AI agents are starting to shape how online purchases happen. They can search for products, compare prices, check stock levels, and complete transactions without human input. Most of the attention so far has gone to how these agents communicate with card schemes, wallets, and payment providers. What has not been discussed nearly enough is how this shift affects merchants.

Merchants will carry the risk, complexity, and operational pressure of agent-driven payments. They already deal with rising fraud from automated systems. Now they must also accept payments that originate from autonomous agents that behave like bots, rely on new communication frameworks, and follow rules that vary by provider. This creates a real risk of fragmentation, higher costs, and new integration work.

Payment orchestration gives merchants a way to stay in control. It creates a unified layer between the agent, the wallet, the PSP, and the merchant’s internal systems. It also avoids the need to integrate with multiple agentic models that card schemes and PSPs introduce. For a broader look at how AI is already reshaping payments, Gr4vy explains it clearly in its guide on how AI is revolutionizing payments: how AI is revolutionizing payments

The goal for 2026 is simple. Merchants must adopt a payment strategy that keeps them independent, flexible, and protected while agentic commerce becomes part of daily transactions.

1. What AI-driven payments will look like in 2026

Agentic commerce is moving quickly from concept to reality. AI agents are expected to handle everyday purchases, especially routine or commodity items where shoppers value speed over personal involvement. An agent can be instructed to buy household goods, check for better prices, monitor stock levels, or reorder items when needed.

Higher-value or emotional purchases are less likely to be delegated at first, but the early signs point to rapid adoption for practical and repetitive buying. This could lead to a greater volume of agentic payments being concentrated among major retailers that already handle large shopping volumes at scale.

2. Why AI-driven payments create new challenges for merchants

Fragmented implementations

Visa, Mastercard, PayPal, and Stripe each have their own vision for how agentic commerce should work. None of them follow the same flow or communication model. Each expects agents to interact with their systems in a different way. This repeats one of the biggest problems from the early years of online payments. Merchants were forced to integrate separately with every provider. Payment orchestration emerged to fix that. The same challenge is resurfacing.

Without orchestration, merchants would have to support multiple agentic systems at once. This is costly, slow, and unsustainable.

Agents resemble bots

From a fraud perspective, agents and bots look almost identical. Merchants already see fraud attempts driven by automated tools, and that trend is growing. Since current anti-fraud systems cannot reliably tell the difference between a legitimate agent and a malicious bot, most agents would get blocked today. This creates friction and raises the risk of false declines.

Authentication and permissioning gaps

Agentic commerce requires authenticated relationships across multiple parties:

• The consumer must authorize the agent
• The agent must authenticate with the payment company
• The merchant must authenticate the agent
• The consumer must prove to the merchant that the agent has permission
• The merchant must authenticate itself back to the agent
  

There is no agreed system today that handles these interactions in a consistent way.

Merchant fraud and fake stores

Fake ecommerce storefronts are a rising threat. Agents cannot rely on intuition or visual cues to judge whether a store is legitimate. If an agent is not connected to a verified merchant directory, it may fall into traps created by fraudsters. This increases risk for both consumers and merchants.

Regulatory uncertainty

There are no clear rules yet on liability for agent-initiated payments. If fraud occurs, the merchant may carry the financial loss until regulators define responsibilities. Merchants should begin slowly, test cautiously, and factor potential losses into early experimentation.

3. Why payment orchestration becomes essential for AI-driven payments

A merchant-controlled layer

Orchestration gives merchants independence from PSP-specific implementations. Instead of building separate integrations for each card scheme or agentic framework, merchants can rely on a single orchestration layer that manages the variations. This prevents lock-in and keeps providers interchangeable.

One interface for multiple agentic mechanisms

If each payment company introduces its own agentic process, orchestration becomes the neutral control point that simplifies everything. The orchestration layer absorbs the complexity and presents a consistent interface for merchants.

Stronger control over agent-specific fraud handling

Agent-based transactions can be tagged and routed through specific anti-fraud tools. Merchants can apply custom limits, choose alternative risk engines, or route these transactions to specific PSPs. This lets merchants experiment safely while limiting exposure.

