SHIP.com has launched two artificial intelligence tools designed to bring agentic commerce into one of the most operationally complex areas of e-commerce: shipping and fulfillment.

The company announced SHIP AI, an AI-powered shipping manager for online sellers, and SHIP MCP, a Model Context Protocol integration that exposes more than 35 shipping capabilities to Claude and other AI applications.

Together, the tools automate tasks such as order analysis, rate comparison, address correction, label preparation, and tracking. They also allow developers to connect AI agents directly to shipping infrastructure. The announcement is significant because much of the recent discussion around agentic commerce has focused on product discovery and payments. SHIP.com is extending the same concept deeper into the physical fulfillment layer.

That means AI agents are moving closer to handling not only what consumers buy and how they pay, but also how those purchases are shipped.

What Is SHIP AI?

SHIP AI is designed to function more like a digital shipping manager than a traditional chatbot. Instead of simply responding to questions, the system can analyze incoming orders and prepare fulfillment work before the seller begins processing shipments.

According to SHIP.com, the system can determine package details, compare shipping options, correct addresses, flag inconsistencies, and prepare multiple orders for shipment simultaneously. Users can also ask the system to update dashboards, run reports and analyze variables such as shipping costs and delivery times.

Joe DiSorbo, founder and CEO of SHIP.com, described the distinction by saying that a general chatbot provides answers, while SHIP AI is designed to perform operational work. The goal is to move sellers away from manually processing every order and toward reviewing work AI has already prepared.

From Manual Processing to AI-Assisted Fulfillment

Shipping remains one of the most repetitive and time-consuming areas of online retail operations. A merchant processing multiple orders may need to verify addresses, calculate package dimensions, compare rates, select carriers, purchase labels and update order information.

SHIP.com says SHIP AI can automate much of that preparation. The company gives the example of a 20-order batch that could take around 25 minutes to process manually. Depending on the level of automation enabled, SHIP.com says the same batch could potentially be prepared in less than a minute with SHIP AI.

That claim is based on the company's own testing and should therefore be treated as a vendor-reported performance example rather than an independent benchmark.

Nevertheless, the broader operational shift matters. The merchant's role shifts from performing each shipping action manually to supervising and approving AI-generated decisions.

Sellers Retain Control Over Financial Decisions

SHIP.com is not presenting SHIP AI as completely autonomous by default. Financial transactions remain under the merchant's control. Purchasing shipping labels, adding insurance or reloading an account balance normally requires seller approval, and the relevant costs are displayed before the transaction is completed.

This human-in-the-loop approach reflects a central challenge facing agentic commerce. Businesses want AI systems to remove repetitive operational work, but financial authority introduces considerably greater risk. SHIP.com's approach lets the AI analyze and prepare decisions while merchants decide how much authority they are willing to delegate.

According to the company, sellers could gradually expand the degree of automation as they become more comfortable with the system.

Early Adoption Suggests Sellers Are Willing to Test AI Shipping

SHIP AI has been available to SHIP.com users since August 11, 2026. The company says that during the first week of beta availability, more than 30% of orders were purchased through SHIP AI.

This figure does not necessarily mean that 30% of all SHIP.com customers have adopted the technology, nor does it demonstrate long-term adoption. However, it provides an early indication that merchants are willing to experiment with AI-driven shipping workflows when those tools are integrated directly into the software they already use.

SHIP is offering the complete AI experience free to users for at least 30 days during the launch period.

SHIP MCP Brings Shipping Capabilities Directly to AI Agents

The second product may ultimately have even larger implications for agentic commerce. SHIP MCP connects SHIP.com's shipping infrastructure to AI applications through Model Context Protocol. MCP is an emerging standard that allows AI systems to connect with external tools, software and data sources.

SHIP.com says its implementation exposes more than 35 shipping capabilities that developers can integrate into AI applications. These capabilities include rating shipments, creating labels, tracking packages, processing order information and managing shipping workflows.

Rather than forcing users to leave an AI environment and manually open separate shipping software, these functions can potentially operate directly inside the AI application.

