Azoma, a London- and Toronto-based technology company specializing in Agentic Commerce Optimization (ACO), has secured $11.2 million in Series A funding to expand its artificial intelligence platform and help global consumer brands improve product visibility across AI-powered shopping assistants.

The investment, announced on October 21, 2026, was led by Puma Growth Partners, with participation from dunnhumby, Twin Path, MaRS IAF, Rank Ventures and Ignite Ventures, alongside angel investors.

The funding comes as artificial intelligence increasingly influences how consumers discover, compare and purchase products online, creating new challenges for traditional e-commerce marketing strategies.

Azoma Secures $11.2 Million to Accelerate Agentic Commerce

Founded in 2022 by former Amazon executive Max Sinclair and machine learning researcher Timur Luguev, Azoma develops technology designed to help brands understand how AI shopping agents discover and recommend their products.

Unlike traditional search engine optimization, which focuses on improving website rankings in search results, Agentic Commerce Optimization aims to ensure that products are accurately represented and recommended by AI-powered platforms.

These include conversational AI applications such as ChatGPT and Google Gemini, alongside shopping assistants integrated into retail platforms, including Amazon's Alexa for Shopping and Walmart Sparky.

Azoma's platform combines AI visibility measurement, product content optimization and performance analysis to help businesses adapt to this emerging commercial environment.

The company reported that its revenue increased almost tenfold over the previous year, while its workforce expanded from 12 to 40 employees across London and Toronto.

Its enterprise customers include L'Oréal, Unilever, Mars, Beiersdorf and Reckitt.

The latest financing follows a $4 million seed round announced in December 2025 and an investment from dunnhumby ventures disclosed in September 2026.

How Azoma Plans to Use the New Investment

The $11.2 million financing will support three principal areas of development: expanding compatibility with AI shopping agents, strengthening product optimization and attribution capabilities, and recruiting additional artificial intelligence specialists.

A central priority will be extending Azoma's technology beyond conventional conversational search platforms to AI assistants capable of carrying out purchasing activities on behalf of consumers.

The company is also developing tools that connect product visibility within AI-generated recommendations to measurable commercial outcomes.

By leveraging dunnhumby's retail data capabilities, Azoma aims to improve its understanding of the relationship between AI-powered product discovery and subsequent sales.

Another component of Azoma's technology is its Digital Twin system, which simulates different AI shopper personas. This enables brands to assess how their products may be presented to shoppers with different purchasing preferences and requirements.

The company is also positioning its platform around emerging commerce interoperability frameworks, including the Universal Commerce Protocol and Agentic Commerce Protocol, which aim to facilitate interactions between AI agents and commercial systems.

Why AI Shopping Agents Are Changing E-commerce Marketing

The expansion of AI-powered shopping assistants represents a significant transformation in how online retailers compete for consumer attention.

Traditionally, e-commerce companies have relied on search engine rankings, sponsored product placements, marketplace advertising and product listing optimization to attract customers.

However, AI shopping agents are increasingly becoming intermediaries between consumers and retailers.

Instead of browsing multiple websites and manually comparing products, consumers can ask an AI assistant to identify suitable options based on price, specifications, availability, delivery conditions or personal preferences.

This introduces a new competitive challenge: products must not only be visible to human shoppers but also accessible, understandable and relevant to the AI systems generating recommendations.

According to Azoma, different AI systems rely on substantially different information sources when generating answers.

The company's analysis of 38 million citations found that editorial content represented 51.9% of citations within Google Gemini but only 7.6% within Google AI Overviews.

Meanwhile, affiliate content accounted for 39.6% of citations generated by Alexa for Shopping, compared with less than 2% across the other engines examined.

These findings suggest that brands cannot assume a single optimization strategy will deliver consistent visibility across every AI shopping platform.

The Five Principles of Agentic Commerce Optimization

To address these challenges, Azoma collaborated with the Digital Shelf Institute to develop a framework structured around five principles of Agentic Commerce Optimization.

Known as the Five C's, the framework focuses on completeness, context, citations, correctness and customer acquisition.

These principles aim to ensure that AI systems have access to detailed product information, understand the relevance of products to specific purchasing needs, reference reliable external information and provide accurate recommendations that can ultimately translate into commercial results.

According to Azoma, the framework is being deployed by 40% of the world's 50 largest consumer packaged goods companies, reflecting growing interest among multinational brands in managing product visibility within AI-driven commerce environments.

Agentic Commerce Could Reshape Global Retail by 2030

The investment in Azoma reflects broader expectations surrounding the economic potential of agentic commerce.

Research projections cited by the company from McKinsey suggest that AI-powered commerce agents could orchestrate between $3 trillion and $5 trillion in global retail revenue by 2030, including as much as $1 trillion in the United States.

Although these figures represent projections rather than realized transaction volumes, they illustrate the potential scale of a market in which artificial intelligence systems increasingly participate in purchasing decisions.

For retailers and consumer brands, the implications extend beyond marketing.

As AI agents become more involved in purchasing processes, businesses may need to reconsider how they structure product catalogs, maintain inventory information, communicate delivery options and distribute product data across external platforms.

For cross-border e-commerce businesses, this evolution could create opportunities to improve product discovery across languages and national boundaries, provided AI assistants can reliably interpret regional availability, pricing and fulfilment conditions.

What Azoma's Funding Means for the Future of E-commerce

Azoma's latest funding round highlights increasing investor interest in the infrastructure required to support AI-driven purchasing experiences.

While conventional e-commerce technology has historically focused on storefronts, payments, logistics and marketplace integrations, agentic commerce is creating demand for platforms that help businesses remain competitive within AI-generated recommendations.

This transition could prove particularly relevant for multinational consumer brands managing thousands of products across different retailers, marketplaces and geographic regions.

Nevertheless, the commercial impact of agentic commerce will depend on consumer adoption, the reliability of autonomous purchasing technologies and the ability of retailers to connect AI interactions with completed transactions.

With $11.2 million in additional financing, Azoma is positioning itself within an emerging segment of e-commerce technology where product visibility may increasingly depend not only on search rankings but also on how effectively AI agents understand, evaluate and recommend products.

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Artificial intelligence agents have completed more than 138 million blockchain transactions through Coinbase's x402 payment protocol on the Base network, according to new research published by blockchain analytics company Chainalysis on October 14, 2026. The findings highlight the rapid development of autonomous payment systems that let AI-powered software buy digital services, access information, and complete transactions without human intervention for every payment.

The research, published as part of Chainalysis' 2026 analysis of cryptocurrency adoption in North America, shows machine-to-machine payments moving beyond early experimentation toward more regular commercial activity. More than 87% of the transactions examined involved payments worth between $0.0001 and $0.10, demonstrating the importance of low-cost payment infrastructure for AI systems that frequently purchase small amounts of data, computing capacity, and other digital resources.

Although these transactions don't match conventional retail purchases, their growth signals a key development in agentic commerce: AI systems are becoming economic participants that can manage limited spending decisions and purchase services as part of automated workflows.

Blockchain payments by AI agents exceed 138 million transactions

Chainalysis found that cumulative transactions using the x402 protocol on Base had exceeded 138 million by its 2026 reporting period. The figure represents a substantial increase from the approximately 1,500 transactions recorded in mid-2025, when the technology was still in its earliest stages of adoption.

Developers and businesses have driven the expansion by experimenting with autonomous software capable of making payments directly to online services. Instead of requiring a human user to manually authorize every transaction, an AI agent can use a funded digital wallet to purchase resources as needed to complete an assigned task.

For example, an AI system conducting financial research might need access to a premium market-data service. A software development agent might need a code review, while another assistant might need to buy more computing capacity or access a specialized AI model. Through compatible payment infrastructure, these transactions can occur automatically within the agent's workflow.

However, the headline figure requires an important distinction. The 138 million transactions represent the number of payments processed through x402 on Base, not the monetary value of those payments. They should not be interpreted as $138 million in revenue or as 138 million consumer shopping orders.

Chainalysis also identified substantial speculative activity during the protocol's early development, particularly involving cryptocurrency tokens. Consequently, transaction growth alone does not establish the scale of commercially productive AI activity.

Nevertheless, the research provides measurable evidence that autonomous payment infrastructure is attracting sustained interest.

How Coinbase's x402 protocol enables autonomous payments

Coinbase introduced the x402 protocol in May 2025 to enable automated payments directly through internet requests. Its name references HTTP status code 402, traditionally associated with the concept of payment being required to access an online resource. The technology allows software applications and AI agents to purchase services without relying on conventional subscription arrangements or repeated manual payment procedures.

When an agent requests access to a paid resource, the service can respond with payment instructions. The agent then evaluates the request, transfers the required amount through a supported blockchain payment mechanism, and provides confirmation to access the resource. Payments commonly use stablecoins, including USDC, which are designed to maintain a relatively stable value against a reference currency such as the US dollar.

The protocol supports multiple blockchain networks, though Base, developed by Coinbase, has emerged as a particularly active environment for x402 transactions. This architecture's economic significance lies in its ability to support very small payments at relatively low settlement costs.

Traditional payment cards are designed primarily for consumer and business transactions involving amounts large enough to justify processing fees and other operational expenses. Payments worth fractions of a cent are generally uneconomical through conventional card infrastructure. Blockchain-based settlement systems can make such transactions more practical, allowing digital services to charge per request rather than requiring customers to buy subscriptions or prepaid packages. This could support new commercial models in which AI systems purchase precisely the information or computing resources they need.

More than 87% of AI payments are worth less than ten cents

One of the most revealing findings concerns the value of individual transactions. Chainalysis examined x402 activity over the 16 months ending in September 2026 and found that more than 87% of payments fell between $0.0001 and $0.10. The most common transaction values were between one and ten cents. These figures indicate that much of the emerging agentic payment economy is based on micropayments rather than conventional retail transactions.

For developers, the ability to charge small amounts for individual services creates opportunities to commercialize digital resources that would otherwise be difficult to sell economically. For example, a financial information provider could charge an AI agent for each dataset requested. A software security company might charge for individual code inspections, while an AI infrastructure provider could charge per model query. This approach differs from the subscription-based pricing structures that dominate many software services.

