Agentic Commerce: The New Era Where AI Buys, Sells, and Pays for You

Want to know a new viral trend on Tik Tok. It’s not six seven. (and if you don’t know what 6-7 means, that’s what the kids are saying these days. If you don’t know what it means, just call over your preteen or teenage kid. They will happily explain it to you.)

Something strange is happening on Tik Tok. There is a trend where girls are showing what ChatGPT is suggesting to them after they have given it a photo of their face. It’s called the ChatGPT GlowUp. Why go to my expensive dermatologist if I can get the same suggestions on ChatGPT?

Go ahead. I’ll give you a few moments to try it on ChatGPT.  

Impressed?

This is just the start of something new. A few days ago PayPal signed a partnership with ChatGPT to be the recommended payment provider while shopping on ChatGPT. While most of us are uncomfortable handing over credit card details, they have found a way around it which is using our PayPal credentials.

Soon, we will have AI agents shopping on behalf of us. That’s Agentic Commerce: a world where AI agents act, negotiate, and transact on behalf of humans and businesses.

Not long ago, shopping online meant clicking “add to cart.” Today, it’s evolving into something radically different. Imagine this: your personal AI agent knows your skin type, tracks your favorite brands, waits for a discount, then buys your moisturizer automatically. You never open an app, never type a credit-card number, never even think about it.

What Is Agentic Commerce?

Agentic Commerce is the next leap beyond e-commerce and automation. It’s a system where autonomous AI agents make commercial decisions: researching products, comparing options, and executing purchases or payments.

Unlike traditional e-commerce that requires user input, agentic commerce thrives on machine-to-machine transactions. It combines language models, APIs, and payment protocols to create a seamless loop of intent, decision, and payment.

But there's a big problem. Our entire global payments infrastructure was built for humans, not autonomous AI agents. Today's payment systems assume a human is directly clicking buy. When autonomous agent initiates a payment, it breaks this assumption and raises some questions.

How can we prove that a user gave an agent specific authority to make a particular purchase?

How can a merchant be sure an agent's request is accurate and not just a hallucination?

And if there's fraud involved, who's accountable? The user, the merchant, the issuer, or even the AI model?

The Three Nodes of Agentic Commerce

Consumers: The Personal AI Layer

Your AI agent learns from your conversations, preferences, and purchase history. It knows your favorite colors, your sustainability goals, and your spending limits. Soon, you’ll delegate recurring purchases or complex comparisons entirely to these agents.

Brands: The Machine-Readable Layer

For brands, success depends on being found, understood, and trusted by AI agents. This requires Answer Engine Optimization (AEO) clear, structured data that answers questions the way an AI parses them. Product metadata, customer reviews, and schemas will matter more than website design.

Payments: The Protocol Layer

Banks and payment networks are creating the connective tissue for this ecosystem. Visa, Mastercard, and Google’s AP2 all serve as communication protocols for autonomous commerce, ensuring transactions between human or non-human agents can occur securely and instantly.

Early Signals and Real-World Examples

• Visa’s experiments with AI-driven transaction approvals where agent identity and intent are verified through behavioral biometrics.

• Mastercard’s collaboration with LayerZero Labs to explore cross-chain payments for autonomous agents.

• Alipay and WeChat Pay, which already support smart contracts enabling AI-triggered purchases in China.

• Startups like MindOS and CommerceLayer, building APIs that let AI agents interact directly with product catalogs and logistics data.

These are not proofs of concept. They are the infrastructure of a new economy forming beneath our feet.

Implications for Stakeholders

For Brands:Your digital shelf is no longer designed for humans. It’s designed for machines. Brands must structure data for conversational discovery, add schema markup, and train AI copilots on product knowledge.

For Retailers:The shopping cart is becoming invisible. Retailers should focus on trust signals, authenticity verification, and seamless back-end integrations to support AI-initiated purchases.

For Banks and Payment Networks:The challenge lies in creating interoperability and compliance between human and AI agents. Banks must rethink fraud detection, KYC, and liability for non-human actors.

For Consumers:Decision fatigue disappears, replaced by intelligent delegation. The consumer’s role shifts from choosing to training their AI.

Risks and Regulation

As agents gain purchasing power, new risks emerge. Who is liable if an AI overspends or gets tricked by synthetic data? What happens when fake agents infiltrate marketplaces?

Regulators will need frameworks for AI identity, consent, and auditability. Financial systems must develop “Agent Authentication Protocols” to distinguish between human and non-human participants in a transaction.

The Future: When Commerce Becomes Collaborative

In the near future, AI agents will collaborate. A home-energy agent might negotiate directly with an appliance agent to reduce power costs. A travel agent might coordinate with an airline’s AI to find an empty seat in real time.

Commerce becomes an ecosystem of agentic orchestration, where multiple AIs interact fluidly across industries. Marketing, logistics, and finance converge into a single, intelligent system. This is where Agent-to-Agent Protocol comes in. A2A, developed by Google, is a communication protocol and interaction model that empowers autonomous AI agents to coordinate, negotiate, and complete tasks directly with one another, minimizing the need for human intervention. Built for interoperability, A2A enables agents—regardless of vendor, architecture, or environment—to securely exchange capabilities, status, and context through standardized protocols like JSON-RPC and HTTP. This accelerates enterprise adoption of autonomous workflows and allows intelligent agents to operate efficiently in real-time, cross-platform marketplaces.

A Call to Action: A.C.T. Framework

The shift is already underway. The question is not if but how fast your organization can adapt.

Follow the A.C.T. framework to prepare for agentic commerce:

• Align your data and brand assets so AI can understand and represent them.

• Connect with agentic protocols and APIs that enable autonomous transactions.

• Train your teams to collaborate with AI, not compete against it.

The future of commerce won’t be won by those who have the best stores, but by those whose agents communicate best.