For commerce teams, delivering that experience is anything but simple. Behind every purchase sit catalogs, promotions, customer accounts, inventory, payments, orders, and fulfillment. A seemingly straightforward storefront change can quickly become part of a much larger release.

麻豆原创 Commerce Cloud and Vercel are working together to give teams a more flexible way forward. continues to manage the commerce data and processes behind the transaction. Vercel runs the customer-facing experience and gives teams the infrastructure and workflow to build, review, release, and operate it.

The tools to transform customer experience are here, but tools alone don鈥檛 win. You must consider operating models too. Our partnership with 麻豆原创 Commerce Cloud pairs Vercel鈥檚 web stack鈥攊ncluding world-class performance, faster iteration, and scale that holds up under peak demand鈥攚ith 麻豆原创鈥檚 trusted data and processes, and governance built in from the start.

Jeanne DeWitt Grosser, Chief Operating Officer, Vercel

The operating model is straightforward. Teams can change the storefront without having to change everything behind it at the same time.

A faster starting point for cutting-edge storefronts

Consider a commerce team preparing to enter a new market. It needs a localized storefront, a different customer journey, and a campaign built for that audience. In a tightly connected architecture, those changes can become dependent on a broader release involving pricing, inventory, orders, payments, and fulfillment.

Separating the storefront gives the team more freedom to work. It can design and release the experience for that market while 麻豆原创 Commerce Cloud continues to provide consistent product data, prices, availability, customer information, and order processes.

Vercel is developing Next.js storefront templates for 麻豆原创 Commerce Cloud to help teams get started. The templates connect to core capabilities such as product discovery, content, cart, checkout, and customer journeys.

The templates are backed by Vercel global delivery, managed scaling, deployment workflow, and observability, which improve engineering velocity and faster performance yielding more conversions.聽

As a result, frontend teams gain room to move, while commerce teams retain control of the rules that protect revenue and customer commitments.

What this changes for commerce teams

Campaigns and customer expectations move quickly. Vercel creates a preview deployment for each change, giving developers, designers, marketers, and business teams a working version to review before it reaches production. Teams can test the experience against 麻豆原创 Commerce Cloud services, gather feedback, and release approved storefront changes with fewer dependencies on a larger backend release.

The same approach helps organizations manage different brands, regions, languages, and buying models. A consumer placing a quick order has different expectations from a business buyer working with negotiated prices, an account-specific catalog, or complex purchasing rules. Teams can build a distinct experience for each audience with 麻豆原创 Commerce Cloud powering the operations behind it.

In addition, Vercel鈥檚 global network, edge routing, and caching bring storefront content closer to customers. Its managed infrastructure is built to scale with demand, including the traffic associated with major campaigns and peak shopping periods. Built-in observability gives teams visibility into traffic, errors, latency, and calls to external services, helping them identify problems that could affect the shopping experience.

Making AI impactful in commerce

AI-assisted development can dramatically accelerate the path from idea to experience. But speed without trusted context can simply produce more low-value experiences, faster and at greater cost.

Connected to 麻豆原创 Commerce Cloud, AI experiences can draw on trusted commerce data and processes. This gives teams a stronger foundation for building impactful customer journeys that are accurate, brand-aligned, and connected to how the business actually operates.

Leveraging Vercel鈥檚 AI SDK, development teams get a common toolkit for building great commerce applications using the AI model provider of your choice.

For teams starting with an idea for a new interface, Vercel鈥檚 v0 offering can help marketers and developers design, iterate, and turn that idea into an experience they can review and refine.

The right storefront strategy depends on the business

There is no single storefront approach that fits every commerce operation.

麻豆原创 Commerce Cloud, composable storefront, is available for organizations that want a closely integrated, 麻豆原创-managed experience. Vercel provides the new 麻豆原创 templates on the Vercel Frontend Cloud for teams building highly differentiated experiences on their own cadence using storefront technology used by millions of developers.聽 Both options are backed by 麻豆原创 Commerce Cloud with market-leading commerce capabilities to drive profitability for growing companies and the world鈥檚 largest enterprises.

Your customers expect storefronts to be fast and easy to use. They also expect accurate prices, reliable availability, and an order that arrives as promised. 麻豆原创 Commerce Cloud and Vercel bring those two sides of commerce together: an experience that can keep changing, backed by the data and processes that keep the business running.