Instead of committing to a monthly payment, autonomous systems could access resources on demand, with costs determined by actual usage. Such arrangements may become especially important as AI agents grow more sophisticated and coordinate multiple specialized services to complete complex tasks. For the broader digital economy, micropayment infrastructure could help create marketplaces where software applications automatically exchange services and information.

However, high transaction volumes should not be confused with high commercial revenue. The predominance of extremely small payments means that even millions of transactions may represent comparatively modest financial value.

AI agents are spending money faster after receiving funds

Beyond transaction volumes, Chainalysis identified changes in how quickly AI-related wallets begin spending after receiving funds. In late 2025, the median interval between a wallet's initial funding and its first x402 payment was approximately 73 days. By the third quarter of 2026, that interval had fallen to just 18 minutes.

The finding suggests developers increasingly create and fund wallets specifically to run automated tasks, rather than for general experimentation or holding digital assets. The proportion of newly funded wallets making their first x402 payment within one hour also increased substantially. In the third quarter of 2025, only 4% of wallets made their first payment within an hour of receiving funds. By the third quarter of 2026, the figure had reached 67%.

This acceleration suggests a closer connection between wallet funding and immediate operational requirements. An AI agent may receive a defined spending allocation shortly before beginning a task and then use those funds to purchase the services necessary to complete it. Such behavior aligns with the development of automated payment workflows in which spending decisions are part of software execution.

Nevertheless, the data does not establish that every transaction was initiated independently by an AI model. Some activity may involve automated applications or scripts operating within predefined instructions.

Repeat funding suggests more sustained adoption

Chainalysis also examined whether wallets continued receiving funds after their initial activity, providing another indicator of recurring usage. Among qualifying wallets first funded in the third quarter of 2025, 70.6% received additional funding within 30 days. For the corresponding group first funded in the second quarter of 2026, that proportion increased to 89.3%.

The analysis focused on wallets that had made payments on at least two separate days, excluding one-time participants from this particular comparison. This qualification is important because the figures measure repeat funding among an already active group rather than retention across all newly created wallets.

Even with that limitation, the increase suggests developers and organizations using x402 are becoming more willing to replenish wallets and keep automated payment systems running. Repeat funding can indicate that an agent is performing tasks valuable enough to justify ongoing expenditure.

For example, a business might allocate a recurring budget to an automated market intelligence assistant that purchases information from external data providers. Similarly, software development teams could fund agents that continuously access testing tools, security services or specialized computing resources. These use cases show how autonomous payments could become a routine part of business operations.

What are AI agents actually buying?

Chainalysis's findings show that the emerging market for autonomous payments is currently concentrated in digital services rather than physical consumer goods. One of the largest spending categories is AI model inference, where an agent pays to access another AI model.

This can occur when a relatively simple agent needs specialized capabilities to complete a task, such as analyzing complex information, generating code or interpreting technical documents. Other important categories include data and search APIs, financial intelligence, software code review, security analysis and tools used to develop or operate AI agents.

In effect, AI systems are increasingly purchasing services from other software systems. This development could create a digital economy in which agents act simultaneously as buyers, service providers and intermediaries.

A business-oriented AI assistant, for example, might buy market data from one provider, get analytical processing from another, and use a third service to generate a report. Each interaction could involve a separate automated payment, potentially completed within seconds.

The model gives providers of specialized digital services opportunities to monetize their capabilities through standardized payment infrastructure. At the same time, Chainalysis cautions that some early x402 transaction activity was driven by speculative cryptocurrency applications, including memecoin-related transactions. The emergence of more sustained information-service payments is an important development, but the overall ecosystem remains early-stage.

United States dominates AI-to-AI payments

The research also identifies substantial geographic differences in the development of autonomous payment activity. According to Chainalysis, wallets attributed to the United States accounted for approximately 30% of geographically identifiable transactions between AI agents and services using x402.

The American share was considerably higher in categories associated with AI infrastructure. US-linked wallets represented 88.1% of identifiable transactions involving AI model inference and 41.8% of payments to agent frameworks and tool catalogs. They also accounted for 23.2% of transactions involving data and search APIs.

These figures reflect the prominent position of American companies in artificial intelligence development, blockchain infrastructure and digital payment technologies. Coinbase, which developed x402, and Circle, the issuer of USDC, are among the companies supporting the infrastructure used for autonomous payments.

The United States is also home to major AI model developers and a substantial ecosystem of businesses building agent-based software. China presents a different pattern. Chainalysis identified particularly strong Chinese-linked activity in security and code analysis services, suggesting the emerging agentic economy may develop different regional specializations.

However, geographic attribution in blockchain analysis has limitations. Wallet activity cannot always be reliably assigned to a particular country, and the available percentages refer only to transactions for which geographic identification was possible.

What autonomous payments mean for e-commerce

Although the Chainalysis findings primarily concern digital services, they have broader implications for e-commerce development. Agentic commerce describes a commercial environment in which AI systems can participate in purchasing decisions, product discovery and transaction execution. For consumers, this could eventually involve shopping assistants that compare products, identify suitable retailers and facilitate purchases according to predefined preferences.

For businesses, autonomous agents may increasingly purchase software services, market intelligence, logistics information and other resources required to support commercial operations.

The x402 protocol demonstrates one possible payment infrastructure for this emerging environment, particularly where transactions are frequent and individually small. However, conventional retail requirements differ from those of machine-to-machine micropayments. Purchasing physical products involves inventory availability, delivery addresses, taxation, consumer protection, fraud prevention, returns, and dispute resolution.

These considerations make it unlikely that a single payment protocol will address every aspect of agentic commerce. Instead, different payment technologies may serve complementary purposes. Blockchain-based stablecoin payments could become increasingly relevant for automated purchases of digital services, while established payment providers continue supporting consumer transactions that require additional authorization and protection mechanisms.

The growth of x402 should therefore be seen as evidence of expanding autonomous payment capabilities, not proof that blockchain transactions are replacing conventional e-commerce checkout systems.

Implications for cross-border commerce and digital services

Machine-to-machine payments could be particularly relevant for cross-border digital commerce. Businesses operating internationally often encounter payment processing costs, currency conversion expenses and administrative requirements when purchasing services from providers in other countries. For small digital transactions, these costs can become disproportionately high.

Low-cost blockchain payments could reduce some of these barriers by letting software applications settle transactions using compatible digital currencies and payment protocols. This may create opportunities for international providers of data, computing services and AI infrastructure to sell access to customers without requiring conventional billing relationships for every transaction.

An AI agent operating in Europe, for example, could theoretically purchase access to a specialized information service located in another region through an automated stablecoin payment. Such transactions could support more flexible international markets for digital resources.

Nevertheless, cross-border adoption will depend on several factors, including regulatory compliance, sanctions screening, cybersecurity, stablecoin availability and the legal treatment of digital asset payments.

Businesses will also need mechanisms to manage automated spending limits, transaction records, and financial accountability. Consequently, autonomous payment infrastructure will need appropriate governance and risk-management systems.

Agentic commerce moves beyond experimentation

Chainalysis research shows that autonomous payment systems are developing more persistent usage patterns. The increase to more than 138 million cumulative x402 transactions, combined with faster initial spending and higher repeat funding among active wallets, suggests that developers are integrating automated payments into increasingly practical workflows.

However, the market remains relatively immature. Most transactions involve very small amounts, early adoption has been driven by speculative activity, and available research does not establish the total economic value generated by autonomous payments. Nevertheless, the findings indicate that a new form of digital commerce is beginning to take shape.

Rather than relying exclusively on human users to initiate purchases, software applications are becoming capable of acquiring resources and services as part of their normal operations. For e-commerce companies, payment providers, and technology developers, this creates opportunities to build infrastructure that supports transactions between people and autonomous systems.

The immediate commercial impact may be most visible in digital services, where AI agents can purchase information, computing resources and specialized capabilities without the logistical complexity of physical retail. Over time, however, the same underlying principle could influence broader commerce: software systems identifying commercial requirements, evaluating available suppliers and executing payments within defined limits. Chainalysis' findings suggest that this transition is already underway, even if the full economic potential of agentic commerce has yet to be demonstrated.

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Shopify has announced a major expansion of its agentic commerce infrastructure, allowing developers and consumers to connect compatible artificial intelligence shopping agents to its catalog of more than one billion products. The initiative, announced on October 13, 2026, removes the need for individual commercial partnerships to access Shopify's shopping infrastructure, opening the door for a wider range of AI assistants to discover products, build shopping carts and facilitate purchases.

The development represents another step toward a retail environment in which AI agents act as intermediaries between consumers and merchants. Rather than navigating multiple websites, shoppers can increasingly use conversational assistants to compare products, evaluate availability and complete transactions through integrated payment systems. Shopify's latest initiative extends these capabilities beyond established technology partners, potentially accelerating competition in the emerging agentic commerce market.

Shopify introduces Shop MCP for AI-powered shopping

At the center of the announcement is Shop MCP, a new connection based on the Model Context Protocol (MCP), which enables compatible AI agents to interact with Shopify's shopping infrastructure. Available through Shopify's Shop ecosystem, the service provides access to product discovery, customer authentication, cart management, checkout and order tracking.

Shop MCP offers 17 tools covering the principal stages of the purchasing journey. AI agents can search Shopify Catalog, retrieve product information, identify available merchandise and create shopping carts. Once a consumer has selected a product, the agent can initiate checkout and assist with completing the transaction.

Importantly, catalog searches do not require an API key, reducing the technical barriers for developers experimenting with AI shopping applications. Shopify also provides a command-line interface and documentation designed to simplify integration with compatible agents.

The launch changes the accessibility of Shopify's commerce infrastructure. Previously, more advanced agentic shopping experiences were largely associated with specific integrations and partnerships. Developers can now connect compatible assistants through a common interface without negotiating a separate commercial agreement with Shopify.

More than one billion products become accessible to AI agents

Shopify Catalog contains more than one billion product listings, providing a substantial inventory for AI-powered product discovery. The catalog includes merchandise from eligible Shopify merchants and participating retailers operating outside Shopify's traditional storefront ecosystem.

Its significance extends beyond the number of available products. Shopify structures product information so AI systems can interpret attributes such as pricing, availability, descriptions, specifications and product variations. This allows shopping assistants to evaluate merchandise against consumer preferences rather than relying exclusively on conventional keyword searches.

