AI Agents and Agentic Commerce: OpenAI, Stripe Reshape How Autonomous Systems Handle Payments

Agentic Commerce Protocol: How OpenAI and Stripe Are Reimagining the Future of Online Transactions: By Milko Filipov

AI-driven shopping is becoming one of the most significant shifts in modern e-commerce. As autonomous agents start handling tasks like comparing products, making purchases, and communicating with online stores, it's becoming clear that today's platforms -- built with human users in mind -- aren't fully equipped for this new reality. To address this gap, OpenAI and Stripe have developed the Agentic Commerce Protocol (ACP), a framework that makes transactions between AI agents, merchants, and customers secure and scalable. In many ways, ACP sets the foundation for a future where autonomous systems can participate in commerce smoothly and safely. Inside the Agentic Commerce Protocol At its core, ACP is a uniform and secure method for handling payments initiated by AI agents. When a user requests a purchase through an AI model such as ChatGPT, the protocol creates a Shared Payment Token (SPT). This token captures the customer's authorization while shielding private financial data -- including bank identifiers and card numbers -- from exposure. Merchants receive the SPT and simply process it through their existing payment setups, meaning ACP integrates smoothly with today's infrastructure without requiring extensive changes. Beyond payments, ACP also includes robust identity verification for AI agents. Only validated, permitted agents can interact with merchant systems, reducing the risk of unauthorized transactions. Every purchase is recorded in an auditable log, giving merchants full insight into agent-driven sales activity. Businesses can also apply governance features such as real-time fraud screening, spending limits, allowed merchant lists, or category restrictions -- tools that are essential as autonomous purchasing scales. And because ACP was designed with concurrency in mind, it supports large numbers of AI agents executing transactions at once, handling everything from multi-item orders to refunds and disputes. Together, these capabilities position ACP as a foundational technology for the next generation of AI-enabled commerce, distinctly more adaptive and transparent than traditional online payment flows. Why OpenAI and Stripe Make a Strong Team The collaboration brings together two leaders in their respective domains. OpenAI contributes the intelligence layer -- large-scale AI systems capable of interpreting consumer intent and coordinating purchases -- while Stripe provides the mature, globally trusted payment infrastructure required to process transactions reliably and at scale. The result is a protocol that is both technologically sophisticated and straightforward for merchants to adopt, accelerating industry-wide readiness for autonomous commerce. Implications for Merchants: Opportunities and Challenges Companies embracing ACP stand to benefit early from a new channel where AI agents influence or complete the purchasing process. Automated transactions may improve conversion rates, speed up decision-making, and increase customer satisfaction. ACP also preserves merchant ownership of the customer relationship -- from order management to customer support -- while enabling AI to drive efficient workflows in the background. However, businesses that postpone adoption risk losing ground to faster-moving competitors who leverage AI-driven interactions to create more seamless customer journeys. In a market where autonomous commerce is becoming integral, falling behind could mean losing both visibility and share. Looking Ahead: The Future of Autonomous Commerce ACP is still in its early stages, and its capabilities are expected to grow. Over time, we can anticipate integration with additional payment providers, expanded partnerships across AI platforms, and more advanced logic for sophisticated purchasing scenarios. As AI technology continues to advance, ACP is set to become a key facilitator of complex, interoperable, and intelligent digital commerce. If you'd like to understand how the ACP fits into the broader agentic commerce landscape, take a look at my earlier article on the topic.

Autonomous Agents Challenge Retailers to Earn Trust | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. "Buy in one click" became a shorthand for the ideal shopping experience: instant, invisible, effortless. This required compressing the distance between desire and purchase, removing steps, and, if possible, turning every moment into a shoppable one. But that era is already coming to a close, thanks to the rise of agentic AI. Findings in the November 2025 Payments Orchestration Tracker® Series, a PYMNTS Intelligence collaboration with Spreedly, reveal that AI agents, autonomous systems that shop on consumers' behalf, are poised to take convenience to its logical endpoint. This emerging next wave of digital commerce won't require clicks at all. Consumers will define an outcome, like, "keep me stocked," "find me the best deal under $50," "buy a replacement when this is about to expire," and an agent will simply make it happen. The question isn't whether this capability will exist. It's how retailers will make consumers feel comfortable using it. And that's not an impossible challenge. In fact, the path forward is achievable with deliberate design and clearer than the hype suggests. Consumers rarely shop in straight lines. They respond to moods, moments, small impulses, social cues, and personal preferences that shift from week to week. They browse aspirationally, comparison-shop for reassurance, and splurge unpredictably. They buy some things purely on habit and others only after a deep emotional assessment. That's why a first step can be ensuring any agentic AI systems interpret consumer intent as dynamic and contextual. A system that understands "keep my pantry stocked" should also recognize that brands, budgets, or diet preferences might change; that a sale might justify a bigger order; that a holiday requires more variety; and that certain items still require human approval. After all, consumers don't need to control every step of an automated process to trust it. They just need to understand what is happening and why. The report found that four in five consumers (80%) are more inclined to make purchases when brands provide a personalized experience, making agentic AI systems that are framed as collaborative partners rather than rigid executors potentially more attractive. Read the report: AI's New Age: Building Human Intent and Trust Into Agentic AI Still, one of the most important shifts required to make agentic retail viable is redefining what "control" means for consumers. Control does not require manually approving every action. It requires having the authority to set boundaries, adjust behavior, pause activity, and reverse decisions when needed. In practice, this means giving consumers the ability to shape agent autonomy on their terms. Some shoppers will want agents that suggest but never buy. Others will want agents that complete specific categories of recurring purchases. Some will delegate routine tasks entirely but maintain manual control over discretionary or emotionally driven categories like fashion, gifts, or beauty. The goal is not to automate everything; it is to automate the parts of shopping consumers are most willing to offload, without intruding on the parts they still enjoy. Agentic functionality will succeed when it blends into familiar environments rather than asking shoppers to adopt new behaviors. This continuity helps consumers see agentic systems not as a radical shift, but as an evolution of tools they already trust. Meeting customers where they are reduces friction and accelerates adoption far more effectively than dazzling them with novelty.

