AI Agents Turn Issuers Into Real-Time Decision Makers

New applications of artificial intelligence technologies, from dynamic wallets to autonomous shopping agents, are compressing the distance across global commerce between intent and transaction to near zero.

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.

Agentic AI’s Role in Collapsing the Commerce Funnel

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.

A New Operating System for Commerce

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 Real-Time Infrastructure Beneath the Agents

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.

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