For example, a shopper could ask an AI assistant to identify a particular type of product within a defined budget, compare available alternatives and prioritize items offering faster delivery. The assistant could use structured catalog information to narrow the options before presenting a recommendation.

This approach could gradually change how consumers discover products online. Instead of beginning their purchasing journey on a search engine or marketplace homepage, shoppers may increasingly start with a conversational request describing what they need.

However, inclusion in Shopify Catalog does not guarantee that a product will be recommended. AI assistants may evaluate multiple factors, including relevance, availability, price, delivery conditions and the quality of product information.

Shop Pay brings checkout into AI conversations

One of the most important aspects of Shopify's announcement is the integration of purchasing capabilities through Shop Pay.

Consumers who connect their Shop accounts to compatible AI assistants can use saved payment and delivery information to streamline transactions. The agent can prepare a shopping cart and initiate checkout, while the consumer confirms the relevant payment details and purchase.

For Shopify-powered stores, orders are processed through the merchant's existing commerce infrastructure and appear in the Shopify administration system. This allows merchants to manage fulfillment and order processing through familiar operational workflows.

The system also supports purchases from participating non-Shopify stores. In these cases, the consumer authorizes the transaction through Shop, after which the agent can receive single-use payment credentials to complete the purchase through the retailer's checkout.

This distinction is particularly important because it demonstrates Shopify's ambition to support commerce beyond its own storefront technology. By connecting product discovery and payment infrastructure across different retail environments, the company is positioning Shop as a broader transaction platform for AI-assisted purchasing.

Consumer authorization remains central to the purchasing process. Shopify's documented checkout flow requires confirmation of the total and payment method before an agent completes a transaction, rather than allowing unrestricted purchases without user involvement.

Shopify moves beyond exclusive AI partnerships

The announcement follows several developments in Shopify's agentic commerce strategy, including integrations with major AI platforms and the expansion of checkout capabilities for browser-based agents.

In September, Shopify announced support for AI shopping experiences involving Meta's Muse, while a subsequent update extended checkout functionality to compatible agents operating directly within web browsers. The October launch broadens this approach by making a standardized shopping connection available to developers building their own assistants.

The change could accelerate the development of specialized AI shopping services. Instead of competing exclusively through general-purpose assistants, developers could create agents focused on particular industries, consumer needs or purchasing preferences.

Examples could include assistants specializing in fashion recommendations, consumer electronics comparisons, home improvement products or recurring household purchases. Such applications could combine personalized recommendations with access to a substantial product catalog and integrated checkout capabilities.

The broader implications are significant. As AI agents become more capable of conducting commercial transactions, retailers may need to consider how their products are represented and recommended within automated shopping environments.

What agentic commerce means for online retailers

For merchants, the expansion of AI shopping introduces both opportunities and challenges.

The principal opportunity is access to additional product discovery channels. Smaller retailers could potentially reach consumers through AI assistants without depending entirely on traditional search engine rankings, paid advertising or marketplace visibility.

However, this does not eliminate competition for consumer attention. Instead, it may change the factors determining which products receive exposure.

Structured product information could become increasingly important as AI assistants compare merchandise according to specific customer requirements. Accurate descriptions, detailed specifications, product variations, availability and delivery information may influence whether a product is considered relevant to a particular purchasing request.

Shopify already provides tools for merchants to manage product information distributed through its catalog. Eligible products can be made available to supported AI channels, while merchants retain certain controls over their participation.

Nevertheless, merchants cannot directly determine how independent AI assistants rank or recommend products. The algorithms and decision-making processes used by individual agents may therefore become an important consideration for digital commerce strategies.

This development could also affect customer acquisition. If consumers increasingly purchase products through AI assistants, retailers may have fewer opportunities to influence the shopping experience through their own website design, promotional messaging and merchandising.

Maintaining brand visibility and customer relationships within AI-mediated transactions could become an important strategic challenge.

Implications for cross-border e-commerce and fulfillment

The expansion of AI-powered shopping could also influence international e-commerce, particularly as consumers become more comfortable purchasing from retailers outside their domestic markets.

AI assistants capable of comparing products across multiple merchants could make international offers easier to discover. However, product visibility alone does not eliminate the operational complexity associated with cross-border transactions.

International shipping costs, customs requirements, import duties, delivery times and return policies remain important considerations. An AI assistant recommending products from overseas merchants must account for these factors if it is to provide consumers with accurate purchasing information.

For fulfillment providers and logistics companies, agentic commerce may increase the importance of reliable inventory data, transparent delivery estimates and standardized shipping information.

A consumer requesting the cheapest available product may receive a different recommendation from someone prioritizing next-day delivery or straightforward returns. Consequently, fulfillment capabilities could increasingly influence product selection before the customer reaches checkout.

Retailers offering dependable delivery services, accurate stock information and clear international shipping conditions may be better positioned to compete in this environment.

Nevertheless, the extent to which agentic commerce will increase cross-border transaction volumes remains uncertain. Shopify has not disclosed sufficient adoption or sales data to establish the commercial impact of its latest expansion.

AI agents could reshape the future of online shopping

Shopify's decision to open its billion-product catalog and purchasing infrastructure to compatible AI agents reflects a broader transformation in digital commerce.

Technology companies are increasingly developing systems that allow AI assistants to move beyond answering product-related questions and participate directly in transactions. The objective is to reduce friction between product discovery, comparison and purchase, potentially creating a more conversational shopping experience.

For Shopify, the strategy also creates an opportunity to expand the relevance of its commerce infrastructure beyond conventional online storefronts. By providing the technical connections through which AI assistants discover products and facilitate payments, the company could strengthen its position within an increasingly fragmented digital retail ecosystem.

However, several questions remain unresolved. Consumer adoption, transaction volumes, merchant economics and the influence of AI recommendations on purchasing decisions will determine whether these capabilities become a mainstream shopping channel.

What is clear is that Shopify's October 13 announcement lowers an important technical barrier to agentic commerce. With access to more than one billion product listings and integrated purchasing capabilities, a broader range of AI developers can now build shopping experiences connected to existing retail infrastructure.

For online merchants, marketplaces and fulfillment providers, the development reinforces a growing strategic consideration: future e-commerce competition may depend not only on attracting human visitors to digital storefronts, but also on ensuring that products, payment systems and logistics information are accessible to the AI agents increasingly participating in purchasing decisions.

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India's e-commerce market generated an estimated $2.5 billion in gross merchandise value (GMV) during the opening two days of its 2026 festive shopping season, as major marketplaces including Amazon, Flipkart and Meesho reported exceptional consumer activity. According to Redseer Strategy Consultants, between 60 million and 65 million consumers placed about 80 million to 90 million orders on October 8 and 9, underscoring the growing scale of one of the world's most dynamic digital retail markets.

Total sales reached about ₹24,000 crore, roughly six times the normal daily GMV. However, the most significant development concerns the changing geographical distribution of online shoppers. About two-thirds of participating consumers came from smaller cities and rural markets, while first-time online shoppers doubled compared with the previous year. The figures suggest that India's e-commerce expansion is increasingly extending beyond its largest metropolitan areas, supported by affordable products, flexible payment options and improving fulfillment infrastructure.

Amazon, Flipkart and Meesho report record festive shopping activity

Amazon's Great Indian Festival 2026 recorded more than 440 million visits during its opening phase, with over 72% originating outside India's nine largest metropolitan areas. The company also reported that the number of products ordered more than doubled year over year during the first 12 hours. Smartphones, electronics, fashion, beauty products and household essentials were among the most popular categories, reflecting the growing diversification of online purchasing.

Payment flexibility played an important role in Amazon's performance. About half of participating customers used equated monthly installment (EMI) plans, while one-third of purchased units benefited from cashback incentives. The company also highlighted the growing importance of Amazon Now, its rapid-delivery service, as consumers increasingly expect shorter fulfillment times alongside competitive prices.

Flipkart reported approximately 6.3 million concurrent users during the opening hour of its Big Billion Days event, with around 60% of demand coming from non-metropolitan markets. Its quick-commerce service, Flipkart Minutes, also saw a significant rise in orders, showing that rapid delivery is becoming an increasingly important competitive factor in Indian retail.

Meanwhile, Meesho reported a 75% year-over-year increase in orders on the first day of its Mega Blockbuster Sale, along with about 60% growth in transacting customers. Its performance reflects the continued expansion of value-oriented e-commerce, particularly among consumers in smaller towns and cities seeking affordable merchandise.

These figures are company-reported results covering different measurement periods and should not be interpreted as directly comparable market shares.

Smaller cities and first-time shoppers drive e-commerce growth

One of Redseer's most important findings is that about two-thirds of festive shoppers came from outside India's largest metropolitan areas. Expanding smartphone access, digital payments, and logistics networks are making online shopping increasingly accessible to consumers in Tier 2 and Tier 3 cities, smaller towns, and rural communities.

The number of first-time online shoppers doubled compared with the previous year's festive season, suggesting that promotional events are attracting new consumers rather than merely increasing purchases among existing customers. Younger shoppers are also becoming increasingly influential, with Generation Z representing about one-third of participants on opening day.

For international brands and marketplaces, these developments reinforce the importance of localized strategies that consider regional purchasing power, product preferences, payment methods and delivery infrastructure. Reaching India's next generation of online consumers will increasingly depend on serving markets beyond traditional metropolitan retail centers.

Smartphones and electronics dominate transaction value

Smartphones accounted for approximately 38% to 40% of total GMV during the opening two days, representing an estimated ₹9,100 crore to ₹9,600 crore in sales. Consumer electronics and large appliances contributed another 25% to 27%, while fashion accounted for about 15% to 18% of transaction value.

Demand for televisions, refrigerators, air conditioners, and laptops was particularly strong, supported by promotional discounts, installment payments, and seasonal purchasing patterns. The popularity of larger televisions and other bulky products also highlights the importance of specialized fulfillment capabilities, particularly as online retail expands into smaller markets.

Fashion GMV rose 22% to 25% year over year, with affordable festive clothing driving strong demand. Products priced below ₹500 performed particularly well, underscoring the importance of accessible pricing for consumers new to online retail.