Claude Users Can Access SHIP.com Shipping Functions

SHIP MCP is available through Claude Desktop CLI and can also be found by searching for SHIP.com within Claude's connector directory. Developers can additionally access the technology directly through SHIP.com when building their own AI applications.

SHIP.com says some early customers have already embedded its capabilities into their own AI applications, enabling orders to be rated, labeled and tracked through those systems. DiSorbo described these integrations as early steps toward fully autonomous agentic commerce.

The distinction matters. SHIP AI primarily focuses on making existing merchant shipping operations more efficient, while SHIP MCP could make shipping itself a machine-accessible service that autonomous AI agents can call.

Agentic Commerce Moves Beyond Checkout

This development reflects a broader shift across e-commerce. Many of the highest-profile agentic-commerce initiatives have concentrated on the early stages of the customer journey. AI agents can increasingly discover products, compare alternatives, recommend purchases and initiate payments. Companies including Stripe, Alipay and major AI providers are already building infrastructure around these interactions.

But purchasing a physical product creates another requirement: the item still needs to leave a warehouse and reach the customer. A genuinely autonomous commerce system eventually needs access to inventory, fulfillment systems, shipping rates, carrier networks, delivery estimates, labels, tracking information, and returns processes.

SHIP.com is attempting to make part of that logistics infrastructure directly accessible to agents. The emerging agentic-commerce stack could therefore begin to resemble Discovery → Decision → Payment → Fulfillment → Delivery, rather than stopping once the transaction is authorized.

The Logistics Layer Could Become Machine-Readable

Agentic commerce also changes the way logistics technology needs to function. Most shipping platforms were originally designed for humans. A user logs into a dashboard, reviews orders, chooses a carrier, generates a label, and manages exceptions through a graphical interface.

AI agents require something different. They need structured, programmatic access to shipping capabilities so they can evaluate different options and perform actions automatically. SHIP MCP represents one approach to solving that problem. Rather than requiring an agent to navigate a human-designed web interface, the system exposes specific shipping actions through standardized tools.

That could eventually allow an AI agent to determine that a particular order needs expedited delivery, one carrier offers a better rate, an address needs correcting, or an alternative service would meet the customer's requested delivery date. The agent could then act on that information within predefined limits.

What This Could Mean for E-Commerce Sellers

For merchants, the immediate benefit is operational efficiency. Shipping teams spend a lot of time on repetitive tasks that follow predictable rules. AI systems are particularly well suited to analyzing those workflows and preparing recommended actions.

But the longer-term implications extend further. As agentic commerce develops, merchants may increasingly operate in environments where software agents communicate directly with logistics platforms.

Instead of a human seller manually selecting a shipping method, an AI system could optimize thousands of shipments based on cost, speed, service level, and delivery probability. Smaller merchants could access capabilities that previously required dedicated logistics teams, while larger businesses could use agents to manage significant order volumes and let human employees focus on exceptions and strategic decisions.

AI-Driven Shipping Still Introduces Risk

Autonomous fulfillment also introduces important limitations. SHIP.com's own terms explicitly warn that AI-generated outputs may be inaccurate, incomplete or outdated and may not always reflect current carrier rules or rates.

Users are therefore responsible for reviewing and approving AI-generated outputs, including shipping labels, addresses, rate selections and customs or regulatory classifications. That is particularly important in cross-border commerce. Incorrect customs information, classifications or addresses can result in delays, additional costs or regulatory problems.

SHIP.com's terms also address automated clients such as AI assistants and autonomous agents. Actions carried out by an authorized automated client can be treated as actions taken by the user. As businesses give agents greater authority, questions of accountability will consequently become increasingly important.

Shipping Platforms Could Become Infrastructure for AI Commerce

The most important aspect of SHIP.com's announcement may not be automated label creation itself. It is the idea that AI systems can call logistics capabilities directly. That turns a shipping platform from a traditional software interface into infrastructure that autonomous commerce applications can use.

The same transformation is already occurring elsewhere in e-commerce. Payment companies are building agent-compatible payment mechanisms. Marketplaces and retailers are exposing product information to AI systems. AI platforms are creating tools that allow consumers to discover and purchase products without leaving a conversational interface. Shipping represents another piece of that puzzle.

