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Visa and Inflow Launch Payment System for AI Agents

Inflow has introduced agent-native commerce infrastructure using Visa Intelligent Commerce. The system provides AI agents with secure payment credentials and a policy engine to govern transactions. Visa reported that 71% of businesses are willing to optimize for AI agents as buyers.

Forbes
1 source·May 8, 4:04 AM(1 day ago)·2m read
Visa and Inflow Launch Payment System for AI Agentsnewsbtc.com
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Inflow, a San Francisco-based company, launched agent-native commerce infrastructure this week built on Visa Intelligent Commerce. The platform combines secure payment credentials with a policy engine that determines what an AI agent is allowed to purchase and how much it can spend.

This addresses a gap in the agentic economy where agents increasingly perform tasks but previously lacked reliable ways to complete payments. AI agents are used for research, email management, calendar scheduling and other functions. Until now, authorizing agents to make purchases has required direct human intervention for each transaction.

The new system gives agents a wallet with built-in rules set by the human owner or business. Inflow describes its platform as business-to-AI infrastructure. It handles identity verification, onboarding, multi-currency wallets and a policy-governed payments engine.

Visa Intelligent Commerce supplies the payment credentials, tokenization, authentication and access to merchants on its global network. "AI agents are a new buyer category, and businesses need a trusted way to support them," a Visa spokesperson said in a statement.

Separately, 77% are already using or piloting AI in their operations. The report indicates many companies are preparing to transact with AI agents that until recently could not complete payments independently. The infrastructure is currently focused on B2B applications.

It targets cloud services including compute, inference, data storage and other resources that agents consume during operation. One example cited in the report involved agents spending on tokens for these services, with all transactions previously requiring manual human authorization.

Existing payment systems combine decision-making and execution in a single human action. Removing the human from the process also removes the policy framework that governs spending. InFlow’s policy engine aims to fill that gap by embedding rules directly into the payment infrastructure.

This approach differs from standard digital wallets that rely on credential access without built-in spending limits or merchant restrictions. The company stated that policies and protections are essential for agentic commerce to function at scale. Major payment processors are expected to develop similar capabilities, though the structural separation of policy and payment has historically been bridged only by human oversight.

Key Facts

Inflow launch
agent-native commerce on Visa network
71% of businesses
willing to optimize for AI agents
77% of businesses
using or piloting AI operations
Policy engine
governs agent spending limits
B2B focus
cloud infrastructure payments

Story Timeline

3 events
  1. Late last year

    Inflow launched to enable agentic payments.

    1 sourceForbes
  2. This week

    Inflow launched agent-native commerce infrastructure with Visa Intelligent Commerce.

    1 sourceForbes
  3. 2026

    Visa released its Business-to-AI report showing business readiness for AI agents.

    1 sourceForbes

Potential Impact

  1. 01

    Businesses may begin accepting payments directly from AI agents using Visa credentials.

  2. 02

    Companies providing cloud services to AI agents could see reduced friction in automated billing.

  3. 03

    AI agent adoption in business operations could accelerate with built-in spending controls.

  4. 04

    Payment processors may add policy layers to existing infrastructure to support agent transactions.

Transparency Panel

Sources cross-referenced1
Confidence score75%
Synthesized bySubstrate AI
Word count350 words
PublishedMay 8, 2026, 4:04 AM
Bias signals removed4 across 2 outlets
Signal Breakdown
Speculative 1Amplifying 1Editorializing 1Framing 1

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