Quick commerce emerges as a major competitive factor

Rapid-delivery platforms generated approximately four to five times their normal daily GMV during the opening two days, according to Redseer. An estimated 14 million to 15 million consumers participated in quick commerce, illustrating the growing importance of convenience and delivery speed in India's digital retail ecosystem.

Originally focused on groceries and everyday essentials, quick commerce is increasingly expanding into electronics accessories, personal care, household products, and other categories suitable for rapid fulfillment. Amazon Now and Flipkart Minutes reflect established marketplaces' growing interest in this model.

However, quick commerce requires a different logistics structure from conventional e-commerce. Maintaining inventory close to consumers depends on dense networks of local fulfillment facilities, accurate demand forecasting, and sufficient order volumes to support short delivery routes. Expanding these capabilities beyond densely populated urban markets will remain a significant operational challenge.

India's e-commerce expansion creates new logistics opportunities

India's online retail market is diversifying geographically, driving growing demand for regional warehousing, transportation networks, and last-mile delivery services. Serving consumers across smaller cities and rural communities requires more extensive distribution infrastructure than traditional metropolitan-focused fulfillment models.

For marketplaces and third-party logistics providers, the challenge is to balance delivery speed, inventory availability, and operating costs. High-volume promotional events intensify these pressures by concentrating millions of orders into a relatively short period, increasing demand for warehouse processing capacity, transportation, and customer support.

International brands entering India must also consider domestic distribution, customs requirements, local consumer preferences, and the economics of reaching customers across different regions. Competitive pricing remains essential, but reliable fulfillment and flexible payment options are becoming equally important components of the purchasing experience.

A new phase for India's digital retail market

India's estimated $2.5 billion in festive e-commerce sales during just two days demonstrates the scale and growing maturity of its online retail sector. Up to 65 million shoppers, combined with strong demand for smartphones, electronics, fashion, and quick commerce, highlights the market's growing diversity.

More importantly, the expansion beyond major metropolitan areas suggests that India's next phase of e-commerce growth will depend heavily on smaller cities, new digital consumers and the infrastructure required to serve them. Amazon, Flipkart and Meesho are competing through different combinations of pricing, product selection, financing and fulfillment capabilities, while Redseer forecasts that approximately 100 million consumers could participate during the first 11-day phase of the festive shopping season.

For the global e-commerce industry, India's performance offers a clear example of how digital retail growth is increasingly driven by broader consumer participation, localized commerce strategies and the continued development of efficient fulfillment networks.

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Global container shipping volumes hit a record 17.46 million twenty-foot equivalent units (TEUs) in August 2026, underscoring the resilience of international trade despite geopolitical instability, rising fuel costs, and mounting pressure on global supply chains. However, the latest figures from Container Trades Statistics (CTS) reveal a more challenging development for international retailers and cross-border businesses: global freight prices rose 44% from August 2025, reaching their highest level in more than two years.

According to the CTS report published on October 8, container volumes increased 3.7% year over year in August, surpassing the previous monthly record established in July. Cumulative global volumes for the first eight months of 2026 were 4.7% higher than during the corresponding period in 2025, confirming that international merchandise flows remain remarkably strong despite widespread uncertainty surrounding trade policies and maritime transportation.

Record container traffic and sharply higher shipping prices are creating a growing challenge for global e-commerce. While demand for international transportation remains resilient, businesses importing products from overseas manufacturing centers face increasing pressure on logistics budgets, inventory management and profitability. For retailers, marketplaces, and fulfillment providers, the latest data suggests the final quarter of 2026 could see sustained trade activity alongside elevated transportation costs.

Global container shipping reaches another historic milestone

The latest CTS figures establish August 2026 as the busiest month for containerized trade in the organization's database, with global liftings reaching 17.46 million TEUs. The result exceeds the previous record of approximately 17.3 million TEUs registered in July, continuing a period of exceptionally strong activity across international shipping networks.

The longer-term comparison illustrates the scale of the expansion. August volumes were 3.7% higher than August 2025, 7.2% higher than August 2024, and 12.9% higher than the corresponding month in 2023. These figures show that global container trade has continued to grow despite repeated disruptions to maritime routes, changes in international trade policy, and higher operating costs.

This performance is particularly notable given the difficult conditions that affected the shipping industry throughout 2026. Elevated fuel prices, security concerns in the Arabian Gulf, constraints affecting the Panama Canal and evolving tariff arrangements have complicated transportation planning for carriers and cargo owners. Nevertheless, global shipping volumes have continued to reach new highs, suggesting international supply chains are adapting to these challenges rather than broadly contracting.

However, record volumes do not necessarily indicate that the industry is entering a period of accelerating growth. CTS has warned that the pace of month-to-month expansion is beginning to moderate, raising questions about whether the current momentum can continue through the final months of the year.

Freight prices climb 44% as shipping disruptions intensify

While container volumes are setting records, freight pricing is also rising sharply. The CTS Global Price Index reached 117 points in August, up from 115 in July, its highest level since July 2024, when Red Sea disruptions exerted substantial pressure on maritime transportation.

The index has risen approximately 50% since January 2026 and stands 44% above its August 2025 level. The increase reflects a substantial deterioration in the cost environment for businesses relying on international container shipping, although actual freight rates vary considerably depending on the route, contract structure, shipping service and cargo characteristics.

Shipping prices have risen alongside disruptions affecting major international maritime corridors. Security concerns and operational difficulties can force shipping companies to adjust routes, extend transit times or allocate additional capacity to maintain service schedules. These adjustments reduce the effective availability of shipping capacity and increase operating expenses, even when the global fleet size remains unchanged.

Higher fuel costs create another layer of pressure. As energy prices rise, carriers face higher operating costs and may introduce or adjust fuel-related surcharges. These transportation costs can affect businesses across the supply chain, from manufacturers and wholesalers to retailers and direct-to-consumer brands.

For cross-border e-commerce companies, the problem extends beyond the headline freight rate. Higher maritime transportation costs contribute to the total landed cost of imported goods, potentially affecting retail pricing, promotional margins and decisions about where inventory should be stored.

Asian exports drive global container trade growth

The Far East remains the principal engine of expansion in global container shipping. According to CTS, exports originating in the region rose 8% in the first eight months of 2026 versus the same period in 2025, adding about 6.3 million TEUs.

Every major destination region recorded growth in containerized cargo originating from the Far East, with Sub-Saharan Africa and South and Central America leading in percentage terms. The figures reinforce Asia's central position within international manufacturing and distribution networks, even as businesses increasingly discuss diversifying their sourcing strategies.

For global e-commerce, the continued strength of Asian exports matters most. China and other Asian manufacturing economies remain important suppliers of consumer electronics, fashion, household products, accessories, and numerous other categories sold through international marketplaces and online retail channels.

The growth in containerized exports also highlights an important distinction between different forms of cross-border commerce. While changes to customs regulations and import duties can alter the economics of individual low-value parcels shipped directly to consumers, larger consolidated shipments continue playing a central role in international retail supply chains.

Many merchants import goods in bulk before distributing them through domestic warehouses, third-party logistics providers or marketplace fulfillment networks. Strong Asian export volumes reflect the continued importance of these inventory-based distribution models, although CTS does not separately identify the proportion of shipments attributable to e-commerce.

North American imports recover despite tariff uncertainty

North American container imports have also shown signs of recovery following a difficult start to 2026. CTS reports that imports into the region rose 2% in the first eight months of the year versus the same period in 2025, reversing the negative year-to-date growth recorded earlier.

Stronger cargo flows from the Far East have supported the recovery. Trans-Pacific trade volumes increased 5% year-to-date, reflecting renewed activity along one of the world's most important shipping corridors.

The improvement is particularly notable given the uncertainty surrounding international tariffs and trade relations. Changes in import duties, customs procedures, and commercial restrictions can affect when businesses place orders, how much inventory they buy, and which countries they choose for manufacturing or distribution.

For retailers importing merchandise into the United States, shipping decisions are closely connected to inventory planning and consumer demand. Companies must balance the cost of maintaining stock against the risk of shortages, delayed deliveries or unexpected changes in import expenses.

However, the recovery should not be interpreted as evidence that every North American port or trade route is experiencing equivalent growth. Separate figures released by the National Retail Federation on October 8 showed that the major US container ports included in its Global Port Tracker handled approximately 2.3 million TEUs in August, down 0.7% year over year. The difference reflects the distinct geographical coverage and methodologies of the two datasets.

The broader picture is therefore one of recovering regional container trade, rather than uniformly accelerating imports across every port and shipping service.

Sub-Saharan Africa emerges as a major growth market

One of the CTS report's most significant regional developments is Sub-Saharan Africa, where container imports rose 13% in the first eight months of 2026. This is the strongest percentage growth among the regions analyzed and highlights the growing importance of African markets in international merchandise flows.

Trade with multiple origin regions, particularly the Far East, supports the expansion. Growing container volumes suggest increasing commercial activity and stronger connections between African import markets and international manufacturing centers.

For cross-border retailers and logistics providers, the trend could have important long-term implications. As international trade volumes expand, demand may rise for freight forwarding, customs brokerage, warehousing, inland transportation, and distribution services that connect imported merchandise with domestic consumers and businesses.

However, rising container imports should not automatically be interpreted as equivalent growth in online retail sales. Container traffic includes industrial materials, machinery, intermediate goods, and other products that extend far beyond consumer e-commerce.

Nevertheless, the expansion demonstrates how international supply chains are evolving beyond their traditional concentration on North American and European destination markets. Businesses developing international distribution strategies may increasingly need to consider emerging trade corridors and the infrastructure required to support them.

Middle East disruptions create a sharp regional contraction

Not every region is benefiting from the expansion in global container trade. The combined Indian Sub-Continent and Middle East region was the only major region in the CTS report to register declines in both imports and exports during the first eight months of 2026.

Imports fell 5% from the corresponding period in 2025, while exports fell 10%. The reduction in outbound volumes was just under one million TEUs, underscoring the scale of the disruption affecting regional trade.

The decline is particularly significant because the region occupies a strategically important position within international maritime transportation. Shipping routes connecting Asia, Europe and the Middle East are closely linked to major energy markets, manufacturing centers and international distribution networks.

Disruptions affecting these corridors can have consequences far beyond the countries directly involved. Changes in vessel routing, port accessibility and transportation schedules can influence capacity availability across other shipping lanes, contributing to congestion and higher operating costs.

