Stripe/agentic-commerce

10 posts

stripe

What Link data tells us about AI spending (opens in new tab)

Link’s survey and transaction data show rapidly growing consumer engagement with AI. Among 250 million Link customers, spending on AI products—especially AI app-building platforms—has surged, with top spenders nearly doubling their monthly AI spending in one quarter. Stripe argues this growth points toward a need for payment infrastructure that allows AI agents to transact on users’ behalf. ### Growing Spending on AI Products - A survey of 394 Link customers found: - 80% had used a chat-based AI agent in the previous month. - 50% used AI for shopping research at least monthly. - The top 10% of AI spenders increased monthly spending from: - $183 in December 2025 - $359 in March 2026 - This cohort previously took 22 months to grow from $84 to $183, but doubled that amount in only three months. - Median spending also rose, from $60 to $72 per month. ### Strong Demand for AI App Builders - Spending growth was even greater for platforms such as Replit, Lovable, and Bolt. - The highest-spending Link customers now spend five times more each month on AI app-building platforms than they did in January 2025. - This suggests users are investing not only in AI tools, but also in platforms that let them create software with AI. ### Payments for AI Agents - As AI agents become more capable and common, they will need to purchase goods and services from businesses and potentially from one another. - Stripe’s Link wallet for agents is designed to support this activity by: - Letting users authorize agent payments. - Providing configurable spending controls. - Giving agents purchasing access across Stripe sellers. - Providing businesses with verified transactions without requiring custom integrations. Stripe’s data indicates that AI adoption is translating into substantial spending, particularly on AI development platforms. Businesses preparing for agent-driven commerce may benefit from supporting secure, user-authorized agent payments.

stripe

Five vertical SaaS insights from Sessions 2026 (opens in new tab)

Vertical SaaS platforms are responding to AI pressure by becoming more deeply embedded in customers’ operations rather than relying on software features alone. Payments, lending, compliance, and other financial or operational services create stronger retention and revenue opportunities, while AI products help platforms remain competitive at the software layer. The post concludes that platforms should monetize AI experimentally and prepare to support emerging agentic commerce. ## Expanding Beyond Software - AI makes software features easier to replicate, but vertical platforms retain an advantage through deep industry knowledge and workflow integration. - Embedded payments connect platforms to transaction processing, revenue tracking, and cash-flow management. - Median payments adoption increased from 27% in 2024 to 40% in 2025, while top Stripe platforms exceed 80%. - Successful companies make payments a company-wide priority: - Include payments in sales demos and compensation plans. - Set goals beyond Gross Payment Volume, including company-wide ARR. - Reinforce adoption through onboarding and customer success. - Embedded payments can generate approximately $4,200 in incremental ARR per adopting customer. - Platforms offering embedded financial products experience 11% lower annual churn, while multiproduct platforms grow revenue 49% faster than software-only peers. ## Building Operational and Financial Moats - Payments can lead to additional services such as capital, banking, cards, payroll, and bill payment. - TheCut’s Stripe Capital program generated $788,000 in accepted financing from 167 barbers within 24 hours. - Financial products help businesses purchase equipment, manage seasonal slowdowns, and fund marketing. - Operational services can also create defensibility: - Moxie embeds compliance tools to help medspas maintain licenses. - Slice negotiates wholesale pizza-box pricing for restaurants. - These specialized services are difficult for a new AI-native competitor to reproduce immediately. ## Developing Vertical AI Products - Most surveyed SaaS platforms—87%—see AI more as an opportunity than a threat. - Platforms are adding industry-specific AI tools, including: - Toast IQ, which identifies local food trends for restaurants. - Quipli, which generates leads from newly filed equipment-rental permits. - Clio’s assistant, which drafts legal documents, summarizes files, and surfaces client insights. - AI is positioned as a way to automate repetitive work while using the platform’s existing customer and industry context. ## Experimenting with AI Pricing - Eighty-six percent of SaaS platforms with AI features charge for them. - Pricing models include: - Bundling AI into existing subscriptions. - Premium tiers. - Stand-alone usage-based or outcome-based pricing. - Since 44% of platforms expect to change their AI pricing within a year, companies should test willingness to pay before committing to a model. - Charging separately can help determine whether AI delivers meaningful customer value. ## Preparing for Agentic Commerce - AI agents are expected to influence product discovery, purchasing decisions, and checkout. - Platforms are preparing with agent-readable catalogs and headless checkout APIs. - This infrastructure is intended to support a projected $5 trillion agentic-commerce opportunity. - Retail platforms still face foundational challenges, particularly inconsistent or poorly structured product data optimized for human shoppers. Vertical SaaS companies should combine AI innovation with deeper operational integration. The strongest long-term strategy is to offer industry-specific automation while using payments, financial services, and specialized workflows to become indispensable to customers.