The Next Phase of Agentic Commerce Reaches the Warehouse

Agentic commerce has often been presented primarily as a change to the shopping experience. Consumers tell an AI assistant what they want, and the assistant searches for the best option. But commerce does not end when the shopper presses, or no longer presses, the checkout button. Orders still need to be processed, packed, shipped, tracked, and delivered.

SHIP.com's new tools show how AI agents are beginning to move into that operational layer. SHIP AI focuses on automating the work merchants currently do inside shipping software. SHIP MCP goes one step further by allowing external AI applications to interact directly with shipping capabilities.

If this model expands, logistics platforms could increasingly become invisible infrastructure behind AI-driven commerce. The customer may interact with an AI assistant, the merchant may approve only exceptions, and software agents could manage much of what happens between the purchase and the doorstep.

For e-commerce, that would mark an important evolution in agentic commerce: from automating the transaction to automating its fulfillment as well.

The post SHIP.com Brings Agentic Commerce Into E-Commerce Fulfillment With New AI Shipping Tools appeared first on Cross-Border Magazine.

Alipay has launched what it calls China’s first full-stack agentic commerce platform, introducing new infrastructure designed to help merchants shift from conventional digital commerce to operations increasingly managed and accessed by artificial intelligence agents.

The platform was presented at Alipay’s AI Ecosystem Partner Conference and brings together tools that make businesses' products, services, workflows, and payment capabilities accessible to AI agents. According to Alipay, businesses with different levels of AI maturity can adopt different components of the system, rather than building their own agentic-commerce infrastructure from scratch.

The announcement represents another step in the rapid development of agentic commerce in China, where Alipay has already been developing AI-native payment technologies, trust protocols and consumer-facing AI agents.

What is Alipay’s agentic commerce platform?

Traditional e-commerce has largely been designed around humans interacting directly with websites, apps and marketplaces.

Agentic commerce introduces another layer: AI agents that can search, compare, select and potentially purchase products or services on behalf of consumers.

Unlike conventional chatbots, agentic AI systems can interact with external software and perform actions toward a defined objective with limited human supervision.

For merchants, this creates an important technical challenge. A product being visible on a website or searchable through Google does not automatically mean that an AI agent can understand the service, determine whether it is appropriate for the user, and complete the required transaction.

Alipay’s new platform is intended to bridge that gap. The company says merchants without their own AI capabilities can use a one-stop solution to convert product and service processes into tools that AI agents can understand and invoke. Alipay describes these as agent-ready Skills and MCP-based tools.

This could allow merchants to make existing commercial services available through emerging AI interfaces without rebuilding their entire technology stack.

From digital storefronts to AI-accessible businesses

One of the most important implications of agentic commerce is that the traditional online storefront may no longer be the only interface between a consumer and a merchant. Instead of opening several websites and comparing products manually, a consumer could potentially tell an AI assistant:

“Find me the best hotel near my meeting, book it within my budget and pay using my preferred payment method.”

The AI agent would then need to interact with multiple businesses, evaluate availability and pricing, verify relevant information and complete the transaction. For this model to work at scale, merchants need infrastructure that can communicate with those agents.

Alipay is positioning its new platform as part of that infrastructure. Its approach combines merchant services, AI tools, payment capabilities, identity systems, risk controls, and transaction infrastructure to support the entire agent-driven commercial process.

Ah Bao becomes a gateway to Alipay’s AI commerce ecosystem

A major part of Alipay's strategy is Ah Bao, the company’s consumer-facing AI service agent. Launched in June 2026, Ah Bao provides access to more than 10,000 AI-enabled everyday services, Alipay says. Consumers can use natural-language conversations to do everything from paying utility bills and locating electric-vehicle charging stations to booking services.

Alipay is now developing Ah Bao as a gateway connecting consumers with businesses participating in its agentic ecosystem.

This marks an important difference between generative AI assistants that simply recommend a service and systems that can actually complete the requested task.

The commercial opportunity increasingly lies in moving AI from recommendation to transaction.

For merchants, participating in these ecosystems may eventually become as important as optimizing products for search engines or marketplaces today.

Businesses may need to ensure not only that consumers can discover their products, but also that AI agents can understand, compare, and transact with them.

