Imagine a shopping assistant that fully understands customer preferences, stays within budget, and makes complex purchases - all with precision. Surprisingly, it’s not a human. But instead, it’s an AI agent. This idea is the foundation of Agentic Commerce: a digital shopping model where AI acts independently for consumers. Unlike traditional e-commerce, where users search, compare, and transact manually, agentic commerce enables AI to complete the process from product discovery to purchase with minimal user input.

Agentic Commerce: What it means for businesses and consumers

For businesses, agentic commerce opens up a powerful new channel to reach and serve customers, not as passive browsers, but through their AI agents acting as decision-makers. Rather than optimizing for human attention alone, businesses are allowing their offerings to be discoverable and competitive in a machine-mediated environment. Noticing this trend, most global retailers recognize that they must respond to the shifting landscape. Indeed, 68% of companies believe AI agents will handle most of their customer interactions in 5 years.

As agents make repeat purchases or reorder subscriptions, businesses can benefit from more stable and predictable demand patterns. Applying standard ecommerce metrics, a study calculated that even at a 5% conversion rate, AI agents could generate around 2.5 million daily orders. At a more aggressive 20% rate, consistent with high-intent conversational queries, daily orders could exceed 10 million. Additionally, agentic commerce also allows for hyper-personalized engagement, which enables companies to deliver relevant offers directly to an individual’s agent based on real-time signals. 

For consumers, agentic commerce represents a leap in convenience. AI agents can learn a user’s preferences (such as style, price sensitivity, and delivery preferences) and use that data to make highly tailored purchasing decisions. Instead of manually searching, comparing, and transacting, users can leave entire shopping workflows to their agents. For example, a user is looking for a new pair of running shoes. Their AI agent will analyse past purchases, fitness goals, and budget, then scan online stores to find the best options that match their preferred brands and size. The tool also compares prices, checks stock availability, and reads reviews before selecting the top choice - then completes the purchase, arranges delivery, and provides tracking updates without the user lifting a finger. This reduces friction in the buying process and eliminates decision fatigue, while ensuring that choices remain aligned with the consumer’s needs. According to Adobe, consumer adoption of agentic shopping technologies is increasing quickly, with traffic to US retail sites from GenAI browsers and chat services increasing 4,700% year-over-year in July 2025. And these users are engaging more deeply: they spend 32% more time on the site, browse 10% more pages, and have a 27% lower bounce rate.

Stand on the shoulders of retail and AI giants 

Leading players in the AI ecosystem such as ChatGPT, Perplexity, and Google Gemini are embedding commerce functionality into their platforms. Perplexity has introduced several new shopping features designed to enhance the online purchasing experience for users in the U.S. The Buy with Pro option enables seamless checkout directly on the platform for select products and merchants, allowing users to save shipping and billing information securely and receive free shipping on eligible orders. When this option isn’t available, users are redirected to the merchant’s website to complete their purchase. Additionally, Snap to Shop offers a visual search function that identifies relevant products from a photo, making it easier to find items without needing exact descriptions. When users ask shopping-related questions, the platform provides clear, objective responses accompanied by product cards featuring relevant items and key details presented in a straightforward, visual format, based on AI-driven recommendations rather than paid promotions.

ChatGPT is also advancing rapidly in this space. The platform recently launched its “Instant Checkout” feature, enabling users to move from product discovery to payment without leaving the chat interface. This functionality is initially being piloted with Etsy merchants, with plans to extend to Shopify sellers, signaling a broader shift toward embedded commerce within conversational AI. Meanwhile, Google is expanding its “AI Mode” shopping interface in the U.S. with new agentic capabilities, including real-time price tracking and automated purchasing via Google Pay—further reducing the need for manual interaction in the buying journey.
This shift toward agent-driven commerce is accelerating due to two reinforcing forces: the global scale of platforms like ChatGPT and the vast retail catalogues accessible through open integrations, particularly with Walmart. While Amazon has opted to limit AI shopping integrations, Walmart has seized the opportunity to become the dominant product source for conversational agents. With a catalog of over 420 million SKUs, Walmart now provides the foundational “agentic digital shelf” for many AI platforms. Recent data shows that ChatGPT alone drives referral traffic equal to roughly 20% of Walmart’s total site visits, underscoring the rising importance of conversational discovery in retail.

How to prevail in the new normal? Strategies for businesses

As third-party AI agents increasingly shape consumer behavior, retailers must strengthen their visibility and adaptability to remain competitive. In order to succeed, retailers need a balanced on visibility and robust AI and data infrastructure.
The evolution from traditional search engine optimization (SEO) to Generative Experience Optimization (GXO) demands that retailers present content in ways that are factual and easily interpreted by AI systems. According to Boston Consulting Group, structuring information for machine readability ensures that generative engines can accurately retrieve and rank brand content. In addition, maintaining an active presence on platforms such as Reddit, YouTube, and Quora enhances the likelihood of being featured in AI-generated answers and recommendations.
What’s more, retailers should tailor their optimization strategies to the unique behaviors of each AI engine. Research shows that Gemini heavily favors first-party content - drawing 72% of its insights from brand-owned sources - making it essential for retailers to invest in authoritative, well-organized on-domain experiences. Rich product education, interactive FAQs, and structured data all help AI agents understand and act on offerings with precision. ChatGPT, by contrast, taps into a wider mix of sources, rewarding brands that publish comprehensive, trustworthy content capable of addressing shopper intent across multiple contexts and touchpoints. Meanwhile, Perplexity and Copilot lean heavily on affiliate and publisher networks. This means retailers need to secure visibility within comparison sites, reviews, and marketplace ecosystems where AI agents often evaluate options. Ultimately, thriving in the era of agentic commerce means mastering a dual strategy: strengthening brand-owned authority while ensuring products, content, and expertise appear seamlessly wherever AI-driven buying decisions occur. 
To support this transformation, retailers also need to build scalable, intelligent data infrastructures that seamlessly integrate with AI systems. One of the examples is Model Context Protocol (MCP) - an emerging standard that simplifies communication between AI agents and back-end systems. Rather than requiring manual updates to individual product pages, an AI system powered by MCP can autonomously identify trending products across social media, analyze emerging search patterns, refine product titles and descriptions with precise keyword optimization, generate enhanced meta tags and image alt text, and deploy updates in real time. This advanced level of automation significantly accelerates search visibility and performance while reducing the operational burden of manual optimization, enabling ecommerce businesses to redirect their focus toward strategic growth. 

A future-ready digital commerce with FPT 

Recognizing the growing importance of AI in the new age of e-commerce, FPT leverages over 20 years of industry experience and a global team of 30,000 professionals - including more than 500 engineers specializing in Digital Commerce & Experience - to deliver exceptional results. FPT’s solution ON.E, powered by Sitecore’s OrderCloud APIs and FPT’s technological expertise, accelerates time-to-market and enhances development efficiency for retailers worldwide. With a flexible, scalable headless architecture and pre-built, composable components tailored to industry needs, ON.E reduces costs by up to 55% and cuts time-to-market by over 30%. The solution’s advanced AI assistant uses large language models to analyze user behavior and generate intelligent, data-driven recommendations, optimizing e-commerce strategies and elevating digital experiences across various retail sectors.

Explore how we enable smarter, future-ready commerce here: https://fptsoftware.com/services/digital-technologies-and-platforms/digital-commerce-and-experience