stripe

Everything we announced at Sessions 2026 (opens in new tab)

Stripe announced 288 products and features at Stripe Sessions, focused on making payments more programmable, expanding the protection offered by its global network, and supporting AI-driven commerce. Major launches cover agentic payments, checkout optimization, fraud prevention, in-person payments, and merchant-of-record services. The overall direction is toward infrastructure that supports automated transactions, global commerce, and new usage-based business models. ## Agentic Commerce and Payments - The Agentic Commerce Suite lets businesses upload product catalogs and control how AI agents access them through the Stripe Dashboard. - Platforms can make connected accounts “agent-ready,” with discovery, checkout, payments, and fraud detection handled through one integration. - Partnerships with Meta and Google enable: - Native checkout inside Facebook ads. - Purchases through Google AI Mode and the Gemini app using the Universal Commerce Protocol. - The Machine Payments Protocol supports agent-driven microtransactions, recurring payments, and other programmatic transactions. - Agents can pay using stablecoins or fiat payment methods, including cards, Klarna, and Affirm, through Shared Payment Tokens and the PaymentIntents API. ## Link and Checkout Improvements - Businesses can authorize agents to pay through Link’s agent wallet while retaining spending controls and purchase visibility. - Link adds Pix and stablecoin support for US businesses, with UPI support in India previewed. - A new Dashboard view shows Link’s effect on conversion, authorization rates, and payment costs. - Checkout Studio will use AI assistance, transaction replay, A/B testing, and recommendations to configure and improve checkouts. - Stripe previewed an embedded Checkout form for interfaces such as sidebars, chat boxes, and modals. - More payment methods now support subscriptions, localized currencies, and cross-border payments, including Pix, UPI, Bizum, BLIK, Pay by Bank, and TWINT. - Adaptive Pricing AI can detect a customer’s preferred currency and localize subscription prices. ## Stripe Terminal and Managed Payments - The Stripe Reader T600 includes an eight-inch screen and can run custom applications for loyalty programs and upselling. - Terminal expands to 15 additional markets and adds payment methods such as Alipay, Klarna, and UnionPay International. - Standalone mode will allow businesses to accept payments without building a point-of-sale system. - Stripe Managed Payments is now available to all digital businesses as a merchant-of-record solution, handling indirect tax compliance in more than 80 countries, fraud, disputes, and customer support. ## Payments Optimization and Intelligence - Businesses can A/B test Authorization Boost against their existing payment performance. - New AI optimizations, including Data Only authentication and PINless debit retries, reportedly increase acceptance rates by an average of 3.8% and reduce processing costs by up to 3.3%. - Stripe 3DS can now be used independently for payments processed by another provider. - The Dashboard assistant can investigate payment performance, identify root causes, and recommend actions using natural language. ## Expanded Fraud Protection with Radar Stripe’s Radar upgrades target newer forms of abuse, including token misuse, account fraud, trial abuse, and fraudulent AI-agent activity. - Free-trial abuse prevention identifies risky trials without unnecessarily blocking legitimate customers. - Radar Signals can detect fraudulent payments, predict disputes and early fraud warnings, identify pay-as-you-go abuse, and detect multi-account or account-sharing behavior. - New merchant signals assess risks such as merchant delinquency and suspicious websites using LLM-powered analysis. - Stripe Issuing authorization signals extend fraud prediction to cards issued by other banks, fintechs, and payment providers. - Radar protection now covers additional payment types, including bank debits, wallets, BNPL, and stablecoins. - Custom Radar models combine a company’s own data with Stripe’s network intelligence. - Improved Checkout interventions use targeted measures such as CAPTCHAs to reduce fraud with less impact on conversion. - Smart Disputes can recommend evidence such as tracking numbers and usage logs, while an evidence library stores reusable documents like terms and conditions. ## Revenue and AI-Native Business Models Stripe also began upgrading its Revenue suite for AI-focused businesses. The announced direction includes real-time metering, rating, alerting, streaming payments, dimensional pricing, new Billing customizations, and broader access to query-ready data. The supplied post ends before detailing these Revenue features. Stripe’s announcements point toward a unified platform for global, automated commerce: businesses can sell through agents, optimize payments with AI, extend fraud controls across payment networks, and support flexible pricing models. Companies building AI products or international digital businesses should evaluate the new agentic commerce, Radar, Checkout, and Managed Payments capabilities as they become available.

