Visa’s entire business model is betting on human behavior. It’s about human consumption and psychology. The reward points you accumulate, the fraud protection you rely on, the Centurion card you dream of, and the zero-liability policy that gives you peace of mind when swiping your card at foreign ATMs—all of this exists not because money transfer is difficult, but because humans are anxious, seek status, and are not good at reading terms and conditions. Visa has leveraged this cognitive difference to build a $500.00B company.
However, AI agents do not possess these traits. They don’t accumulate points, don’t seek fraud protection, and don’t aspire to own a black card. They have only one instruction: complete the task. And when the task involves payment, the agent performs complex calculations that humans would never bother to calculate: the cheapest path, the fastest settlement, the lowest fees. Every time, automated, without any emotion.
Last month, an article on SubStack titled “Global Intelligence Crisis in 2028” caused Visa’s stock price to plummet 4.00%, Mastercard to fall 6.00%, and American Express to fall 12.00% in a single day of trading. The report was labeled as a “scenario analysis” rather than a “prediction.” But the market didn’t buy it. The technical arguments were also irrelevant. The problem is that by 2027, agents will bypass transaction centers and instead use stablecoins for settlement. Visa has spent fifty years perfecting its product, and now its customer base is being replaced. In machine-to-machine commerce, a 2-3% interchange fee is clearly a target. This is the core argument of Citrini Research.
This does not mean that artificial intelligence will destroy Visa tomorrow. Rather, the fee structure on which Visa has built its business empire is essentially a tax on human irrationality, while the traders themselves are completely rational. This is what Visa is all about.
What is Visa selling? To understand why this is important, you must understand what the interchange fee is actually used for. When you use a credit card to shop, the merchant pays a 2-3% fee to the credit card network and your issuing bank. This fee is used to pay for your points rewards, fraud protection, shopping insurance, and dispute resolution services. The entire consumer value proposition of credit cards is borne by the merchant, who ultimately passes the cost on to consumers by slightly increasing the price of goods. This is a perfect and stable system that has been running for fifty years, because consumers in the transaction are willing to bear all these costs, except that they do not pay directly.
AI agents don’t need these. It will not object to the fee, nor will it request a refund. The rationale for charging this fee is that it protects against human error, fraud, and impulsive behavior. If there are no humans involved in the transaction, this fee is completely meaningless.
American Express is the most typical example of this problem. Its customers are high-income, high-spending, and aspirational high-end cardholders. Its annual fee is higher than Visa or Mastercard, precisely because its customers are willing to pay for identity and privilege. The premise of this model is that purchasing behavior is human-driven, and customers choose American Express over Visa because access to VIP lounges is worth the money. Agents will not actively choose American Express; they will only look for the cheapest solution to complete the transaction. In a world where software controls credit cards, high-end membership levels do not exist.
An agent-led commercial routing model that bypasses interchange fees poses a greater risk to credit card banks and single-business issuers that rely heavily on 2-3% transaction fee revenue and build their entire business segment around merchant-subsidized reward programs. Visa and Mastercard have network businesses that can adapt. But those issuers who build their entire profit and loss model around interchange fees and reward programs have nowhere to retreat.
The week everyone shipped at once: The Citrini report and the infrastructure project launch happened to be released within the same three weeks. Tempo officially launched on the mainnet last Wednesday. The payment blockchain jointly developed by Stripe and Paradigm, designed for high-volume stablecoin settlement, was launched in sync with the Machine Payment Protocol (MPP). MPP is an open standard that allows AI agents to autonomously pay for services without manual approval. The protocol introduces a session mechanism. The agent only needs to authorize a spending limit once, and then it can continue to make micro-payments when consuming services such as data, computing, or API calls. Funds are paid using OAuth authentication. The user authorizes a budget, and the agent can spend it. The entire process does not require using a bank card at every step.
Anthropic, DoorDash, Mastercard, Nubank, OpenAI, Ramp, Revolut, Shopify, Standard Chartered Bank, and Visa are all listed as design partners for Tempo. The entire payment and e-commerce ecosystem recognizes this structural change. On the same day that Tempo went live, Visa’s cryptocurrency division launched a command-line interface tool for AI agents to make payments through terminals without API keys, accounts, or manual authorization. Visa calls it “command-line commerce”—machines can transact without human intervention. Mastercard agreed to acquire stablecoin infrastructure startup BVNK for $1.80B. Circle launched Nanopayments on the testnet, a sub-cent and gas-free USDC transaction designed for agents to use pay-per-use APIs without accounts or credentials. Sam Altman’s World project launched AgentKit, which allows agents to carry cryptographic proofs to prove that they represent real people. The toolkit is directly integrated into Coinbase’s payment system, enabling the platform to verify agent identities without hindering legitimate transactions.
In my opinion, what happened last week was that companies were racing to become the new Visa, lest Visa realize what it had lost.