Payments are becoming AI-native

Payments are another essential piece of the agentic commerce model.

Earlier in 2026, Alipay introduced new AI payment infrastructure including AI Wallet and Token Pay, designed to enable transactions involving AI agents and AI-powered applications.

The company has also developed an Agentic Commerce Trust Protocol, intended to establish a standardized framework for interaction between AI systems and service platforms.

The challenge is significant.

Allowing an AI agent to make purchases raises questions about authorization, identity, transaction limits, fraud prevention, and whether the AI's actions accurately reflect the user's intention.

Alipay has therefore built security and trust mechanisms alongside its payment infrastructure, rather than treating AI payments as just another checkout method.

This development is not limited to Alipay's domestic ecosystem.

Alipay+ has also introduced an Agentic Mobile Protocol designed to let AI agents initiate payments through compatible digital wallets while users maintain control over spending intentions, budgets, and security.

The infrastructure supports scenarios where AI agents can transact without requiring consumers to manually open a payment application for every purchase.

Why agentic commerce matters for e-commerce merchants

The arrival of full-stack agentic commerce platforms could eventually change how online businesses approach customer acquisition.

Today, e-commerce companies invest heavily in areas such as:

SEO
marketplace optimization
paid advertising
social commerce
mobile applications
conversion optimization

Agentic commerce could add another requirement: AI discoverability and transactability.

An AI shopping agent needs structured information about products, pricing, availability, delivery, returns and payment options before it can confidently select a merchant.

That means product feeds and APIs could become increasingly important parts of customer acquisition infrastructure.

Commerce may consequently evolve from businesses optimizing primarily for human interfaces toward businesses optimizing simultaneously for humans and machines.

Competition for the AI commerce layer is intensifying

Alipay is not developing agentic commerce in isolation.

Technology companies, payment networks, marketplaces and AI providers are increasingly exploring ways for autonomous AI agents to interact with commercial services.

The strategic question is becoming which platforms will control the infrastructure connecting:

Consumers → AI agents → merchants → payments → fulfillment

The companies controlling those connections could gain significant influence over how products are discovered and transactions are routed.

Alipay already occupies an important position in digital payments and consumer services in China, giving it an existing ecosystem from which to develop an agentic commerce layer.

Its latest platform therefore represents more than the introduction of another AI assistant.

It aims to provide the underlying commercial infrastructure through which AI agents can interact with thousands of businesses.

Agentic commerce still faces major challenges

Despite rapid development, fully autonomous commerce remains an emerging model.

Security is one of the largest concerns.

Recent academic research examining agentic-commerce systems has highlighted potential vulnerabilities at the protocol level, particularly when agents interact with credentials, payment systems and external services.

Merchants and payment providers must also address questions surrounding authorization, liability, refunds and disputes.

If an AI agent buys the wrong product, exceeds a budget or incorrectly interprets a consumer's request, responsibility for that transaction could become difficult to determine.

Reliable identity verification and clear user controls will therefore be critical before highly autonomous purchasing becomes mainstream.

The next phase of e-commerce could be machine-to-business

Alipay’s launch shows how quickly agentic commerce is moving from experimentation to commercial infrastructure. The internet was originally designed for humans to visit websites.

Mobile commerce shifted that interaction toward apps. Marketplaces then centralized product discovery and purchasing within large commercial ecosystems. AI agents could represent the next change in that interface.

Consumers may increasingly describe what they want to achieve, while software agents determine which merchants, products, and services can fulfill that request.For e-commerce businesses, that could ultimately create a new competitive requirement. Visibility may no longer be enough.

Merchants may also need to become visible, understandable and transactable to AI agents. Alipay’s full-stack agentic commerce platform is an early indication of what that future could look like.

The post Alipay Launches China’s First Full-Stack Agentic Commerce Platform appeared first on Cross-Border Magazine.

ESW has launched a new agentic commerce solution designed to help international brands make their products discoverable, purchasable and operationally supported inside artificial intelligence platforms.

The cross-border e-commerce provider announced that Microsoft Copilot will be the first integration for ESW Agentic Commerce, allowing participating brands to connect AI-powered product discovery directly with secure checkout and payment capabilities.