stripe

Insights from Shoptalk 2026: How agents are changing retail (opens in new tab)

Agentic commerce is already reshaping retail, especially product discovery, embedded checkout, and customer engagement across AI-powered surfaces. However, retailers still lack a common strategy for managing product data, choosing channels, and deciding between first-party and third-party agent experiences. The article argues that success will depend not only on agent-compatible infrastructure, but also on strong brands, unified customer data, and frictionless checkout. ## Agentic Commerce Needs a Standard Framework - Retailers are experimenting with where to begin, which partners to use, and how to syndicate accurate product data across AI platforms. - Search and discovery are changing quickly: - Sephora is using loyalty data in its ChatGPT app to personalize recommendations and highlight benefits such as samples and free shipping. - OpenAI reported that more than half of its searches are discovery-oriented, with 70% containing detailed constraints or context. - AI agents increasingly function as storefronts. Brands that are not discoverable through these systems risk losing visibility. - Direct product feeds are becoming important because they provide agents with more structured and current information than web crawling. - Stripe’s Agentic Commerce Suite allows retailers to connect catalogs and syndicate them across supported agents without building separate integrations. - Many companies are using test-and-learn programs to measure how products are discovered, recommended, and purchased through AI surfaces. ## Commerce Is Expanding Beyond Chat Interfaces - Agentic commerce is appearing across: - Embedded checkout - Product discovery - Customer service - Catalog enrichment - Post-purchase systems - Meta demonstrated a Facebook checkout flow using the Agentic Commerce Protocol, allowing shoppers to move from an ad to product information, AI-generated review summaries, and in-app purchase. - New consumer brands may increasingly be built on agentic infrastructure, reducing customer acquisition costs and dependence on standalone websites. - Retailers must decide how much to invest in first-party experiences versus third-party agents across categories such as fashion, beauty, and home goods. - The market is unlikely to be controlled by one large language model or channel; instead, commerce will spread across many specialized applications and surfaces. ## Brand Trust Becomes More Important - As AI simplifies comparison shopping, trust, consistency, and emotional connection will play a larger role in brand selection. - New Balance is emphasizing consistent quality, store improvements, and better-trained associates rather than relying primarily on discounts. - Tapestry is studying Gen Z to maintain Coach’s relevance, while Victoria’s Secret is focusing on comforting, confidence-building store experiences. - Stitch Fix is using first-party customer data to power Stitch Fix Vision, an AI tool for personalized outfit visualization. - Retailers will need unified customer data and systems that preserve identity and context across websites, stores, apps, and AI agents. ## Checkout and Commerce Infrastructure Remain Fundamental - Customers arriving through agent-driven journeys may be ready to buy and less tolerant of checkout friction. - Stripe says its Optimized Checkout Suite selects payment methods using more than 100 signals and typically increases conversion by 2%–3%. - Core requirements remain unchanged: - Fast, branded checkout - Relevant payment methods - Effective fraud prevention - Connected online, in-store, and in-app commerce data - Stripe’s Agentic Commerce Suite is designed to let businesses connect their catalog and commerce systems once, then expand into compatible agents and channels. Retailers should begin with structured product data, measurable experiments, unified customer systems, and a frictionless checkout experience. Agentic channels are developing rapidly, but durable brand value and strong commerce fundamentals will remain essential as those channels multiply.

