword queries, and even use results from multiple searches to make purchasing decisions. Like, if you were traveling from Winnipeg to Wickenburg, Arizona then Wewahitchka, Florida with your beloved Corgi Kirby? You'd search "predators in Arizona," then "predators in Florida ," then "best anti coyote pet protection," then "will a CoyoteVest pet protector work vs hawks or alligators?" Building knowledge and using it to refine subsequent queries. Google AI Mode eliminates the need to translate. Now you can ask your complex, multi-part, questions. "This summer I’ll be traveling from Canada to rural Arizona and then rural Florida with a 4.5 kilo corgi. What kind of special harness, or body armor should I consider buying to protect my pet?"

This shift from step by step search to “conversational” really does “fundamentally” transform product discovery. Instead of having to conduct research across multiple touchpoints. Your website, reviews sites, competitor comparisons, social media, Google AI Mode consolidates that multi-part shopping journey and presents it as a running, personalized, annotated, conversation.

The implications go beyond consumer convenience. Conversational commerce changes the entire shopping journey timeline. Previously e-commerce discovery might take days or weeks as customers research across multiple sessions. AI Mode compresses this timeline into single, extended conversations that can move from initial interest to purchase consideration in minutes.

Does Google AI Mode Upend The e-Commerce Marketing Funnel?

For as long as it’s been a thing online retail has been based on a fairly straightforward customer journey. Awareness that led to consideration and an evaluation that led to a purchase. So Digital Marketing, Content Strategy, and Customer Experience Design (CX) could all just assume that consumers would move through distinct phases with different touchpoints and brand messaging requirements. Google’s AI Mode disrupts that linear online shopping experience by enabling what they’re calling Query Fan-Outs. Thematic or rather simultaneous searches designed to address all of the various aspects of each complex customer query within a single search result.

When I asked it about small pet protective gear for the South and South West in the summer, AI Mode simultaneously researched not only the types of predators and brand options vs them, it anticipated needs based on my likely mode of travel (e.g. car carriers), and that my urban Canadian corgi wouldn’t be used to the gear or weather common to my rural destinations and so returned both cooling tips and cooling product options as well as tips for getting my pet acclimated to bulky protective gear. This parallel processing means consumers can jump between funnel stages rather than progressing through them. So a shopper casually exploring a product category can quickly move to detailed feature evaluations, and even price comparisons.

For Shopify retailers, this compression may demand rethinking content strategies and customer touchpoint designs. Instead of optimizing for different funnel stages, brands need to prepare for customers who arrive already educated about their needs, competitive landscape, and price expectations.

The challenge for e-commerce merchants could soon become meeting consumers wherever they are in their decision-making process rather than guiding them through predetermined shopping journeys. Which would require different kinds of product information, competitive differentiation, and value propositions optimized for conversational queries rather than simply keyword phrases

Why AI Mode’s Shopping Graph Integration May Change Everything

I think previous AI shopping experiments failed because they lacked comprehensive product data and reliable purchasing paths. Like Amazon's Alexa could answer some of your questions about products, but would struggle with complex comparisons and purchase completion. Other chatbots could provide information but couldn't access real-time inventory, pricing, or availability.

That Google's AI Mode is fully integrated with their Shopping Graph solves these restricting limitations. The Shopping Graph contains over 35 billion product listings from retailers ranging from global brands to local shops, with more than 2 billion listings refreshed hourly for accuracy.

This infrastructure enables Google AI Mode to provide current pricing, availability, reviews, and product specifications within spoken-conversational responses. When consumers ask complex questions, they receive answers based on fresh, comprehensive product data rather than static information.

In case you’re panicking about what that may mean for smaller brands and even niche Shopify Merchants in larger niches. I should pause here to note that the sheer scale of Google’s Shopping Graph will mean that AI Mode will surface products from smaller retailers alongside those of major brands, potentially democratizing product discovery. So a well-optimized local retailer's products could appear in AI Mode responses alongside Amazon and other major e-commerce players, based on their relevance to customer queries rather than marketing spend or platform presence.

For Shopify merchants, that will create both opportunities and present challenges. Products with strong reviews, competitive pricing, and detailed specifications have better chances of surfacing in Google AI Mode responses. But this also means competing on product merit and data quality rather than just SEO tactics, paid Search Marketing budgets and smarter Landing Page Design.

