Agentic Commerce is a new digital shopping model in which AI agents act on behalf of consumers, handling the entire journey from product discovery to checkout with minimal user input. Unlike traditional e-commerce, where people must manually search, compare, and transact, Agentic Commerce lets AI automate these steps to maximize convenience for both businesses and shoppers.
You can think of it as a shopping assistant that deeply understands customer preferences, respects budget limits, and can manage even complex purchase decisions with high precision. Rather than a human, this assistant is an autonomous AI agent that independently navigates the buying process, from finding suitable options through to completing the purchase.
Agentic Commerce: What it means for businesses and consumers
Agentic commerce is reshaping how value flows between companies and their customers by letting AI agents act as the primary decision-makers in many transactions. Its impact looks very different depending on whether you are a business or a consumer:
What agentic commerce means for businesses
For businesses, agentic commerce creates a powerful new channel to reach and serve customers through their AI agents rather than only through human browsing behavior. Instead of optimizing solely for human attention, companies must now make their products and services discoverable and competitive in a machine-mediated environment where AI agents compare options on behalf of users.
Global retailers are already recognizing this shift and preparing to respond. Most see AI agents becoming the dominant interface for customer interactions. In fact, 68% of companies believe AI agents will handle most of their customer interactions within the next five years.
As agents take over repeat purchases and subscription reorders, businesses can benefit from more stable, predictable demand patterns. Using standard ecommerce metrics, one study estimated that even at a 5% conversion rate, AI agents could generate around 2.5 million daily orders. At a more aggressive 20% conversion rate—consistent with high-intent conversational queries—daily order volume could exceed 10 million.
Agentic commerce also enables hyper-personalized engagement. Companies can deliver highly relevant offers directly to an individual’s AI agent based on real-time signals, such as current context, historical behavior, and evolving preferences, increasing the likelihood of conversion and long-term loyalty.
What agentic commerce means for consumers
For consumers, agentic commerce represents a major leap in convenience. AI agents can learn each user’s preferences—including style, price sensitivity, brand affinity, and delivery constraints—and use that knowledge to make highly tailored purchasing decisions on their behalf.
Instead of manually searching, comparing, and completing transactions, users can delegate entire shopping workflows to their agents. Consider a simple example: a user wants a new pair of running shoes. Their AI agent can analyze past purchases, fitness goals, and budget, then scan online stores to identify the best options that match preferred brands, styles, and sizes.
The agent then compares prices across retailers, checks stock availability, and reviews ratings and customer feedback before selecting the top option. It can complete the purchase, arrange delivery, and provide tracking updates—all without the user needing to intervene. This reduces friction in the buying process and cuts down on decision fatigue, while still keeping outcomes aligned with the consumer’s needs and constraints.
Adoption of agentic shopping technologies is already accelerating. According to Adobe, traffic to US retail sites from GenAI browsers and chat services increased by 4,700% year-over-year in July 2025. These users also engage more deeply with retailers: they spend 32% more time on-site, browse 10% more pages, and show a 27% lower bounce rate, indicating that agentic commerce is not only growing but also changing how consumers interact with online shopping experiences.
Stand on the shoulders of retail and AI giants
Major players in the AI ecosystem such as ChatGPT, Perplexity, and Google Gemini are rapidly embedding commerce functionality into their platforms. Perplexity, for example, has rolled out a suite of shopping features aimed at improving the online buying experience for U.S. users.
Its Buy with Pro option enables seamless checkout directly on the platform for select products and merchants. Users can securely save their shipping and billing information and access free shipping on eligible items. When this option is not available, Perplexity redirects shoppers to the merchant’s website to complete their purchase.
Perplexity also offers Snap to Shop, a visual search tool that identifies relevant products from a photo, helping users find items without knowing the exact terms to search for. When people ask shopping-related questions, the platform responds with clear, objective answers accompanied by product cards that surface relevant items and key details in a straightforward, visual format. These results are driven by AI recommendations rather than paid placements.
ChatGPT is advancing quickly in the same direction. The platform recently introduced its Instant Checkout feature, which allows users to move from product discovery to payment without leaving the chat interface. This capability is initially being piloted with Etsy merchants, with plans to extend to Shopify sellers, highlighting a broader industry shift toward embedded commerce within conversational AI.
At the same time, Google is expanding its AI Mode shopping interface in the U.S. with new agentic capabilities such as real-time price tracking and automated purchasing via Google Pay. These features further reduce the amount of manual effort required from consumers along the buying journey.