stripe

Three of the biggest fraud trends from MRC Vegas 2026 (opens in new tab)

Fraud is becoming more automated, adaptive, and difficult to detect with traditional rules-based systems. At MRC Vegas 2026, leading fraud teams emphasized dynamic authentication, fraud controls embedded directly into agentic payments, and layered identity verification to address deepfakes and synthetic identities. The common goal is to reduce friction for trusted customers while applying stronger defenses where risk is highest. ## Dynamic Authentication Based on User Intent - Universal authentication creates unnecessary friction, increases false positives, and can cause businesses to lose legitimate customers and their long-term value. - Airbnb advocates building behavioral profiles over time to measure “high-trust velocity”—the likelihood that a user’s activity reflects legitimate intent. - Trusted users can proceed without additional challenges, while authentication is reserved for the small percentage of traffic proven to be risky. - Stripe Radar’s adaptive 3DS uses AI to trigger authentication only when transaction behavior appears unusual. - Stripe reports that eligible businesses have seen fraud reductions of more than 30% with this approach. ## Fraud Detection for Agentic Commerce - Ashley Furniture’s existing rules-based system handled different authorization needs for quick-ship products and custom orders. - That model became insufficient when AI agents began making purchases across channels. - Fraud detection must be part of the payment infrastructure and evaluate transactions in real time, rather than analyzing them only after purchase. - Stripe Shared Payment Tokens let agents use a customer’s saved payment method without exposing payment credentials. - Combined with Stripe Radar, these tokens transmit risk signals such as potential disputes, card testing, stolen-card usage, and issuer declines. - These signals help distinguish legitimate, high-intent agents from low-trust automated bots. ## Deepfakes and Synthetic Identity Fraud - Fake identities are easier to create because criminals can access document templates and generative AI impersonation tools. - Fraudsters may produce convincing fake IDs, images, voices, and videos with limited resources. - Effective verification depends on identifying inconsistencies that forgeries fail to reproduce, such as incorrect signatures, mirrored photos, or mismatched expiration dates. - No single verification check is reliable enough; multiple independent checks are necessary. - Stripe Identity uses AI to detect fake documents and spoofed photos, compare ID images with selfies, and validate Social Security numbers and addresses against databases. Businesses should replace blanket controls with risk-sensitive interventions: minimize friction for trusted users, integrate fraud detection into agent-driven payment flows, and use layered identity verification to catch increasingly convincing forgeries.

stripe

Introducing the Machine Payments Protocol (opens in new tab)