The key strategic question for merchants may become how well does our product data perform in conversational contexts? Google’s AI Mode doesn't just index product pages, it understands product relationships, use cases, and customer needs. In other words, that a spiked vest might be too hot on a doggo used to a cold climate. So retailers need product information that answers not just "what is our product?" but "how does our product solve for specific use cases?"

Is Virtual Try-On Technology a Gimmick or Game-Changer?

Virtual try-on tech has existed for a while now, but most implementations felt like marketing gimmicks, interesting demos that provided little practical value for actual purchase decisions. Limited product catalogs, poor image quality, and unrealistic body representations made these tools fun novelties. But. Frankly. Google's virtual try-on tool plain operates at a different level. It works with billions of Shopping Graph Product Listings, powered by custom image generation models that purportedly understand how different materials/cuts behave on different body types.

Shoppers can upload personal photos and virtually try products directly within search results. The technology preserves clothing details how fabrics fold, stretch, and drape while adapting to individual body shapes and poses. It’s a capability that actually addresses one of e-commerce's persistent limitations. Our inability to physically examine a product before buying it. For retailers in the apparel game, virtual try-on may reduce return rates and increase conversion confidence.

Of course the broader implication extends beyond clothing. You see, virtual try-on demonstrates Google AI Mode's ability to simulate real-world product experiences within digital interfaces. This suggests future capabilities for other product categories. Furniture placement in rooms, cosmetic color matching, automotive customization. Retailers should consider how virtual or augmented product experiences might apply to their categories. While not every product needs virtual try-on, many products would benefit from enhanced digital simulation of real-world usage.

Can AI Mode’s Agentic Checkout Become Every Consumer’s Personal Shopper?

Now, if you were to kidnap Kirby the corgi and force me to name the single most impressive or potentially game changing tech tucked into AI Mode, I’d get my favorite turkey bacon addicted dog back then tell you I think it’s probably: Agentic Checkout. You see, Google’s latest agentic commerce preview is essentially a virtual personal shopper that will allow the AI to complete purchases on behalf of its users with their permission and oversight. Yes you read that correctly.

Consumers may now be able to set price targets for specific products, and let the AI assistant monitor pricing across a range of retailers, then notify them whenever products reach their desired price points. Whenever they choose to purchase, the system will add items to merchant carts then complete the checkout process using Google Pay, and get confirmation for each step.

To Sum Up. Google AI Mode’s Agentic Feature Will Purportedly …

• Track and compare product pricing and monitor merchant listings
• Communicate with consumers using price drop notifications
• Add the product(s) to the merchant’s shopping cart
• Auto-fill forms and other purchase details on a user’s behalf
• And finally it will securely complete any transactions using Google Pay

Which, assuming it works as advertised, will either be another experimental digital tool that no real human consumer will ever trust enough to actually use, or it’ll change checkout completely.

It’s a capability designed to transform Google AI Mode from information provider to transaction facilitator. Instead of guiding customers to e-commerce sites for purchase completion, Agentic can handle an entire transaction. So it either will go the way of Buzz, Glass and Picasa or “Kill the Checkout Page” dead as disco. Seriously though. It will probably lower cart abandonment rates by eliminating the inherent friction between product discovery, and completing a purchase.

I’ve never really been a “the sky is falling” aka "Game over, man!" guy, so I don’t really agree that this means that “AI Just Ate the Checkout” by introducing it, but if it catches on, agentic checkout will certainly transform the retailer/consumer relationship. If Google’s AI Mode starts completing purchases on behalf of customers, Shopify Merchants will lose some control over checkout experiences, post-purchase customer communications, and consumer data collection.

The competitive implications of Google’s agentic personal shopper could be significant, to say the least, e-commerce merchants with better pricing and superior inventory management, and fulfillment capabilities will likely benefit from AI that automatically finds and purchases the best products. But retailers reliant on the checkout experience, upselling, or customer relationship building during the purchase process could find themselves (or at least their current business models) pushed aside.

That said, the words doing all the heavy lifting in those paragraphs were the qualifiers. I mean, Google has been playing with and rolling out similar tools for almost a full decade now. You may recall that back in 2017 they partnered with TicketMaster on an experimental rollout that would have purportedly allowed Google Assistant to purchase concert and other event tickets using voice commands. And back in 2021, they introduced Google Duplex in select markets, another AI Assistant, capable of making restaurant reservations and other local business appointments (haircuts, etc) requiring back-and-forth conversations with staff for its users, and neither took off.