AI Agents Turn Issuers Into Real-Time Decision Makers | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. However, for issuers, retailers and the platforms connecting them, the emergence of AI agents that can complete multistep tasks end-to-end isn't simply another feature cycle. It's the start of a potential structural realignment set to rewrite how shoppers handle everything from finding a product to choosing the best payment method to executing the transaction. "The real transformation happens when payments are built directly into AI-driven workflows," Marqeta Chief Technology and AI Officer Fouzi Husaini told PYMNTS. "We envision agentic commerce becoming just a standard part of how the payment ecosystem works," Husaini said, adding that the issuers who will thrive as agentic AI capabilities mature will not be passive processors but active enablers. This is not a distant-future scenario. Powered by real-time data, flexible payment infrastructure and rapidly maturing autonomous agents, the AI shift in commerce is already reshaping how retailers, issuers and platforms think about their roles in the buying journey. In the next operating system of commerce, the payment isn't the end of the story but the beginning. This represents a shift from user-pulled to system-pushed commerce. As retailers have learned over the past decade, discovery is no longer the problem. Recommendation engines and content-driven shopping behaviors have multiplied opportunities for consumers to encounter new products. What has remained fractured is the leap from intent to purchase. Users still leave apps, break flows or fall out of channels altogether before converting. Each subsequent step serves as an opportunity for friction, abandonment and profit loss. In an AI-native environment, however, the traditional purchase funnel compresses into a single, often invisible action. Once authorized by a consumer, an AI agent handles everything that follows. "When payments are built directly into these AI-driven workflows... that eliminates friction points where consumers traditionally had to leave one experience to complete a transaction," Husaini said, citing Marqeta research that found 29% of surveyed U.S. consumers said they are interested in AI-powered wallets that automatically optimize payment choices based on their spending habits. In the traditional linear flow, the consumer starts at a merchant, checks out, and the issuer processes the transaction. Agentic commerce breaks that sequence. AI agents might initiate a purchase from a banking app, trigger a transaction from a card-linked service, or preemptively select an issuer-optimized payment method. Suddenly, issuers appear not at the end of the transaction, but at the beginning. "As AI agents take on more decision-making, issuers now have an opportunity to start to shift left and be present earlier in the purchase journey rather than at the point of transaction," Husaini said. The shift could have far-reaching implications. For retailers, it means the front door of commerce may no longer be the storefront. For issuers, it opens an opportunity to shape decisions rather than merely process them. For consumers, it introduces a future where their financial tools work autonomously and proactively. As agents take over the decisioning layer, retailers must ensure their products, prices and promotions are machine-readable and accessible. The interface of commerce may shift away from the retailer's own app or website to an AI layer sitting between consumer and brand. Retailers that fail to prepare risk losing visibility and relevance as agents steer consumers elsewhere. "Trust and security become even more critical when we're talking about AI agents executing transactions on behalf of customers," Husaini said, adding that as agents gain autonomy, the systems that secure transactions, from fraud detection to authentication, must evolve as well. The enabling layer underneath the rise of agents may ultimately prove more transformative than the AI bots themselves. Real-time data infrastructure and open, standardized interfaces are becoming crucial. For agents to execute tasks reliably, they need fast, permissioned access to account data, contextual information and transaction capabilities, without brittle or bespoke integrations. "You have to start with things being secure and accessible," Husaini said. That's where protocols like Marqeta's Model Context Protocol (MCP) server come in. Originally developed by Anthropic, MCP is quickly becoming a preferred way for AI systems to access structured contextual data. Marqeta's implementation allows AI agents to directly interact with payment infrastructure, doing tasks like pulling balances, initiating transactions, receiving real-time signals and more, all through standardized APIs. "It creates a direct connection between AI applications and payment infrastructure, dramatically reducing time to market," Husaini said, adding that intelligent credentials, driven by AI and powered by issuers, could increase top-of-wallet use. Husaini also said he foresees "new revenue streams and partnerships" for issuers as they transform into platforms for AI services. Instead of merely providing payment rails, they become orchestrators of intelligent commerce ecosystems, where agents plug in, execute tasks and operate autonomously.