AI agents are moving beyond chatbots toward autonomous systems that plan, act, and evaluate results, creating demand for agent-friendly commerce. Stripe and Tempo are launching the Machine Payments Protocol (MPP), an open standard that lets agents make programmatic payments to businesses and services. MPP supports microtransactions, recurring payments, stablecoins, fiat, and existing Stripe payment methods without requiring human intervention. ## The Challenge of Agent Payments - Traditional financial workflows are designed for humans. - Agents often cannot independently: - Create accounts - Navigate pricing and subscription options - Enter payment details - Configure billing - These obstacles limit agents’ ability to purchase services and participate in the internet economy. ## How the Machine Payments Protocol Works - An agent requests a resource from a service, API, MCP server, or other HTTP endpoint. - The service returns a payment request. - The agent authorizes payment. - The requested resource is delivered automatically. - Stripe businesses can integrate MPP through the PaymentIntents API with only a few lines of code. - Payments appear in Stripe’s existing API and Dashboard and settle through the business’s normal balance, currency, and payout schedule. - Standard Stripe capabilities remain available, including tax calculation, fraud protection, reporting, accounting integrations, and refunds. ## New Agentic Business Models MPP is already enabling agents to pay for services such as: - Browserbase: headless browsers billed per session - PostalForm: printing and mailing physical documents - Prospect Butcher Co.: ordering food for pickup or delivery in New York City - Stripe Climate: making programmatic contributions - Parallel Web Systems: paying per API call for web access Payments can use stablecoins, cards, buy now, pay later methods, and Shared Payment Tokens. ## Stripe’s Agent Economy Infrastructure Stripe positions MPP alongside its broader Agentic Commerce Suite, Agentic Commerce Protocol, MCP integrations, and support for x402. Together, these tools are intended to help businesses sell directly to agents and support new automated commerce patterns. Businesses interested in enabling agent payments can review Stripe’s MPP documentation and join the early-access program.

stripe

10 things we learned building for the first generation of agentic commerce (opens in new tab)

AI-driven commerce is emerging quickly, but making it reliable requires much more than adding an AI checkout button. Sellers must manage fragmented catalog integrations, real-time inventory and variant data, evolving protocols, secure payment tokens, fraud detection, fulfillment, and post-purchase operations. The central recommendation is to use adaptable infrastructure and begin with a limited, measurable product selection rather than launching an entire catalog at once. ## Catalog Integration and Data Quality - Product catalogs are the entry point for AI agents, but each agent may require a different format, such as: - SFTP file drops - Custom APIs - Agent-specific feed specifications - Reformatting the same catalog for multiple agents creates a costly maintenance burden. - Reliable “ingestion-ready” data determines whether products appear consistently across AI shopping surfaces. - A shared commerce layer can syndicate one catalog across supported agents and eliminate duplicate integrations. ## Real-Time Inventory and Product Variants - Agents need to verify current availability immediately before presenting checkout options. - Inventory becomes harder to manage when products include combinations of: - Sizes - Colors - Customizations - Variant-specific availability - Checkout APIs must support real-time availability checks and alternative recommendations when a particular configuration is unavailable. - Real-time accuracy is essential for customer trust and brand reputation. ## Protocol Evolution and Compatibility - Agentic commerce protocols are changing rapidly, with new releases adding payment handlers, scoped tokens, discounts, buyer authentication, and transport methods. - Sellers risk creating “zombie integrations” that become obsolete when an AI platform changes direction. - A protocol-agnostic commerce layer can help businesses support standards such as ACP and Google’s UCP without rebuilding their systems for every change. ## Secure Payments Through Shared Payment Tokens - Shared Payment Tokens allow agents to initiate payments with a buyer’s permission without exposing payment credentials. - The token layer connects AI agents to existing payment rails while limiting transaction scope. - Agentic commerce requires more than payment authorization; systems must also support: - Product discovery - Checkout state management - Shipping - Returns and refunds - The broader infrastructure must cover the full transaction lifecycle. ## Fraud Detection Without Human Browser Signals - Traditional fraud tools often depend on signals such as mouse movements, browser fingerprints, device details, and window size. - Those signals disappear when an AI agent performs the transaction. - Network-level payment history can provide risk context even when a purchase is new to a particular seller. - Shared Payment Tokens allow fraud systems such as Radar to evaluate agentic purchases similarly to traditional checkout transactions. - Early deployments with major retailers reportedly experienced fraud rates near zero. ## Start with a Focused Product Selection - Sellers should avoid enabling their entire catalog immediately. - A practical launch strategy is to: - Select a small group of high-conversion SKUs - Use simple products with direct-to-home fulfillment - Monitor conversion, inventory behavior, payment methods, and fulfillment issues - URBN initially focused on popular categories such as dresses and denim rather than its full range, which also includes complex products like plants and custom furniture. - Early launches should function as controlled experiments that produce data for broader expansion. ## A Strategic Shift in Retail Discovery - Agentic commerce moves buying intent from stores, websites, and branded mobile apps onto AI platforms. - This changes how sellers must approach: - Product discovery - Brand control - Trust - Dispute resolution - The relationship between the seller and customer - Agents increasingly mediate product selection and purchase decisions, requiring sellers to adapt their commerce strategy beyond the traditional storefront. Sellers should treat agentic commerce as an evolving channel rather than a one-time integration. Start with reliable data, a narrow product scope, secure tokenized payments, and infrastructure that can absorb protocol changes before scaling to more products and complex fulfillment scenarios.