This helps explain why global freight prices can rise even while overall shipping volumes remain strong. Maritime transportation operates as an interconnected network, so capacity restrictions in one region can affect commercial conditions elsewhere.

For international merchants, the consequences may include longer transit times, less predictable delivery schedules and additional costs associated with rerouting or alternative transportation arrangements.

European exports stabilize as international trade patterns shift

Europe's export performance has also improved, although growth remains considerably weaker than in the Far East. According to CTS, European container exports returned to approximately flat year-to-date growth in August after declining in earlier months of 2026.

The stabilization reflects steady or improving cargo flows across most destination regions. Although zero growth may seem modest compared with expansion elsewhere, it still represents an improvement for European exporters operating in a challenging international trade environment.

Earlier CTS figures also indicated strong demand for imports from Europe. In its July report, the organization recorded 6.1% year-to-date growth in European imports, supported in part by about 1.5 million additional TEUs originating in the Far East.

The contrast between stronger imports and relatively subdued exports highlights the continuing importance of Asian manufacturing within European supply chains. It also illustrates the challenges European exporters face as they try to expand international sales amid rising transportation costs and changing trade conditions.

For European e-commerce businesses, these developments reinforce the importance of logistics planning. Companies importing products from Asia must account for higher freight costs, while those exporting to international customers must maintain competitive delivered prices.

This is especially relevant for businesses operating across multiple European marketplaces, where they can distribute inventory through regional fulfillment centers to reduce delivery times and improve service reliability.

What record shipping volumes mean for cross-border e-commerce

The latest container shipping data has important implications for online retailers, particularly those relying on imported inventory. Although global container traffic doesn't directly measure e-commerce activity, maritime transportation remains a critical part of the supply chains supporting international online sales.

A large proportion of merchandise sold through marketplaces such as Amazon, Walmart, AliExpress and other retail platforms reaches its destination market through conventional freight networks before entering domestic fulfillment and parcel delivery systems. Rising ocean freight costs can therefore affect the economics of online retail long before someone places an order.

For businesses importing consumer goods, higher transportation expenses increase inventory acquisition costs. Depending on product margins and competitive conditions, merchants may absorb part of the increase, negotiate with suppliers, adjust selling prices or reduce promotional discounts.

The effect can be particularly significant for low-margin products, bulky merchandise and categories where transportation represents a substantial share of the final landed cost. Businesses selling high-value, lightweight products may experience a different cost impact, depending on their shipping arrangements and sourcing locations.

Freight volatility also complicates inventory planning. Retailers must determine how much stock to order, when shipments should depart and whether additional inventory should be held closer to customers to reduce exposure to unexpected transportation delays.

These decisions become especially important ahead of major shopping periods, when product availability and delivery reliability can directly influence conversion rates and customer satisfaction.

Rising logistics costs strengthen the case for regional fulfillment

One potential consequence of sustained freight volatility is a greater emphasis on regional inventory management and fulfillment. Rather than relying on frequent international replenishment, retailers may consolidate larger shipments and distribute inventory through warehouses closer to their main consumer markets.

This approach can provide several advantages. Regional fulfillment facilities let merchants serve domestic and neighboring markets with shorter delivery times, reduce reliance on individual international shipments, and manage returns through local logistics networks.

However, regional warehousing introduces additional costs, including storage, inventory financing, labor, customs administration and operational management. The optimal model depends on sales volumes, product characteristics, demand predictability, and customers' geographic distribution.

Higher ocean freight prices do not automatically make local fulfillment cheaper for every merchant. Instead, it strengthens the need for detailed landed-cost calculations that consider transportation, inventory holding costs, customs requirements, and last-mile delivery expenses together.

For third-party logistics providers, this environment may create opportunities to offer more integrated services that combine international freight forwarding, customs clearance, inventory management, and domestic order fulfillment. As cross-border commerce becomes increasingly complex, merchants may place greater value on logistics partners that can manage the full movement of goods from manufacturing locations to final consumers.

Shipping companies and logistics providers face different economic pressures

The increase in freight prices also have different implications for businesses in the transportation industry. Ocean carriers can benefit directly from higher shipping rates, particularly when demand remains strong and capacity is constrained. Freight forwarders, however, operate under a different commercial model. These companies coordinate transportation and logistics services for customers, meaning that rising carrier rates do not necessarily translate into equivalent increases in profitability.

According to Reuters reporting published on October 6, European shipping and logistics companies are expected to benefit from resilient international trade and elevated freight prices, although the effects vary across different segments of the industry.

Carriers such as Hapag-Lloyd and Maersk are more directly exposed to ocean freight pricing, while logistics providers including DSV, DHL and Kuehne+Nagel may benefit from demand for additional services such as customs clearance, warehousing and complex supply-chain management. For e-commerce merchants, the distinction matters because ocean transportation is only one component of the overall logistics bill. Customs brokerage, port handling, inland transportation, storage and final-mile distribution can all contribute to the total cost of bringing products to market.

Businesses seeking to control logistics expenses therefore need to evaluate the complete supply chain rather than focusing exclusively on container freight rates.

Peak-season inventory planning becomes more complicated

The latest CTS figures arrive as retailers prepare for the final quarter of 2026, traditionally one of the most important periods for consumer spending and e-commerce activity. Black Friday, Cyber Monday, and the Christmas shopping season create significant demand for inventory, fulfillment capacity, and reliable transportation.

However, recent US port data suggests that the peak import season may already be moving past its busiest period. The National Retail Federation reported on October 8 that the extended US retail shipping peak appears to be winding down following sustained activity throughout the summer and early autumn.

According to the NRF, most holiday merchandise has already arrived, with remaining shipments increasingly focused on replenishment and preparation for early 2027. Its Global Port Tracker projects that US import volumes at the ports it covers will reach about 25.8 million TEUs for the full year, up 1.4% from 2025. These figures provide an important qualification to the global CTS data. Record worldwide shipping volumes do not necessarily mean retail imports will keep accelerating through the final quarter, particularly in markets where businesses have already brought forward seasonal inventory.

For merchants, the challenge is to manage existing stock efficiently while retaining sufficient flexibility to respond to unexpected changes in consumer demand. Higher freight prices make last-minute replenishment more expensive, while uncertain transit times can reduce the reliability of international restocking.

Retailers with accurate demand forecasts, diversified logistics arrangements and strategically positioned inventory may therefore be better equipped to navigate the current environment.

Could global freight prices remain elevated through 2027?

The central question facing the container shipping industry is whether strong volumes and high freight prices will persist. The CTS Global Price Index has risen sharply since the beginning of 2026, but future movements will depend on several interacting factors, including geopolitical developments, fuel prices, shipping capacity and global merchandise demand.

Fewer maritime disruptions could eventually return effective capacity to the market, potentially easing freight rates. Conversely, continued route restrictions, higher fuel costs, or renewed congestion could sustain pricing pressure even if container volume growth begins to moderate.

The pace of demand growth will also be important. CTS has already identified signs of slowing month-to-month momentum, suggesting that the market may be approaching a period of more moderate expansion after consecutive record months.

For retailers and importers, the prudent approach is not to assume freight prices will keep rising indefinitely or quickly return to earlier levels. Instead, businesses need to prepare for continued uncertainty and assess how different shipping-cost scenarios could affect their margins, inventory decisions and international expansion plans.

Recent years have shown that global supply chains can remain operational during major disruption, but resilience often comes at a considerable financial cost.

Global trade remains resilient, but the cost of resilience is rising

The latest Container Trades Statistics report presents a striking picture of the international shipping industry. Global container volumes reached a record 17.46 million TEUs in August 2026, while the Global Price Index climbed to 117 points, approximately 50% above its January level and 44% higher than a year earlier.

The figures show that international merchandise trade continues to expand despite geopolitical tensions, shifting tariff policies, and operational constraints affecting major shipping routes. Strong exports from the Far East, recovering North American imports and rapid growth in Sub-Saharan Africa are helping sustain global container traffic, even as disruptions in the Indian Subcontinent and Middle East weigh on regional performance.

For cross-border e-commerce, the implications extend beyond the shipping industry. Higher freight prices affect inventory acquisition costs, product pricing, warehouse strategies, and international merchants' competitiveness. They also reinforce the importance of efficient fulfillment networks and the ability to adapt quickly to changing transportation conditions.

The broader message is that global trade is not retreating amid disruption. Instead, businesses and logistics providers are finding ways to keep goods moving through an increasingly complicated international environment. The challenge for the remainder of 2026 and beyond will be determining how much that resilience costs, and which companies are best positioned to absorb or manage the resulting pressures.

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Ant International's Antom has partnered with Google Gemini to expand access to Google's AI services across Asia, combining localized payments, subscription management, and digital distribution infrastructure in a collaboration that has already reached approximately 10 million users in Indonesia.

The partnership connects Google AI Plus with Antom's extensive network of digital wallets, e-commerce platforms and other digital services across the region. Beyond processing payments, Antom is providing infrastructure covering billing, tax management, risk management, marketing and account services throughout the subscription lifecycle.

The initiative initially launched in Indonesia in July 2026 and is now expected to expand into additional Asian markets. It provides another example of how global technology companies are increasingly relying on local payment ecosystems to scale digital products across highly fragmented markets.

For the payments industry, the partnership also demonstrates how payment orchestration is evolving beyond transaction processing. Providers such as Antom are increasingly combining payments with customer acquisition, localization, risk management and digital commerce services — capabilities that could become even more important as AI platforms move toward agentic commerce.

Antom and Google Gemini target Asia's fragmented payment landscape

Asia represents an enormous opportunity for global digital services, but it is also one of the world's most complex payment environments. Consumers across the region rely on a wide variety of digital wallets, bank transfers, QR-based payment systems, and local payment methods rather than a single dominant payment infrastructure.

For international companies, supporting those methods individually can require multiple technical integrations, commercial relationships and compliance processes. Antom's role is to simplify that complexity.

The Ant International subsidiary allows merchants to access more than 300 payment methods through a single integration, reaching consumers in more than 200 markets and supporting payments in more than 140 currencies. In Indonesia alone, the payment landscape includes digital wallets such as DANA, GoPay, OVO, and ShopeePay alongside QRIS, bank transfers, and numerous online banking options.