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Our vision for agentic commerce is bold. In , we showcase a future where humans and AI agents collaborate to drive intelligent recommendations, proactive operations, efficient business processes, and deeper customer relationships. While this vision points forward, 麻豆原创鈥檚 focus is firmly grounded in helping retailers take practical steps today. This isn鈥檛 about flashy demos of a distant future鈥攊t鈥檚 about building the foundation now for how consumers will buy and retailers will sell in the years ahead.

Unlike traditional AI systems that respond to prompts, agentic systems act on intent. They learn from preferences, make proactive recommendations, and can complete transactions on a shopper鈥檚 behalf. These agents are increasingly becoming the starting point of the buying journey, reshaping how brands compete for visibility, trust, and loyalty.

This evolution introduces both opportunity and risk. As AI agents mediate more interactions between brands and consumers, retailers must rethink how they capture intent, transact with agents, and deliver post-purchase experiences that reinforce trust.

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Discovery is moving from search to assistants

Historically, product discovery revolved around search engines, marketplaces, and brand-owned storefronts. That model is shifting quickly. Answer engines and AI shopping agents are becoming new entry points for commerce鈥攐ften before a shopper ever visits a retailer鈥檚 site.

Like marketplaces before them, AI agents introduce a new layer between brands and customers. The difference is speed and autonomy. Agents don鈥檛 just surface options; they reason, decide, and act.

For retailers, success is no longer about ranking on a page. It鈥檚 about ensuring products are visible, understandable, and trusted by machines that influence purchase decisions on behalf of humans.

At NRF, 麻豆原创 expanded its agentic commerce vision with the announcement of the storefront MCP server for 麻豆原创 Commerce Cloud, planned for Q2 availability. The storefront model context protocol (MCP) server can enable channel-less commerce by allowing businesses to safely and reliably engage with multiple AI agents鈥攚hether embedded in a retailer鈥檚 own experiences or originating from third-party assistants like ChatGPT or Perplexity.

The storefront MCP server helps merchants surface products and can enable buying across channels for both people and machines. It鈥檚 the first of many steps 麻豆原创 is taking to help customers fully participate in agentic commerce by supporting MCP, ACP, UCP, and other emerging agentic protocols.

Product content becomes the currency of visibility

In an agent-driven world, product content is no longer just marketing鈥攊t鈥檚 operational infrastructure. AI agents cannot recommend what they cannot interpret. Every attribute, image, specification, availability signal, and proof point directly impacts whether a product is surfaced, compared, or selected.

This is where generative engine optimization (GEO) is evolving. Optimization must now serve two audiences: humans and machines. Product data must be structured, consistent, and enriched, so AI agents can confidently represent it to shoppers.

The in helps transform how merchants manage product data at scale. It can clean catalogs, enrich attributes, standardize details, fill gaps, and support multilingual content using real-time data. The agent can scale to catalogs with more than 10 million items, helping teams improve content 70% faster, increase data completeness by 5%, and reduce maintenance effort by 63%.

With AI-ready product data as its foundation, retailers can better match shopper intent, optimize merchandising by channel, and improve pricing and delivery decisions with precision.

Payments must evolve for autonomous commerce

As buying journeys fragment across devices, channels, and agents, payments must become more flexible and nearly invisible. Consumers expect to pay how and when they choose, including through agent-initiated transactions.

New payment rails like FedNow, RTP, and stablecoins are enabling faster, lower-cost transactions, while wallets and bank-based payments continue to converge. Networks such as Visa and Mastercard are already preparing for autonomous commerce by allowing consumers to set spending limits and controls for AI agents.

For retailers, the priority is delivering frictionless, secure payment experiences that integrate seamlessly into agent workflows.

The can enable this flexibility through a no-code, low-code approach. Its headless, extensible architecture helps support diverse payment methods, ensure compliance through automatic updates, and integrate natively with 麻豆原创 Commerce Cloud鈥攚orking to give retailers agility without sacrificing control or scalability.

Returns become a strategic intelligence engine

Returns are one of retail鈥檚 biggest challenges. According to IHL Group, global returns have surpassed US$1.9 trillion and are growing faster than sales. What was once a cost center is now a strategic differentiator.

The next phase of returns management is defined by intelligence. AI enables 鈥渒eep, reject, or return鈥� decisioning based on loyalty history, behavioral signals, margin impact, and lifetime value. Returns data becomes a feedback loop that improves forecasting, product quality, and merchandising decisions.