stripe

Supporting additional payment methods for agentic commerce (opens in new tab)

Stripe is expanding Shared Payment Tokens (SPTs) to support more payment methods for agentic commerce. SPTs now cover Mastercard Agent Pay, Visa Intelligent Commerce, and BNPL options from Affirm and Klarna, allowing AI agents to make authorized purchases without accessing customers’ underlying payment credentials. Stripe says this makes it the first provider to combine agentic network and BNPL tokens through one payment primitive. ## Expanded Support for Agentic Payments - Sellers interact only with SPTs; Stripe provisions and manages the underlying payment tokens. - Businesses already processing payments through Stripe automatically gain access to these methods in agentic transactions. - The new capabilities are already being used to process payments across supported AI agents. ## Network-Led Payments from Mastercard and Visa - Mastercard and Visa issue secure agentic network tokens that let authorized AI agents initiate payments on a customer’s behalf. - Stripe provisions a token based on the customer’s purchase intent and shares it with the agent. - Agents can reuse the token across participating sellers and locations where Mastercard or Visa are accepted. - Payment networks translate the token to the latest underlying card number, verify and authorize transactions, and support fraud and dispute management. - Additional authorization data helps issuers make better provisioning and transaction decisions. ## Affirm and Klarna for Agentic Commerce - Stripe is adding SPT support for Affirm and Klarna, enabling agents to offer installment payment options. - BNPL transactions now exceed $300 billion globally, and Stripe reports up to a 14% revenue increase in BNPL-eligible sessions. - When a customer chooses BNPL, Stripe displays the provider’s confirmation flow in the agent interface and securely passes seller credentials to the provider. - The customer experience remains familiar while Stripe handles the integration details. Stripe plans to add more payment methods to SPTs, broadening the range of payment options available to customers and AI agents.

stripe

The three biggest agentic commerce trends from NRF 2026 (opens in new tab)