For a global service such as Google Gemini, connecting to this fragmented ecosystem through a payment orchestration provider can reduce the technical and operational complexity of entering individual markets. The partnership therefore extends beyond simply adding another payment method to Google AI Plus. Antom is effectively providing part of the commercial infrastructure required to distribute and monetize Google's AI services locally.

Indonesia becomes the first market

The collaboration began in Indonesia in July 2026 with a campaign offering a 12-month free trial of Google AI Plus to eligible students aged 18 to 25. Consumers can access the offer through several widely used digital channels, including DANA and GoPay, as well as Indonesian e-commerce platform Tokopedia. The campaign also extends to physical retail through participating MomoYo locations, a dessert and beverage chain operating in the country.

According to Ant International, the initiative has already reached approximately 10 million users in Indonesia. The scale of the initial rollout demonstrates the potential of combining payment infrastructure with distribution. Instead of relying exclusively on Google's own channels to acquire subscribers, Gemini can appear within digital wallets, e-commerce platforms and other services consumers already use.

For Antom, the model creates what the company describes as a "two-way growth engine": global digital businesses gain access to local users, while payment platforms and merchants can add new services and promotions designed to increase engagement.

A+Rewards connects Gemini with local digital ecosystems

A central component of the partnership is A+Rewards, Antom's digital marketing platform. A+Rewards is integrated into more than 30 major digital platforms and provides in-app entry points through which consumers can discover offers from participating brands and digital services.

According to Ant International, the wider network connects approximately 2.85 billion active digital payment users. For Google Gemini, this creates a distribution channel that extends far beyond conventional advertising or app-store discovery. Users can encounter Google AI Plus offers while interacting with services they already use for payments, shopping, and everyday digital activities.

The infrastructure uses AI technologies and privacy-preserving computing to support customer acquisition and promotional campaigns. In Indonesia, for example, Google AI Plus trials can be discovered through DANA, GoPay and Tokopedia.

This integration of payments and marketing is increasingly important in digital commerce. Payment providers historically entered the customer journey primarily at checkout. Platforms such as Antom are attempting to participate much earlier, helping merchants acquire customers before subsequently processing and managing their transactions.

Antom manages more than payments

One of the most important aspects of the Google partnership is the breadth of services Antom is providing. The company is consolidating billing, tax management, risk management, marketing and account services alongside payment processing.

This lets Antom support much of the subscription lifecycle for AI companies entering new markets. For global digital businesses, these operational requirements can become significant barriers to international expansion.

Local taxation rules vary. Payment preferences differ between countries. Fraud patterns change between markets. Subscription billing requires recurring payment capabilities, while customer acquisition may depend on partnerships with local digital ecosystems.

A payment provider that can combine these functions can reduce the number of separate systems and partners a global company needs to manage. The model is particularly relevant for subscription-based AI services, which increasingly compete for paying consumers worldwide.

As AI platforms expand internationally, the ability to accept local payment methods and manage recurring billing could become almost as important as the underlying technology itself.

Southeast Asia emerges as a major AI market

Google's decision to expand Gemini through local Asian payment ecosystems also reflects the rapid adoption of artificial intelligence across Southeast Asia. Google says interest in AI in the region is approximately three times the global average, while the number of active Gemini users in Southeast Asia has more than doubled over the past year.

The region is also overwhelmingly mobile-first. About three-quarters of Gemini requests in Southeast Asia come from mobile devices, and younger consumers in particular often use apps rather than traditional desktop browsers.

Indonesia illustrates that behavior particularly clearly. According to Google, around 82% of Gemini prompts in the country originate from mobile devices. Language localization is equally important. Approximately 84% of Gemini prompts in Indonesia are made using local languages.

These characteristics create a natural connection between AI services and mobile payment ecosystems. Digital wallets in Southeast Asia are often much more than payment applications. They can function as broader digital platforms combining payments, promotions, financial services, shopping, and other consumer activities. Integrating AI subscriptions into those environments gives companies such as Google another route to reach highly engaged mobile users.

Payments become a distribution channel

The Antom-Gemini partnership illustrates a broader transformation occurring within the payments industry. Payment providers are increasingly attempting to move beyond the final transaction. Traditionally, a payment service provider became visible when the customer reached checkout. Its primary responsibilities were authorizing the transaction, moving funds and managing associated financial risks.

That model is expanding. Modern payment platforms increasingly provide fraud prevention, currency conversion, subscription billing, tax services, customer analytics and marketing tools. Antom's A+Rewards network takes this development further by turning payment ecosystems themselves into customer acquisition channels.

Digital wallets can expose users to subscription offers. E-commerce platforms can distribute digital services. Merchants can become physical acquisition points for online products. Payments therefore become part of a broader commercial infrastructure connecting global brands with local consumers. This can be particularly valuable for cross-border commerce.

A company entering Indonesia, Thailand, Malaysia or another Asian market does not necessarily need to reproduce its existing Western payments strategy. Instead, it can connect with the local digital ecosystems consumers already trust and use.

Antom builds an infrastructure layer for global digital commerce

The Google collaboration also demonstrates Ant International's ambitions beyond its traditional association with Alipay. Antom is positioned as Ant International's merchant payment and digitization services business, providing payment infrastructure to companies operating internationally.

Its platform supports more than 300 payment methods through a single integration and allows merchants to accept payments across more than 200 markets and over 140 currencies. The company describes its payment architecture as AI-native and combines payment processing with risk management, digital marketing and other merchant services. This infrastructure is particularly relevant in Asia, where payment fragmentation remains a significant challenge for international merchants.

Instead of integrating independently with dozens of wallets, banks, and alternative payment systems, businesses can use an orchestration layer that connects them to multiple local options. The approach resembles developments elsewhere in global e-commerce, where infrastructure providers increasingly compete to become the layer connecting merchants with multiple marketplaces, payment systems or logistics networks. Complexity itself is becoming a business opportunity.

The connection with agentic commerce

Although the Google Gemini partnership is focused primarily on distributing and monetizing Google AI Plus subscriptions, it arrives as the payments industry prepares for a much larger transformation: AI agents capable of initiating and completing purchases.

This distinction is important. The current collaboration does not mean Gemini is autonomously purchasing products through Antom. Instead, Antom is providing payment and commercial infrastructure around Google's AI service. However, the same capabilities required to sell AI subscriptions internationally — payment orchestration, local payment methods, identity, risk management, recurring billing and cross-border settlement — are also likely to become important components of agentic commerce.

Antom is already developing agentic payment and agentic commerce capabilities. The broader industry is moving rapidly in the same direction. Visa, Mastercard, PayPal, Stripe, and other payment companies are developing infrastructure designed to identify AI agents, authenticate consumers, and allow authorized software agents to execute transactions.

Commerce platforms are simultaneously adapting their systems so AI agents can discover products and interact with checkout environments. The challenge becomes particularly complicated when those agents operate internationally.

An AI assistant purchasing something for a consumer in Indonesia may need access to completely different payment methods from an agent operating in Germany, the United States, or Japan. Payment orchestration platforms that can translate between global AI services and local payment ecosystems could therefore become an important layer in agentic commerce.

Localization could become critical for AI commerce

Much of the current discussion around agentic commerce focuses on whether AI agents can discover products, compare prices and complete checkout. But international commerce introduces another problem: localization.

An AI agent may understand what a consumer wants to buy, but completing the transaction requires access to payment methods that the merchant accepts and that the consumer actually uses. That problem becomes significantly more complicated across borders.

Asia provides perhaps the clearest example. Payment behavior varies substantially between countries, with digital wallets, QR systems, bank transfers, cards, and other alternative payment methods competing for consumer adoption.

A global AI platform attempting to interact directly with every local payment system would face considerable technical complexity. Payment orchestration can provide an abstraction layer between the AI service and those local networks.

Instead of building hundreds of individual integrations, AI platforms could connect to infrastructure that routes transactions through the appropriate payment method for each consumer and market. Antom's existing reach across hundreds of payment methods puts it in a strong position as that ecosystem develops.

AI, payments and commerce continue to converge

The Antom-Google partnership is another indication that the boundaries between artificial intelligence, payments and digital commerce are becoming increasingly blurred. Google wants to expand access to Gemini across Asia.

Antom provides access to local payment ecosystems, digital platforms and merchants. Digital wallets become distribution channels for AI subscriptions. And the payment provider manages much more than the transaction itself, including marketing, risk, billing, and account services.

For now, the objective is straightforward: make Google AI Plus easier to discover, access, and eventually monetize across diverse Asian markets. But the underlying infrastructure has broader implications. As AI assistants evolve from tools that provide information into agents that can act on behalf of consumers, they will need connections to the same commercial systems humans use today: merchants, marketplaces, payments, identity services, and logistics networks.

The companies controlling those connections could become increasingly important intermediaries in the next generation of digital commerce. Antom's partnership with Google Gemini offers an early example of how that infrastructure may develop—not by replacing local payment ecosystems, but by connecting global AI platforms directly to them.

The post Ant International and Google Gemini expand AI payments partnership across Asia appeared first on Cross-Border Magazine.

A major strategic divide is emerging over the future of agentic commerce. Shopify is opening its merchant ecosystem to Meta’s new AI shopping agent, Muse, while Amazon has taken the opposite approach and blocked the same agent from shopping on Amazon.com. The contrast reveals two very different visions of how AI should interact with online retail. Shopify appears willing to let third-party agents become a new commerce channel, while Amazon is defending tighter control over its marketplace, customer experience and commercial infrastructure.

On one side, Shopify is working with Meta so Muse can help users discover products and complete purchases across Shopify-powered stores using Shop Pay. On the other, Amazon says Meta did not obtain permission for Muse to access its marketplace and has blocked the agent from shopping on behalf of customers. The dispute raises a wider question for the entire e-commerce industry: should AI agents be welcomed as a new layer of distribution and checkout, or treated as external intermediaries that could weaken retailer control over customers, data and monetization?

Shopify embraces Meta’s Muse as an AI commerce channel

Shopify has chosen the more open approach. The company is partnering with Meta to integrate Shop Pay agentic checkout into Muse, allowing the AI assistant to facilitate purchases from merchants operating on Shopify. Shopify had already started preparing for this shift earlier in September by adding Meta as an AI channel inside Shopify Admin. Merchants can manage whether product catalogs are shared with Meta, control direct checkout access and monitor performance from within Shopify’s agentic-commerce settings.