The launch represents another important step in the development of agentic commerce: a model in which AI assistants do more than recommend products. They can increasingly compare options, guide purchasing decisions and complete transactions on behalf of shoppers.

For international retailers, however, connecting an AI recommendation to a completed order is considerably more complicated than adding a buy button to a chatbot. Payments, localisation, fraud prevention, import duties, compliance, fulfilment and returns must still operate correctly behind the interface.

ESW is positioning its new Agentic Commerce infrastructure as the layer that manages that complexity.

What is ESW Agentic Commerce?

ESW Agentic Commerce is a new infrastructure solution intended to connect retailers’ existing e-commerce operations with AI-powered shopping environments.

The system allows brands to integrate and optimise their product catalogues for discovery by AI platforms. Once a shopper finds a suitable product, the transaction can be completed securely within the AI experience rather than requiring the customer to move to a separate retailer website.

According to ESW, the solution works alongside a retailer’s existing e-commerce infrastructure. Brands therefore do not need to replace their current commerce platform to participate in AI-assisted shopping channels.

The technology is supported by the ESW Agentic Hub, which acts as an infrastructure layer connecting AI agents with the company’s international commerce capabilities.

Through this layer, AI platforms can potentially access the product, checkout and operational services required to move a shopper from initial discovery to a completed cross-border order.

ESW says Microsoft Copilot will be the first integration, with support for additional agents and platforms expected in the coming months. The service is immediately available to brands and customers in the United States, while broader availability is planned.

Microsoft Copilot becomes the first integration

Microsoft has been developing Copilot into a transactional shopping environment rather than limiting it to search, recommendations and product comparisons.

Copilot Checkout allows shoppers to discover, evaluate and purchase products without leaving the conversational interface. Microsoft says the merchant remains the merchant of record and retains ownership of the transaction, customer data and commercial relationship.

The ESW integration extends this concept towards international commerce.

A customer could theoretically ask Copilot for a product recommendation, compare several options, select an item and complete the purchase inside the same conversation. ESW would then provide the underlying international commerce infrastructure required to process and support the transaction.

That infrastructure can include:

• Localised checkout experiences
• International payments
• Fraud management
• Duties and tax calculations
• Regulatory compliance
• Cross-border shipping
• Fulfilment
• Customer service
• International returns

The customer may experience the journey as a simple conversation, but the transaction still depends on a complex network of commercial and logistical systems.

This operational layer is particularly important when the shopper, merchant, payment provider and delivery destination are located in different countries.

From conversational search to conversational checkout

Generative AI has already changed how some consumers research products. Shoppers can ask an AI assistant to compare specifications, interpret reviews, recommend suitable products or narrow a large catalogue according to highly specific requirements.

Until recently, however, most AI-assisted shopping journeys ended with a link.

The AI could recommend a product, but the shopper would usually have to leave the conversation, visit the merchant’s website, find the correct product again and proceed through a conventional checkout.

Each additional step created an opportunity for the customer to abandon the purchase.

Agentic commerce attempts to remove that separation between discovery and transaction. Instead of acting primarily as a search interface, the AI assistant becomes an active participant throughout the purchasing journey.

Microsoft reported that shopping journeys involving Copilot produced 53% more purchases within 30 minutes of an interaction than journeys without Copilot. When clear shopping intent was present, journeys involving Copilot were reportedly 194% more likely to result in a purchase.

These figures were published by Microsoft and should be interpreted as early platform data rather than independent measurements of the wider e-commerce market. Nevertheless, they suggest that reducing the distance between product recommendation and checkout could have a measurable effect on conversion.

Why agentic commerce is especially relevant to cross-border retail

Domestic transactions are already complicated. International orders add multiple layers of friction and risk.

A product recommended by an AI assistant may be available in one country but restricted in another. The displayed price may need to include local taxes, import duties or customs charges. Payment preferences, consumer regulations, delivery options and return procedures may also differ by market.

An AI assistant cannot reliably complete an international order simply by identifying the right product. It must also connect with systems capable of answering operational questions in real time.