Avoiding shopping cart lock-in

If agentic solutions are built inside shopping cart systems, merchants become tied to whichever cart they use. Orchestration at the payment layer keeps the merchant free to choose their own commerce stack. Both layers can work together without creating dependency.

4. The Gr4vy approach to AI-driven, orchestrated payments

Gr4vy has already built and demonstrated an early version of agentic payment orchestration. Their approach is described in detail in payment orchestration for agentic commerce:
payment orchestration for agentic commerce

MCP servers inside single-tenant merchant instances

Gr4vy deploys single-tenant instances for each merchant, which allows it to run an MCP server inside every environment. MCP acts as a front-end specifically for agents. It mirrors what hosted checkout, secure fields, and API integrations already do for human-driven transactions.

Agentic Shopping Layer

This layer handles how agents search for products, check inventory, compare results, and interact with merchants. Gr4vy’s demo was built using Claude extensions, with multiple MCP servers registered as different merchants so that agents could choose between stores.

Inventory management

Merchants rely on their own systems or ERPs to manage inventory. Gr4vy built a bridge layer inside the MCP server that allows merchants to upload inventory data periodically. Future versions will support real-time sync.

Wallet Layer

In real deployments, the wallet may come from the card schemes or from existing wallet providers. For the demo, Gr4vy used its Vaulting capability to tokenize payment methods and let buyers add cards, verify them, set limits, and approve agent-initiated charges.

Agentic Orchestration Layer

This layer detects which token an agent uses, formats it, and hands it off to Gr4vy’s backend orchestration. It lets merchants route agentic traffic through their existing PSPs and workflows without changes to the core payment stack.

Backend Orchestration and Flow rules

Agentic transactions can be identified and routed differently from standard ecommerce traffic. Merchants can use alternative fraud tools, apply limits, or direct payments to specific PSPs. This allows gradual adoption while minimizing risk.

5. What still needs to be solved before 2026

• A verified directory of merchants and payment MCPs
• Clear KYB standards for agent onboarding
• More predictable consumer behavior for agent shopping
• Avoiding future walled gardens from AI platforms
• Clear regulations around fraud liability and dispute handling

These open questions will shape how fast agentic commerce becomes mainstream.

FAQ

What is agentic commerce?

Agentic commerce refers to transactions initiated and completed by AI agents on behalf of users. These agents can search for products, compare prices, check inventory, and purchase items without human input. It is expected to grow first in routine and repeat purchases.

Why do AI agents pose challenges for merchants?

AI agents behave like automated bots, which makes them difficult for fraud tools to identify as legitimate. Cross-party authentication is not standardized, and each payment company proposes a different agentic model. This creates more complexity for merchants than for PSPs or card schemes.

How does payment orchestration help with AI-driven payments?

Payment orchestration creates a neutral layer that connects agents, wallets, PSPs, and fraud tools through one integration. It prevents lock-in, reduces integration work, and lets merchants route agent traffic differently from standard ecommerce purchases.

What is an MCP server?

An MCP server is a framework that allows AI agents to communicate with external services. In Gr4vy’s model, the MCP server acts like a front-end for agents, helping them connect to the wallet layer, inventory data, and the orchestration layer in a controlled way.

How does Gr4vy manage agentic payments securely?

Gr4vy tags agentic transactions, routes them through custom rules in the Flow engine, and allows merchants to apply limits, use specific fraud tools, or send payments to different PSPs. This helps merchants adopt agentic commerce without exposing themselves to unnecessary risk.

Will AI agents replace shopper-driven checkouts?

Not in the short term. Early use cases focus on commodity items and routine purchases. High-value or discretionary buys are still likely to involve the shopper. Over time, adoption will depend on trust, regulation, and the tools merchants put in place to support safe agentic transactions.

AI-driven payments will change how online purchases work, especially for everyday items that benefit from automation and speed. This shift brings new challenges for merchants, from fragmented agentic systems to fraud, authentication gaps, and unclear regulatory rules.

Payment orchestration provides the structure merchants need to stay flexible while exploring agentic commerce. With single-tenant architecture, an MCP layer, vaulting, and flow-based routing, Gr4vy gives merchants a safe and independent path into this new era of payments.

Contact Gr4vy to explore how orchestration can support your move into AI-driven payments in 2026.