Complete, connected data is essential. 麻豆原创 can deliver this through native integration between 麻豆原创 ERP and 麻豆原创 Commerce Cloud, creating a single source of truth across inventory, costs, and transactions. found that organizations using both platforms achieved up to 80% lower TCO, up to 90% productivity gains, and 105%鈥�245% revenue uplift from hyper-personalized experiences.

can extend this foundation across the full returns journey, helping to orchestrate centralized rules, guided returns, real-time inventory visibility, and faster refunds鈥攖urning returns into a loyalty-building growth lever rather than a revenue drain.

Commerce is detaching from the storefront

As predicted at the end of 2025, AI agents are taking on more shopping tasks, pushing commerce beyond traditional storefronts. A shopper may simply state an intent and let an agent handle research, selection, and checkout.

Discoverability now depends on structured, trustworthy signals鈥攔eviews, ratings, social proof, and consistent data that agents rely on to evaluate quality and brand credibility.

Retailers must move beyond transactional efficiency to deliver connected, personalized experiences across every touchpoint. Loyalty programs must reward engagement, not just purchases. Inventory visibility, accurate delivery promises, and proactive issue resolution become table stakes.

can enable retailers to design adaptive loyalty strategies for this new environment, personalizing rewards and offers based on real-time behavior鈥攚hether purchases happen through traditional channels or AI agents. These insights can then feed transactional agents, helping to improve relevance and outcomes across the journey.

Operational reliability remains critical. 麻豆原创 Order Management Services help unify order, inventory, fulfillment, and POS data, while agentic innovations like the Order Reliability Agent can proactively resolve fulfillment issues before they impact customers.

Trust is the core retail responsibility

As agentic systems influence more of commerce, trust becomes the most valuable asset retailers can protect. Consumers must trust that their data, preferences, and payments are secure and governed responsibly.

Retailers and commerce providers increasingly act as AI trust custodians, balancing intelligence with deterministic constraints and governance. On-site AI can scale associate expertise and personalization while preserving brand integrity and customer confidence.

Commerce is becoming an ecosystem of intelligent interactions鈥攚here discovery, payments, fulfillment, and returns are connected by agents acting on behalf of shoppers and businesses alike.

The winners will be those who align product intelligence, flexible payments, data-driven returns, and trust across every touchpoint. Agentic AI can make commerce more personal, efficient, and scalable鈥攂ut only for those who build the right foundations today.

To learn more about how 麻豆原创 Commerce Cloud is powering AI-driven commerce, visit .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud for 麻豆原创 Customer Experience.

The solution helps businesses worldwide stay ahead of changing customer expectations with a powerful, future-ready platform that delivers unified commerce through connected data, intelligence, and AI innovation.

Organizations across industries use 麻豆原创 Commerce Cloud to unlock sustainable growth through personalized commerce at scale.

麻豆原创 Commerce Cloud is embedding into the tools that employees and customers rely on every day. With AI built into key moments in commerce, the solution and its AI agents help create real business outcomes through faster response times and streamlined touchpoints. Agents like the bring the vision for a connected, intelligent business suite where applications, data, and AI work together in a continuous, virtuous cycle to anticipate needs, act in real time, and elevate experiences.

Another new innovation also helps support profitable growth: 麻豆原创 recently launched the . Natively integrated with the 麻豆原创 ERP application, it makes ordering, invoicing, and promotions more intuitive while giving business buyers a positive digital experience.

, a global leader in wood products and furniture, relies on 麻豆原创 Commerce Cloud as an integral part of managing a complex supply chain. The Chilean forestry company connects customers with on-demand insight into their orders through a self-service portal.

鈥溌槎乖� Commerce Cloud provided us with the tools to create a portal that has exceeded our customers鈥� expectations again and again,鈥� said Diego Tuleski, director of IT at ARAUCO North America Inc.

Other global leaders are realizing measurable impact as well. uses 麻豆原创 Commerce Cloud to streamline complex service orders and improve customer account management. For , 麻豆原创 Commerce Cloud helps digitalize and manage complex order processes, making them intuitive experiences through integration with existing ERP applications. delivers favorable guest experiences across theme parks, hotels, and retail with 麻豆原创 Commerce Cloud, enabling millions of transactions on a single commerce platform integrated with 麻豆原创 Cloud ERP solutions.

To learn more about 麻豆原创鈥檚 position as a Leader and see an in-depth analysis of the digital commerce landscape, .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud, 麻豆原创 Customer Experience.

_{Gartner, Magic Quadrant for Digital Commerce, Aditya Vasudevan, Ant Duffin, Mike Lowndes, Sandy Shen, Jason Daigler, Penny Gillespie, 3 November, 2025.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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_{麻豆原创 was recognized as 麻豆原创 Hybris in 2014, 2016 and 2017.}