These may include:

• Is the product available in the shopper’s country?
• What is the final landed cost?
• Which currency and payment methods should be offered?
• Are import restrictions applicable?
• How long will delivery take?
• Who is responsible for collecting taxes and duties?
• Can the item be returned locally?
• How will fraud and payment risk be managed?

ESW already provides international commerce services covering payments, compliance, localisation, shipping and returns across more than 200 markets. The company says it works with more than 150 global brands and processes more than eight million cross-border orders annually.

Agentic Commerce applies those capabilities to a new customer interface.

Rather than building a separate international transaction system for every AI platform, ESW’s proposed model gives brands a central infrastructure layer that can be extended across multiple agents.

Product data becomes a commercial priority

The emergence of AI-powered shopping will also increase the importance of product data.

Traditional e-commerce search is often built around keywords, categories, filters and paid placements. AI discovery is more conversational and contextual.

A shopper may not search for a particular product name. Instead, the shopper might ask:

“Find me a waterproof jacket suitable for a week in Iceland that fits in hand luggage and costs less than €200.”

To respond accurately, the AI must understand far more than a product title and category. It may need structured information about materials, sizing, climate suitability, weight, delivery availability, price, inventory and return conditions.

Brands whose product information is incomplete, inconsistent or inaccessible to AI systems may become less visible even when their products would otherwise meet the customer’s requirements.

This creates a new optimisation discipline for merchants. In addition to search engine optimisation, marketplace optimisation and feed management, brands will increasingly need to consider how products are interpreted and selected by AI agents.

Important areas will include:

• Accurate structured product attributes
• Consistent descriptions across channels
• Real-time pricing and inventory
• Clear shipping eligibility
• Detailed sizing and compatibility information
• Transparent return conditions
• Verified brand and product information
• Machine-readable commercial policies

In agentic commerce, product data is not merely descriptive content. It becomes part of the decision-making infrastructure.

ESW says retailers can retain their existing platforms

One of the most significant aspects of the ESW proposition is that retailers are not expected to replace their existing e-commerce platforms.

ESW Agentic Commerce is designed to operate alongside the merchant’s current technology stack. The retailer can therefore extend its catalogue and transaction capabilities into AI environments while continuing to use its existing platform for core commerce operations.

This reduces one of the most obvious barriers to agentic commerce adoption.

Large international retailers often operate highly customised systems involving commerce platforms, enterprise resource planning software, product information management, order management, warehouse systems and multiple payment providers.

Replacing that infrastructure solely to participate in a new AI sales channel would be costly and risky.

An integration layer allows retailers to test agentic commerce without treating it as a complete platform migration.

Nevertheless, brands will still need to determine how orders generated through AI interfaces are attributed, managed and measured. Questions around customer identity, consent, marketing permissions, returns and post-purchase communication will become increasingly important as the channel develops.

The retailer must remain visible

Agentic commerce could reduce purchasing friction, but it may also weaken the direct relationship between shoppers and retailers.

When a customer shops through an AI assistant, the assistant may control much of the experience:

• The initial recommendation
• The comparison criteria
• The products displayed
• The explanation of advantages and disadvantages
• The checkout interface
• The post-purchase conversation

This creates a strategic risk for brands. The AI platform could become the primary interface, while the retailer becomes an invisible fulfilment provider.

Microsoft has attempted to address this concern by emphasising that merchants participating in Copilot Checkout remain the merchant of record and retain control of their transaction data and customer relationship.

However, formal ownership of the transaction does not necessarily guarantee control over the customer experience.

Retailers will need to ensure that AI commerce integrations preserve brand identity, communicate accurate product information and create opportunities for continued customer engagement after the purchase.

Otherwise, brands may become increasingly dependent on AI platforms in much the same way that many merchants became dependent on search engines, marketplaces and social networks.

Agentic commerce will create new compliance questions

The ability of an AI system to complete a purchase introduces legal and regulatory questions that conventional product recommendation tools do not face.

Retailers must be able to demonstrate that customers were shown accurate prices, material product information, delivery conditions and return rights before the transaction was completed.