This move toward agent-driven commerce is being accelerated by two reinforcing forces: the global scale of platforms like ChatGPT and the massive retail catalogues available through open integrations, particularly with Walmart. While Amazon has chosen to restrict AI shopping integrations, Walmart has stepped into the gap to become the leading product source for conversational agents.
With a catalog of more than 420 million SKUs, Walmart now provides the foundational "agentic digital shelf" for many AI platforms. Recent data indicates that ChatGPT alone drives referral traffic equivalent to roughly 20% of Walmart’s total site visits. This underscores how quickly conversational discovery is becoming a critical channel in retail.
How can retailers prevail in the new AI-driven normal?
As third-party AI agents increasingly shape consumer behavior, retailers must rethink how they secure demand. Winning in this new normal requires a dual strategy: strengthening brand-owned authority while ensuring products, content, and expertise are easily understood by AI systems and visible wherever AI-driven buying decisions occur.
From SEO to GXO and machine-readable visibility
As AI agents mediate more shopping journeys, retailers need a balanced focus on visibility and robust AI and data infrastructure. The shift from traditional search engine optimization (SEO) to Generative Experience Optimization (GXO) means content must be factual, structured, and easy for AI systems to interpret.
According to Boston Consulting Group, structuring information for machine readability helps generative engines accurately retrieve and rank brand content. In parallel, maintaining an active presence on platforms such as Reddit, YouTube, and Quora increases the likelihood that brands will be referenced in AI-generated answers and recommendations.
Tailoring optimization to each AI engine
Retailers should also adapt their optimization strategies to the distinct behaviors of each AI engine. Research indicates that Gemini heavily favors first-party content, drawing 72% of its insights from brand-owned sources. This makes it critical to invest in authoritative, well-organized on-domain experiences. Rich product education, interactive FAQs, and structured data equip AI agents to understand and act on offerings with greater precision.
By contrast, ChatGPT relies on a broader 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 more heavily on affiliate and publisher networks, so retailers must secure visibility within comparison sites, review hubs, and marketplace ecosystems where AI agents often evaluate and rank options.
Ultimately, thriving in the era of agentic commerce involves mastering this dual approach: consolidating authority on owned channels while ensuring the brand’s products and expertise surface naturally wherever AI-driven purchase decisions are made.
Building scalable, intelligent data infrastructures
To support this transformation, retailers also need to build scalable, intelligent data infrastructures that integrate seamlessly with AI systems. One emerging example is the Model Context Protocol (MCP), a standard designed to simplify communication between AI agents and back-end systems.
Instead of updating individual product pages manually, 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 degree of automation accelerates search visibility and performance while reducing the operational burden of manual optimization, allowing ecommerce businesses to redirect resources toward strategic growth.
Future-ready digital commerce with FPT
Recognizing the growing importance of AI in the new age of e-commerce, FPT draws on 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 measurable results for retailers worldwide. FPT’s digital commerce solution ON.E, powered by Sitecore’s OrderCloud APIs and FPT’s technological expertise, helps businesses accelerate time-to-market and improve development efficiency.
With a flexible, scalable headless architecture and pre-built, composable components tailored to specific industry needs, ON.E can reduce costs by up to 55% and cut time-to-market by over 30%. This modular approach enables retailers to quickly adapt, expand, and modernize their e-commerce ecosystems without compromising performance or customer experience.
In addition, ON.E’s advanced AI assistant leverages large language models to analyze user behavior and generate intelligent, data-driven recommendations. This capability supports smarter e-commerce strategies and elevates digital experiences across a wide range of retail sectors.
Explore how FPT enables smarter, future-ready commerce here: https://fptsoftware.com/services/digital-technologies-and-platforms/digital-commerce-and-experience
Conclusion
Agentic commerce is no longer a distant vision but the new operating system of digital retail, where AI agents own the journey from discovery to checkout and consumers simply set the intent. As platforms like ChatGPT, Perplexity, and Google Gemini weave frictionless purchasing into everyday search and conversation, winning attention increasingly means being legible, trusted, and instantly actionable to machines as much as to humans.
To truly prevail in this new normal, retailers must pair GXO-ready content and data with scalable, intelligent infrastructures such as MCP-powered systems that keep offers fresh, relevant, and AI-discoverable in real time. That’s where future-ready foundations like FPT’s ON.E platform become a strategic advantage, turning AI from an experimental add-on into the core engine of growth. The real question now is not whether agentic commerce will reshape your business, but how quickly you choose to reshape your business for agentic commerce.