How Will AI Mode’s Emphasis on Conversations Over Keywords Impact Paid Search Marketing?

We’re all understandably hyper focused on AI just now, but Google’s in the advertising business, and they’d like to keep being in it, so they have confirmed that Paid Search Ads will appear in AI Mode just as they now appear in AI Overviews. The difference in AI mode will be that your ads will purportedly be “integrated into responses contextually” rather than displayed separately as they are now. Which will shift search engine marketing away from keyword-based targeting to conversational context matching. Which is to say that advertising within AI Mode will require a thorough understanding of customer intent, the way they speak and naturally phrase questions, rather than mastery of how they’ve learned to truncate queries for the benefit of search engines.

Going forward, when consumers ask questions about products, ads need to demonstrate clear relevance to their specific needs rather than be broad keyword matches. This change could benefit retailers with strong differentiation and clear value propositions. Natural language search targeted advertising will certainly increase the costs of SEM campaigns and challenges involved in optimizing them, but reward online retailers who learn to articulate why their products meet use cases, not just the big budget brands.

You Can Start Adapting Your Search Tactics and Content Strategy Now

I don’t think I could stress enough the degree to which how much of the above is simultaneously both an approaching dramatic shift in the literal shape of e-commerce and the sort of product marketing hype I’ve seen go nowhere or push the search ecosystem forward, substantively but “only” minimally, for anyone with a job title other than mine. Google AI Mode's impact will either unfold over months or over years or not at all. But merchants should prepare for a future that will include a transition to natural language voice (and therefore conversational) search immediately.

• Product Information Optimization: Be sure your Shopify store’s product data answers consumer queries as they would be spoken naturally, not just their keyword translations. Include use cases, problem-solved and comparative advantages in product descriptions.
• Review Management: Google’s AI Mode heavily weights customer reviews in product recommendations. That means that customer review collection and customer response management will be critical to establishing and maintaining your online visibility.
• Inventory Integration: Maintaining real-time inventory and pricing data integration with Google’s Merchant Center will ensure that your customers see accurate info in AI Mode.
• Competitive Intelligence: Monitor how competitors appear in AI Mode responses to better understand positioning and messaging that resonates with conversational queries.
• Conversational Content Strategy: Build out content that addresses complex customer questions rather than simply offering product information. Start thinking about product content in terms of customer education and problem-solving rather than as just lists of features.

Strategic Preparation for Long-Term Changes

Beyond digital marketing tactics, e-commerce retailers should prepare for substantive shifts.

• Post-Purchase Experience: If AI Mode is handling product discovery and purchase, retailers must compete on fulfillment, customer service, and ongoing value creation.
• Data Development: Invest in customer data collection and analysis so that you’ll better understand how Google AI Mode is affecting your customer’s behavior and preferences.
• Customer Journey Redesign: Plan for customers who arrive more educated and ready to purchase. Put more focus on conversion optimization and differentiation rather than top-of -funnel awareness.

What Makes AI Mode Different from Previous Search Revolutions?

Ok so again. This could all go nowhere. Trust me. I have set up more Google+ (https://www.forbes.com/sites/stevedenning/2015/04/17/five-reasons-why-google-died/) pages for more brands than I care to admit. Only here’s the thing. Search as it was constituted only a year ago required consumers to learn to speak its language. Google’s AI Mode is an attempt to flip that burden on its head and adapt search to how customers naturally ask questions. It feels different.

Previous virtual shopping tools worked with limited product catalogs. AI Mode operates across billions of products. Earlier AI shopping assistants couldn't complete transactions. AI Mode can handle the entire purchase process. Most importantly, AI Mode leverages Google's existing search dominance rather than requiring customers to adopt new platforms or behaviors. It isn't another app or a service customers need to discover, it is an evolution of tools they already use.

This one could wind up being the biggest challenge for online retailers since mobile ecommerce emerged. The opportunity lies in reaching customers through more natural, helpful interactions that can dramatically improve discovery and conversion. The challenge will require rethinking basic assumptions about customer behavior, marketing strategy, and competitive differentiation.

The merchants who thrive in this new environment will be the ones who embrace the shift from optimization aimed at search algorithms to optimizing around consumer conversations, and who recognize that in a world where Google AI Mode is handling transactions, their real competitive advantage will depend on offering experiences and relationships customers value beyond mere convenience.