Agentic commerce is moving from an experimental idea to an implementation priority for retailers. At NRF, roughly 75% of attendees said they were implementing or planning agentic commerce, while major platforms such as Microsoft and Google introduced new shopping infrastructure and protocols. Retailers are responding by gradually preparing their catalogs and building both third-party agent integrations and proprietary AI shopping experiences. ## Retailers Are Moving from “If” to “How” - Retailers are now focused on scaling agentic commerce while preserving trust, brand identity, and control. - Stripe reported adoption by brands including URBN, Etsy, Coach, Kate Spade, Revolve, and Abt Electronics. - More than 25 ecosystem partners, including Salesforce, Squarespace, and PwC, endorsed Stripe’s Agentic Commerce Protocol (ACP). - Microsoft’s Copilot Checkout will let users purchase from Etsy and URBN brands without leaving the chat. - Google introduced the Universal Commerce Protocol (UCP), joining ACP and other emerging agentic commerce standards. - Stripe says its Agentic Commerce Suite will support multiple protocols through a single integration. ## Retailers Are Building Agent-Ready Catalogs Incrementally - Effective agent shopping depends on structured, current product feeds containing accurate descriptions, prices, availability, attributes, and taxonomy. - Large retailers may have thousands or millions of products, making full catalog optimization impractical as a first step. - URBN began with high-impact categories such as dresses and denim. - The company standardized product language, attributes, and taxonomy in those categories before expanding. - This focused approach allows retailers to demonstrate value quickly rather than attempting a costly catalog-wide transformation. ## Retailers Are Developing Their Own AI Shopping Experiences - Retailers are concerned that relying exclusively on third-party agents could weaken customer relationships and loyalty. - First-party AI tools can use customer and purchase data unavailable to external platforms. - Home Depot’s Magic Apron provides website-based, personalized assistance grounded in the retailer’s existing customer relationship. - Ralph Lauren’s Ask Ralph creates shoppable outfit combinations based on customer prompts. - The emerging model combines third-party agents for product discovery with first-party experiences for deeper personalization and brand engagement. ## Infrastructure for Agentic Commerce - Stripe’s Agentic Commerce Suite connects a retailer’s product catalog to selected AI agents through the Stripe Dashboard. - It supports checkout, payments, fraud detection, and order events. - Retailers can continue using their existing commerce systems while adding agent-based sales channels. Retailers should treat agentic commerce as a practical, staged rollout: begin with high-value product categories, improve catalog data incrementally, support major commerce protocols, and build first-party AI experiences alongside third-party integrations.

stripe

Introducing the Agentic Commerce Suite: A complete solution for selling on AI agents (opens in new tab)

Stripe’s Agentic Commerce Suite is designed to help businesses sell through AI agents without building separate integrations for every platform. It provides product discovery, checkout, payments, fraud protection, and order-event handling through a single, modular integration while allowing merchants to retain their existing commerce systems. The suite is rolling out through Stripe, ecommerce platforms, and omnichannel commerce providers. ## The Integration Challenge - Supporting each AI agent can require up to six months of work. - Businesses otherwise need to maintain: - Public, versioned ACP endpoints - Agent-specific catalogs and APIs - Access controls and commerce-stack integrations - The Agentic Commerce Suite aims to standardize these requirements. ## Making Products Discoverable - Merchants connect their product catalog to Stripe or import it from supported product syndicators. - Stripe provides a hosted Agentic Commerce Protocol (ACP) endpoint. - Product, pricing, and availability data can be shared with AI agents in near real time. - Merchants can select supported AI agents in the Stripe Dashboard and enable payments with minimal additional work. ## Simplifying Checkout and Order Management - Stripe Checkout Sessions API supports agentic checkout, including taxes and shipping. - Businesses can use Stripe Tax and other Stripe products or continue using their existing systems for: - Tax codes - Inventory checks - Dynamic shipping rates - Existing order management and fulfillment workflows remain in place. - Merchants stay responsible for customer relationships, refunds, and disputes as the merchant of record. ## Agentic Payments and Fraud Protection - AI-agent transactions introduce different fraud risks because automated traffic can resemble suspicious activity or be manipulated by attackers. - The suite supports Shared Payment Tokens (SPTs), which let agents use a buyer’s saved payment method without exposing payment credentials. - SPTs can be restricted by: - Seller - Time period - Transaction amount - Tokens are observable throughout their lifecycle to help prevent unauthorized actions and disputes. - Stripe Radar can evaluate risk signals such as card testing, stolen cards, issuer declines, and likely fraudulent disputes. ## Availability and Adoption - Early participants include Etsy, URBN brands, Ashley Furniture, Coach, Kate Spade, Revolve, and others. - The suite will be available through: - Stripe Dashboard and APIs - Wix, WooCommerce, BigCommerce, Squarespace, and commercetools - Omnichannel platforms including Akeneo, Mirakl, Pipe17, and Rithum - Businesses can join the waitlist and consult Stripe’s integration guides. Businesses seeking to sell through AI agents can use the suite to avoid bespoke integrations while preserving their existing catalog, checkout, fulfillment, and customer-service operations.