This is significant because Shopify is not merely allowing Muse to browse merchant websites. It is connecting Meta to structured commerce infrastructure, giving the AI cleaner access to product data, availability and checkout functionality. That reduces the need for the agent to interpret conventional websites designed for humans. Instead, Shopify can act as the commerce layer beneath the AI interface, providing the product and transaction infrastructure while Meta controls the consumer-facing experience.

Shop Pay becomes the transaction layer

The partnership also highlights the strategic value of Shop Pay. Muse users will be able to complete purchases through Shopify’s accelerated checkout infrastructure across participating stores. That means the customer may begin and remain inside Meta’s AI environment while the transaction itself still flows through Shopify’s commerce stack. For Shopify, the loss of the traditional storefront as the primary interface does not necessarily mean losing the economic value of the transaction.

This is a critical distinction in the emerging agentic-commerce model. Shopify does not primarily depend on consumers visiting Shopify.com, because its business is built around providing infrastructure to merchants wherever commerce happens. If discovery increasingly moves into AI assistants, Shopify can still capture value through product feeds, checkout, payments and merchant operations. Its strategy therefore appears less focused on protecting the storefront and more focused on becoming indispensable infrastructure underneath AI-driven commerce.

Amazon takes the opposite approach

Amazon has chosen a far more restrictive position. The company blocked Muse from shopping on Amazon.com after Meta reportedly declined Amazon’s request to exclude its marketplace from the agent’s shopping capabilities. Users attempting to shop on Amazon through Muse began seeing a message stating that continued access by an unauthorized AI agent violated Amazon’s Conditions of Use. Amazon says the issue centers on authorization, transparency and how third-party agents interact with its platform.

According to Amazon, Meta did not provide advance notice that Muse would shop on Amazon.com, the agent does not adequately identify itself while browsing, and the company has concerns around customer credentials and account access. Amazon argues that third-party applications making purchases on behalf of users should operate transparently and respect whether a service provider wants to participate. The company’s position is that consumer permission alone is not enough; the merchant platform should also be able to decide whether an external agent can access and transact through its systems.

Meta disputes the credential-risk concern

Meta has said Muse does not directly see users’ passwords or payment credentials. According to the company, credentials are stored securely and can be used by the AI without being exposed to the model itself. Muse operates inside a virtual machine and can use a browser to interact with services when a public API is not available. Meta also says the agent seeks confirmation before taking sensitive actions such as sending messages or completing purchases.

This difference in interpretation is central to the dispute. Meta views the consumer as authorizing the agent to act on their behalf, while Amazon argues that the platform being accessed also needs to consent. That tension could become one of the most important legal and commercial questions in agentic commerce. It effectively asks whether an AI agent should be treated like a user-controlled browser, an automated bot, a commercial intermediary, or something entirely new.

Amazon wants AI agents to identify themselves

Amazon’s position is also closely linked to transparency and identity. The company argues that an external AI agent entering customer accounts, browsing product pages and initiating transactions should clearly identify itself to the retailer. This reflects a broader issue emerging across e-commerce and payments: merchants increasingly want to know which agent is acting, who authorized it, what permissions it has, whether it is operating within those limits and who is responsible if something goes wrong.

These are no longer theoretical questions. Payment networks including Mastercard and Visa are already developing identification and authorization layers specifically for AI agents. Amazon is effectively applying the same logic at the marketplace level. If agentic commerce is to scale, retailers may demand a standardized way to recognize trusted agents, verify user intent and establish accountability before allowing automated systems to interact deeply with their commerce infrastructure.

Shopify sees AI agents as another distribution channel

Shopify’s strategy appears fundamentally different. Rather than requiring consumers to begin every transaction within a Shopify-controlled environment, the company is treating AI assistants as another sales and distribution channel. This resembles the way Shopify already connects merchants with Google, social networks, marketplaces, mobile commerce and point-of-sale systems. Agentic platforms now become another route through which merchants can reach potential customers.

That approach fits Shopify’s architecture particularly well. Its value lies in powering merchants across multiple channels rather than owning a single consumer destination. If an AI platform becomes the place where shoppers discover and compare products, Shopify can still remain the system handling structured catalog data, merchant operations, payments and checkout. In that model, losing control of the interface does not necessarily mean losing control of the transaction infrastructure.

Amazon has more to lose from external agents

Amazon’s incentives are very different because its marketplace is not simply a transaction engine. The company controls product discovery, search, advertising, reviews, recommendations, checkout, fulfillment and customer service inside one highly integrated environment. External AI agents could bypass several of those layers by searching, comparing and selecting products on behalf of users without presenting Amazon’s traditional marketplace interface.

This matters because Amazon has built a huge advertising business around product discovery. Sponsored placements, search positioning and marketplace visibility are all tied to shoppers navigating Amazon directly. If an AI agent evaluates products based mainly on price, reviews, availability and delivery terms, some of the commercial value of those interfaces could be reduced. Amazon therefore has more strategic incentive than Shopify to preserve control over how shoppers discover and select products.

The fight is about who controls product discovery

This is why the Shopify-Amazon split matters beyond Muse itself. Agentic commerce is changing where product discovery happens. Today, shoppers typically search, browse, compare products, open listings, add items to a cart and complete checkout. An AI agent could compress that process into a single instruction such as: “Find me the best stroller under €500, with strong reviews and delivery before Friday.”

The agent could then search across multiple merchants, evaluate the available options and complete the transaction according to the user’s preferences. If that behavior becomes common, the center of gravity in e-commerce may move away from individual marketplace interfaces and toward AI platforms. The strategic question then becomes less about who owns the product listing and more about who owns the interface between shopper and merchant.

Shopify is betting on infrastructure, Amazon on ecosystem control

The two companies are effectively making different bets on the next phase of e-commerce. Shopify is betting that infrastructure remains valuable even if another company controls the consumer interface. Its role can still include catalog data, merchant operations, payments, checkout and order management. Amazon appears more determined to preserve control over both the infrastructure and the customer-facing environment, including search, advertising, recommendations and transaction flow.

Neither position is necessarily permanent. Amazon could eventually negotiate access agreements with selected AI platforms, while Shopify could impose stricter controls if agentic commerce creates problems for merchants. But the current split exposes two competing models. One is open and infrastructure-led, while the other is more closed and ecosystem-driven. Those models could shape how retailers interact with AI agents over the next several years.

Amazon is already challenging other AI shopping agents

Muse is not the first AI shopping agent Amazon has opposed. The company has also attempted to restrict access by agents from Perplexity, Google and OpenAI. Its dispute with Perplexity has already moved into the courts, where Amazon initially secured a preliminary injunction before a US appeals court later rejected part of its argument under federal anti-hacking law. Contractual claims based on terms of service remain a separate issue.

That legal background helps explain the language Amazon is now using with Muse. The company is framing the dispute around authorization and contractual access rather than purely around cybersecurity. This suggests Amazon is trying to establish a broader principle: AI agents should not assume unrestricted access to its commercial environment simply because an individual user authorizes them to act.

Amazon itself uses agentic shopping technology

Amazon is not opposed to AI shopping agents in principle. The company has developed its own agentic-commerce capabilities, including Buy for Me, which can help customers purchase products from external merchant sites, and Alexa for Shopping, which can research products and provide recommendations. Amazon argues that the difference lies in transparency and merchant consent.

According to Amazon, Buy for Me identifies itself when interacting with external merchants and allows businesses to opt out. That distinction reinforces the company’s central argument: the problem is not autonomous shopping itself, but how external agents enter and use another company’s commerce environment. In other words, Amazon supports agentic commerce when the rules of access are negotiated and visible to all participants.

Muse is gaining traction quickly

The dispute matters partly because Muse is already attracting significant attention. Meta launched the personal AI agent on September 8, positioning it as a system capable of handling multi-step tasks including shopping, appointment booking, email management and other everyday activities. Shortly after launch, Muse climbed rapidly through Apple’s US App Store rankings, indicating strong early consumer interest.

Growing adoption increases the urgency for retailers and commerce platforms to decide how they want to interact with these agents. For Shopify merchants, Meta represents a potential new source of product discovery and checkout. For Amazon, Muse currently represents an unauthorized intermediary operating inside a commercial environment Amazon has spent decades building and monetizing.

Agentic commerce could disrupt e-commerce advertising

Advertising may become one of the areas most affected by this shift. Traditional marketplaces monetize shopper attention by selling visibility within search results and product pages. Retailers pay to move products higher in rankings or increase exposure across marketplace interfaces. AI agents may operate differently, especially if they prioritize objective criteria such as price, delivery speed, return policies and product specifications.

If consumers increasingly delegate purchasing decisions to agents, traditional sponsored placement could become less influential. An AI may not respond to the same visual hierarchy and advertising formats as a human shopper. That creates a potential challenge not only for Amazon but also for Google and other platforms whose commercial models depend heavily on monetizing search and product discovery.

Merchants face their own strategic decision

Retailers will also need to decide how open they want to be to AI agents. Participation could bring significant benefits by creating new channels for product discovery, customer acquisition, conversion and cross-border sales. At the same time, merchants may lose some control over brand presentation, customer relationships, upselling and the overall shopping journey.

A consumer who shops entirely through Muse may never see the merchant’s homepage, marketing funnel or carefully designed product pages. Competition could therefore shift toward machine-readable factors such as price, stock availability, delivery speed, product attributes and returns. That would change how retailers think about optimization and could make structured product data increasingly important.

Structured commerce data becomes more valuable

Shopify’s role demonstrates this shift clearly. When Shopify shares catalog data directly with Meta, Muse does not need to scrape and interpret every merchant website independently. Instead, the agent can access standardized commerce information such as product descriptions, variants, prices, stock levels and checkout capabilities.

That gives Shopify an important strategic position in the agentic ecosystem. The company already sits between merchants and numerous external sales channels, and AI assistants can become another distribution layer connected to that infrastructure. As more shopping moves through agents, the platforms controlling high-quality structured commerce data may become increasingly valuable.

