Agentic AI: Reshaping Commerce and Business Operations

How agentic AI will change commerce as we know it | Fortune

Throughout history, we've witnessed breakthroughs that didn't just improve things -- they've also completely reshaped human experiences. In commerce, similar paradigm shifts have repeatedly altered how people shop and how businesses operate: the first cash register changed bookkeeping; the introduction of the barcode completely changed global logistics; and the arrival of the internet changed our reliance on physical stores. Today, the world of retail and payments stands on the verge of another such monumental moment: agentic commerce. Agentic commerce is a fundamental shift that will reshape how consumers discover, search, and purchase products. In the coming years, shoppers will embrace AI agents that discover products, compare options, negotiate prices, and complete purchases to give them exactly what they want, at prices that work for them. Unlike predictive AI (which helps us forecast), or generative AI (which helps us create), agentic AI takes the crucial step of taking action on a person or company's behalf. It goes beyond traditional e-commerce to a truly assistive experience -- whether on a consumer's own device or through a retailer's site -- that feels like a personal shopper for every consumer. By next year, we anticipate a significant rise in consumers interacting with AI agents to manage their shopping, from initial intent to final receipt. For merchants, the agentic era introduces two new interaction models for connecting with customers. First, merchants can own the consumer experience from product discovery to checkout. This model requires creating a branded, conversational agent that can interact with a shopper's AI agent. For example, a consumer could instruct their agent: "I'm going to the Canadian Rockies in August and am not sure what to wear. Can you recommend a couple of outfits in my style?" The merchant's agent could communicate with the shopper's AI agent to access permissioned shopping data to provide more relevant recommendations based on the consumer's style and budget preferences. The second model involves operating as a fluid ecosystem player, prioritizing the sale no matter where it originates -- from a consumer's agent, another merchant's platform, or from something different altogether, like a social app. Imagine a consumer asks the merchant's agent to purchase a product that is not in its catalog or is currently out of stock. Instead of losing the sale, the agent could interact with other retailers' agents to source the item, complete the transaction, and fulfill the order -- creating a frictionless and endless shopping experience that puts the shopper's needs first. For payments providers, agentic commerce is a fundamental shift in the transaction process. It replaces the standard checkout experience with a direct, automated connection between personal AI agents and merchant AI agents. These smart agents can handle everything from price tracking to fraud detection, making transactions faster and inherently more secure. However, having a human in the loop will be important to ensure that critical, high-value transactions initiated by autonomous agents on behalf of a person are reviewed and verified by that person. To enable these new interaction models, interoperability is crucial, and the industry is championing protocols like the Agent Payments Protocol (AP2), an open, payment-agnostic framework for secure, trusted, and seamless agent-led transactions that already has partners like Mastercard and PayPal on board. With AP2, both consumers and merchants can unlock new ways of interacting with each other. For example, a user could instruct their AI agent to book a round-trip flight and a hotel for a specific weekend with a total budget of $1,500, and then the agent can find a combination that fits and securely book both simultaneously. The shift to agentic commerce is happening now. To take advantage, I believe there are four core areas where executives must focus: There's no doubt the future of commerce will be agentic. The time to build the foundation for this industry shift is now. As AI becomes more sophisticated, commerce will move far beyond transactions to anticipating and managing our needs autonomously. Business leaders who act decisively today won't just keep pace; they will help engineer the future.

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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. The authors describe agentic AI as a "team of digital colleagues" capable of autonomous reasoning, planning and coordination across departments, freeing organizations from the limits of rules-based automation. Case studies from Hitachi Digital, NTT DATA and Bigblue show how these systems can rewire complex operations by turning fragmented, multi-system environments into seamless, outcome-driven workflows. To do this successfully, organizations must appoint "mission owners" who define and oversee goals, empower AI agents to act toward them and structure work around results rather than departments. The authors outline three imperatives for building agentic AI systems: design around outcomes and clear accountability; unlock data silos through shared business logic rather than perfect data centralization; and develop leaders and governance frameworks capable of supervising autonomous systems responsibly. They stress that agentic AI doesn't demand flawless or unified data. It does demand interoperable systems, clear logic and human oversight. Leaders, they write, must be willing to delegate to digital teammates while maintaining guardrails for transparency, security and escalation. Companies that begin with high-friction workflows, assign ownership and build governance into design will, they conclude, "write the playbook for the operating model of the future." "Agentic AI marks a significant evolution in intelligent automation," the article states. "Guided by human supervision, it becomes an intelligent layer that links scattered processes and cuts through silos into a more seamless flow." In order for agentic commerce to work, it will of course need to be secured. Cloudflare's October 2025 blog post, "Securing Agentic Commerce: Helping AI Agents Transact with Visa and Mastercard," by Rohin Lohe and Will Allen, explains how the next phase of digital payments, commerce executed by AI agents, will require a new trust framework between consumers, merchants and payment networks. To that end, Cloudflare is partnering with Visa and Mastercard to develop infrastructure that authenticates AI agents through cryptographic protocols. Visa's Trusted Agent Protocol and Mastercard's Agent Pay both rely on Web Bot Auth, a Cloudflare proposal that uses public-key cryptography and HTTP message signatures to verify that an agent acting on a consumer's behalf is legitimate, authorized and non-replayable. This system lets merchants instantly recognize registered agents and determine whether they are browsing or making payments, without confusing helpful AI assistants for malicious bots. Cloudflare's approach makes agentic transactions verifiable across the full ecosystem -- developers, merchants, networks and consumers -- without overhauling existing merchant infrastructure. The authentication flow allows Cloudflare to validate agent requests by checking cryptographic keys, timestamps and nonce uniqueness before forwarding a verified transaction. Over the coming months, Cloudflare plans to integrate Visa's and Mastercard's protocols into its Agent SDK, enabling developers to easily manage agent keys, create valid signatures and transact securely using standard APIs. This shared security layer, the company notes, ensures that trusted agents can interact with merchant sites safely while maintaining full compliance with payment networks' trust requirements. As the authors put it, "The era of agentic commerce is coming, and it brings with it significant new challenges for security." Banks are starting to add their own flavor of thought leadership to the agentic debate as well. In a piece titled "Agentic AI: A Strategic Shift in Business Evolution," UBS Chief Technology Officer and Technology Fellow Mitra Heravizadeh positions agentic AI as a foundational inflection point, not a passing trend. For UBS, becoming an "AI-enabled institution" means embedding autonomous intelligence directly into its operational fabric, from decision-making and market prediction to client engagement. Heravizadeh writes that AI agents will function as "intelligent collaborators," executing multi-step tasks once handled by humans and enabling a move from reactive problem-solving to proactive opportunity creation. To achieve this, UBS is re-architecting its digital infrastructure around agility, interoperability and continuous learning, what it calls the core design principles of the agentic enterprise. The post details how UBS is restructuring its operating model to manage and govern AI agents responsibly. IT teams will evolve to oversee autonomous systems through defined permissions, behavioral monitoring and compliance oversight. To scale this transformation, UBS has created an Agentic AI Center of Excellence (CoE) to coordinate innovation and maintain ethical, secure and standardized deployment across engineering, data science and compliance teams. The CoE's mission is to establish a shared language and governance blueprint so AI agents can "communicate, collaborate, and operate together in a compliant, secure, and ethical manner." As Heravizadeh puts it, "Agentic AI is not a future trend -- it's a present reality," one that will shape the next era of financial innovation and institutional intelligence.