For cross-border orders, the process may also involve:

• Consumer protection requirements
• Data protection rules
• Product safety obligations
• Customs declarations
• Sanctions screening
• Import restrictions
• Tax collection
• Payment authentication
• Accessibility requirements
• Records of customer consent

There is also the question of responsibility when an AI assistant recommends an unsuitable product, presents incorrect information or completes a purchase based on an ambiguous instruction.

The commercial agreement between the retailer, commerce provider and AI platform will need to define how responsibility is distributed.

These issues will become more significant as AI agents gain greater autonomy. Recommending a product is different from selecting quantities, accepting terms, choosing delivery services or authorising payment.

Agentic commerce infrastructure must therefore provide both convenience and traceability.

AI platforms are becoming a new distribution channel

ESW’s launch should be understood as part of a broader shift in e-commerce distribution.

Retailers have previously adapted their businesses for successive generations of digital channels:

• Desktop websites
• Mobile commerce
• Online marketplaces
• Social commerce
• Retail media
• Voice commerce
• Conversational commerce

AI assistants may now become another major entry point.

ESW cites McKinsey research estimating that agentic commerce could represent a global opportunity of between $3 trillion and $5 trillion by 2030. The company also references a Gartner prediction that traditional search engine volume could decline by 25% as consumers increasingly use AI chatbots and virtual agents.

These projections should not be treated as guarantees that AI agents will replace conventional e-commerce journeys. Consumer trust, technical reliability, product coverage and regulatory oversight will all influence adoption.

However, the direction of investment is increasingly clear.

Microsoft, Google, OpenAI, payment companies, commerce platforms and major retailers are all developing systems that allow AI assistants to participate more directly in shopping and transactions.

The strategic question for retailers is therefore shifting from whether AI will influence product discovery to how much of the commercial journey AI platforms will ultimately control.

What retailers should do now

Most brands do not need to rebuild their entire commerce strategy around autonomous AI agents immediately. However, waiting until the channel is mature could leave retailers with significant product-data and infrastructure work to complete.

Retailers preparing for agentic commerce should begin with several practical steps.

Audit product information

Product catalogues should contain detailed, consistent and structured information that AI systems can interpret accurately.

Missing attributes, inconsistent naming and vague descriptions could reduce both visibility and recommendation quality.

Improve real-time data access

AI shopping systems require current information about prices, promotions, inventory, delivery options and geographical availability.

Static or frequently outdated feeds will not be sufficient for transactional experiences.

Review international checkout capabilities

Retailers should assess whether their existing systems can calculate local prices, duties, taxes and delivery conditions in real time.

Agentic discovery will not generate sustainable revenue if customers encounter inaccurate landed costs or failed international orders.

Establish clear governance

Brands should define which actions an AI platform can perform, what information it can access and when customer confirmation is required.

Higher-risk actions should include appropriate human approval or explicit shopper consent.

Protect the customer relationship

Retailers should understand what customer information they receive, how post-purchase communication works and whether they can continue serving the customer outside the AI platform.

Measure the channel separately

Agent-driven traffic and transactions should be distinguishable from conventional search, marketplace and direct website sales.

Without clear attribution, retailers will struggle to evaluate conversion, acquisition costs, repeat purchases and platform dependency.

A significant step, but not the finished model

ESW Agentic Commerce provides a clearer view of how AI-assisted shopping could become operational at an international scale.

The announcement moves the conversation beyond experimental chatbots and product recommendations. It focuses on the less visible infrastructure required to turn an AI interaction into a compliant, fulfilled and serviceable transaction.

Microsoft Copilot gives ESW an established AI interface through which to launch the solution. ESW contributes the international checkout, payment and operational capabilities required behind that interface.

The initial availability is currently limited to the United States, and broader adoption will depend on how quickly additional markets, retailers and AI platforms are integrated. Questions also remain regarding customer ownership, compliance, attribution and the influence AI assistants will have over product selection.

Even so, the direction is important.

E-commerce is entering a stage in which the storefront may no longer be a website, app or marketplace page. It may be a conversation.

For international brands, success in that environment will depend not only on whether an AI assistant can find their products, but whether the entire cross-border transaction can operate correctly after the recommendation is made.

The post ESW Launches Agentic Commerce with Microsoft Copilot, Connecting AI Discovery to Checkout appeared first on Cross-Border Magazine.