The future could split into open and closed commerce ecosystems

The Shopify-Amazon divide may point toward a broader fragmentation of agentic commerce. Some platforms may operate as open commerce infrastructure, allowing multiple AI agents to access catalogs and transactions through standardized integrations. Others may remain more closed, allowing only approved agents or proprietary AI experiences to participate.

The result could resemble earlier battles over mobile operating systems, app stores and platform APIs. Retailers and marketplaces may have to choose between reach and control, while AI companies may need to negotiate access to the largest commerce ecosystems rather than assuming they can browse and transact freely.

A defining battle over the next e-commerce interface

The dispute between Shopify, Amazon and Meta ultimately comes down to control. Meta wants Muse to become an interface through which consumers can complete everyday tasks, including shopping. Shopify sees an opportunity to make its merchant ecosystem accessible through that interface. Amazon sees an external agent entering a shopping environment it has spent decades building, optimizing and monetizing.

All three positions are commercially rational, but they point toward very different futures for e-commerce. Shopify’s model says the consumer can shop anywhere while Shopify provides the infrastructure underneath. Amazon’s model says the shopping environment itself remains strategically important and should not be accessed by third-party agents without permission. As AI shopping agents become more capable, the next major battle in e-commerce may not be over assortment or delivery speed, but over which AI is allowed to stand between the shopper and the store.

The post Shopify Opens Its Stores to Meta’s Muse While Amazon Blocks the AI Shopping Agent appeared first on Cross-Border Magazine.

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.

Stripe believes one of e-commerce's most familiar elements could eventually become obsolete. Will Gaybrick, Stripe’s President of Product and Business, has argued that the traditional checkout page could disappear as artificial intelligence, digital wallets, and agentic commerce increasingly collapse product discovery and payment into a single transaction.

Speaking on the A16z Show, Gaybrick said the checkout page could become unnecessary not only for AI agents, but eventually for human shoppers as well. His argument is straightforward: when payment credentials, identity and authorization are already securely available through tools such as Stripe Link, consumers should increasingly be able to purchase directly from the product or discovery interface rather than navigating several checkout screens.

The prediction offers a glimpse of how Stripe expects online commerce to change as AI agents become increasingly capable of finding products, evaluating options, and completing purchases on behalf of consumers.

From checkout page to instant transaction

The traditional e-commerce journey is familiar:

A customer discovers a product, visits a merchant website, adds it to a cart, proceeds to checkout, enters delivery information, chooses a payment method and confirms the order. Agentic commerce challenges almost every step of that model.

Stripe defines agentic commerce as online shopping in which AI agents can find, compare, and potentially purchase products on users' behalf. The shopper provides an objective — for example, finding a particular product under a certain price with delivery before a specified date — and the agent handles much of the searching and decision-making.

In this environment, the shopper may never need to navigate a conventional checkout page. Instead, product discovery, decision-making, authorization and payment could take place inside an AI assistant, search environment or other digital interface. Stripe explicitly notes that customers using an AI agent may not need to see a checkout page at all.

Why Stripe thinks checkout could disappear

Checkout disappearing doesn't mean the underlying processes vanish. Merchants would still need to calculate taxes, confirm inventory, determine shipping costs, process payments, prevent fraud, manage orders, and handle fulfillment. The difference is that those processes increasingly happen behind the interface.

Instead of presenting each step to a human shopper, commerce infrastructure could communicate directly with an AI agent. Gaybrick has pointed to systems such as Stripe Link and Shopify's Shop Pay as early examples of how stored payment credentials and accelerated checkout can already reduce the number of steps required to purchase online.

Agentic commerce takes that concept considerably further. Rather than simply speeding up a checkout page, AI could make the page unnecessary.

Stripe is already building infrastructure for agentic commerce

Stripe's prediction is closely connected to products the company has been developing over the past year. At Stripe Sessions 2026, the company expanded its Agentic Commerce Suite and announced additional partnerships with companies including Meta and Google. Stripe also introduced new ways for AI agents to pay using Link's agent wallet.

Stripe describes its Agentic Commerce Suite as infrastructure that connects businesses, agents, and buyers. Merchants can make their products available to AI agents while maintaining control over pricing, descriptions, fulfillment and the customer relationship. AI applications can then embed checkout directly inside their own interfaces.

This model represents a fundamental shift in the merchant website's role. Instead of every purchase requiring consumers to reach a retailer's checkout interface, transactions could increasingly be completed wherever the customer discovers the product.

AI agents need their own payment infrastructure

Giving an AI agent purchasing authority creates problems that conventional payment systems were never designed to solve.

An agent may need to:

• Identify the correct product;
• Confirm availability;
• Compare shipping options;
• Understand return policies;
• Operate within a spending limit;
• Prove that the consumer authorized the transaction;
• and complete payment without gaining unrestricted access to the customer's financial credentials.

Stripe has been developing infrastructure specifically for these scenarios.

Its Link wallet for agents can issue a one-time-use card or Shared Payment Token backed by payment methods already stored within Link. According to Stripe, the agent itself does not receive the user's underlying payment credentials. This allows agents to transact while preserving spending controls and payment security.

Stripe has also introduced Issuing for agents and other mechanisms designed to give autonomous software controlled purchasing power.

Machine Payments Protocol removes checkout entirely

The transformation becomes even clearer when commerce takes place between machines rather than between a human and a retailer. In March 2026, Stripe and Tempo introduced the Machine Payments Protocol (MPP), an open standard that lets AI agents transact directly with businesses and other services.

Traditional online payment flows assume that a human will visit a website, select a product, and complete a checkout form. MPP instead allows software agents to interact programmatically with paid services. Stripe says conventional financial infrastructure was built primarily for humans, meaning AI agents often struggle with tasks such as navigating pricing pages, selecting subscription tiers, creating accounts or entering payment details.

Machine-readable payment protocols are designed to remove those obstacles. If adoption grows, some forms of commerce may therefore never generate a visible checkout interface at all.

E-commerce UX could become commerce infrastructure

The implications for retailers could be substantial. For years, merchants have invested heavily in optimizing their checkout pages.

Businesses test:

• Button positioning
• Page layouts
• Payment methods
• Form length
• Guest checkout
• Upselling
• Cart recovery
• Conversion rates.

Agentic commerce could shift part of that optimization away from visible user interfaces and toward APIs, structured data, and machine-readable commercial rules. Stripe advises businesses preparing for agentic commerce to expose structured product information and build checkout flows that can function without a human directly interacting with them.

That means an AI agent needs reliable access to information including:

• Product availability
• Pricing
• Shipping times
• Returns policies
• Taxes
• Merchant identity
• Fulfillment guarantees.

In other words, the checkout experience increasingly becomes an infrastructure problem rather than purely a web-design problem.

Product discovery and checkout could merge

One of the biggest changes could be eliminating the boundary between discovering something and buying it. Today, discovery often happens outside the retailer's website.

Consumers may discover products through:

• Google
• Social media
• Marketplaces
• Influencers
• Comparison services
• Increasingly, AI assistants.

Historically, shoppers had to leave that environment and visit a merchant's checkout. Agentic commerce lets the transaction stay inside the discovery layer.

Stripe has already worked with OpenAI on the Agentic Commerce Protocol, designed to allow businesses to sell through AI interfaces while maintaining control over their transactions. Stripe said the protocol's first real-world implementation supported Instant Checkout inside ChatGPT.

The company is also working with AI and technology platforms including Microsoft Copilot, Anthropic, Perplexity, Vercel and others as it develops infrastructure for agent-driven commerce.

Merchants risk becoming invisible to AI agents

The change could also create a new form of competitive pressure. Traditional SEO focuses on ensuring that search engines can discover and understand a merchant. Agentic commerce introduces another audience: machines that are actively choosing which merchant should receive a transaction.

Stripe argues that businesses need structured product catalogs, clean APIs, transparent policies and real-time availability if they want AI agents to transact with them successfully. A retailer that is difficult for an AI agent to understand could theoretically become less competitive even if its consumer-facing website remains excellent.

The industry may therefore see the emergence of what could effectively become agent optimization alongside traditional SEO and conversion-rate optimization.

Trust remains the biggest challenge

Despite rapid technological development, agentic commerce still faces substantial barriers. Consumers must trust AI systems enough to allow them to spend money. Businesses must also distinguish legitimate AI agents from malicious automated systems.

Traditional fraud tools rely heavily on signals associated with human behavior, devices and payment credentials. Agent-initiated transactions can change those patterns. Stripe has acknowledged that agentic commerce challenges many assumptions built into existing permission and fraud systems.

Its Shared Payment Tokens, Link agent wallet and Stripe Radar infrastructure are designed partly to address this problem by attaching authorization and risk information to agent transactions. Human approval is also likely to remain important for many purchases, particularly expensive or sensitive transactions.

Agentic commerce therefore does not necessarily imply giving autonomous software unlimited purchasing authority. Instead, the emerging model relies on controlled delegation.

The checkout page may disappear, but checkout will not

Stripe's prediction should therefore be understood carefully. Commerce will still require authorization, payment processing, taxes, fraud prevention, shipping and fulfillment. What could disappear is the visible page where those processes traditionally come together.

For consumers, that could mean fewer forms, fewer redirects, and fewer abandoned carts. For merchants, however, it could require substantial behind-the-scenes changes. Retailers may increasingly need commerce systems that can communicate directly with AI agents while preserving pricing control, customer data, brand identity, payment security and fulfillment rules.

Stripe is betting that this transition will happen quickly. The company said during Stripe Sessions 2026 that it expects AI agents eventually to account for a significant share of online transactions and is positioning its payments infrastructure accordingly.

E-commerce is moving beyond the website

The broader significance of Gaybrick's comments is not simply that checkout pages may become shorter or more convenient.

They suggest that the website itself could gradually lose its position as the central interface of digital commerce.

In an agentic-commerce environment, consumers may increasingly interact with AI assistants rather than individual retailer websites. Those agents could search across merchants, evaluate products, negotiate constraints and complete transactions without reproducing the traditional browsing journey.

The merchant remains responsible for the product, pricing, payment and fulfillment. But the interface connecting the merchant to the consumer may belong to someone else. That makes Stripe's prediction about the death of the checkout page part of a much larger transformation. The next era of e-commerce may not be defined by better checkout pages. It may be defined by commerce that no longer needs them.

The post Stripe says traditional checkout pages could disappear in the Agentic Commerce Era 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.