The obvious paradox: Now nothing is said clearly enough, that is, Visa is not stagnant. It participated in the development of Tempo’s Machine Payment Protocol (MAPPS), launched Visa Crypto Lab, and its cryptocurrency head also wrote an article in Fortune explaining how agents can use bank cards to pay through new standards. Mastercard is investing $1.80B in stablecoin infrastructure. Stripe acquired Bridge and Privy. Existing companies are aware of this shift and are preparing for the full arrival of the new infrastructure. Visa’s argument is that it can extend its track to agent-driven commerce before agent-driven commerce builds a track that makes Visa irrelevant. This statement is not entirely wrong. Stripe processed $1.90T in total payments in 2025, a year-on-year increase of 34.00%. These companies are not shrinking. The network distribution advantages of card organizations are difficult to replicate.
I admit that I am not very willing to say this publicly, because historically, once someone puts forward this argument, a new product will be released to make them look stupid. So, the loophole in this argument is here: Visa’s distribution advantage is based on its relationship with merchants and consumer trust. Merchants accept Visa because consumers hold Visa; consumers hold Visa because merchants accept Visa. The operation of the entire cycle depends on people. Once agents become the main buyers in an important business field, this flywheel will slow down. Agents have neither brand loyalty nor wallets. All they have are budgets and instructions. Whichever route is the cheapest and fastest will win their business, and the switching cost is zero.
I want to accurately state where we are, because the current development speed of public opinion has exceeded the data itself. Although the ecosystem around x402 is valued at approximately $7.00B, on-chain data shows that the protocol’s daily transaction volume last week was only about $28000.00, most of which came from testing rather than actual transactions. This number is vastly different from Visa’s daily transaction volume. The transaction volume of x402 has exceeded 50.00M. Although the amount of a single transaction is small, the number of transactions indicates that the infrastructure is being used. Developers are developing based on this. Merchant-side services that accept agent payments are also growing. This is how payment networks start.
McKinsey estimates that by 2030, AI agents may facilitate $3.00T to $5.00T in global consumer transactions. This estimate may be correct or too optimistic. But what is undeniable is that the agent-driven business model has not yet been widely adopted. Merchants building native agent services, companies using agents as primary buyers, and transaction volumes that can truly test the economics of transactions are still developing. The reason why Citrini’s report caused market panic is that it simulated a series of credible events. Mastercard’s Q1 2027 financial report will not attribute the slowdown in transaction volume to “agent-led price optimization.” At least not for now. The first to be affected will be micro-payments for AI infrastructure, not consumer commerce. Agents completing research tasks will call hundreds of specialized data APIs per session. Each call costs only a fraction of a cent. After a week, these calls may bring $40.00 in revenue to the developers operating the service. Credit card networks cannot cope with this situation. The economics of minimum transaction amounts do not work. The merchant onboarding process does not work. The fee structure does not work. This type of business model is destined to be unable to operate within Visa’s framework. It needs a completely new model, and x402, Nanopayments, and Tempo are building this model.
As the model built by Citrini shows, the disruption to consumer commerce, even if it happens, will only come later. It requires agents to handle a considerable portion of discretionary spending, which in turn requires consumers to trust agents and hand over the purchasing decisions they currently make themselves to agents. Visa has been hit by higher-quality customers. These customers no longer need the elements that Visa relies on to succeed. The 2-3% interchange fee is not a transaction tax, but a tax on human irrationality. And agents are completely rational. How do I know this is important? Because Visa spent $1.80B last week to ensure that it is not excluded from the answer.
[Block unicorn]
AI Agents and the Disruption of Traditional Payments: A Crypto Market Analysis
The recent developments surrounding AI agent payment infrastructure represent a paradigm shift that could fundamentally alter the $500B payment industry. The thesis—that AI agents will bypass traditional payment networks by eliminating the human psychology that justifies interchange fees—is not merely theoretical but is now being actively built by major players across the financial ecosystem.
Market Fundamentals: The Irrationality Tax
Visa’s business model is predicated on what could be termed an “irrationality tax”—the 2-3% interchange fee that merchants pay to cover rewards, fraud protection, and other human-centric services. This fee structure has remained stable for decades because consumers are willing to accept slightly higher prices in exchange for convenience and psychological benefits.
AI agents, however, represent the ultimate rational economic actors. They don’t accumulate points, don’t seek status symbols, and won’t pay for features they don’t need. This creates a fundamental mismatch between traditional payment networks and machine-to-machine commerce. The very justification for Visa’s business model—human psychology—becomes irrelevant in an AI-driven economy.
Current State and Market Reaction
The market’s reaction to the “Global Intelligence Crisis in 2028” report—with Visa down 4%, Mastercard 6%, and American Express 12%—demonstrates that investors are beginning to price in this disruption. However, current on-chain data shows that while infrastructure is being built, actual transaction volumes remain minimal. The x402 protocol, for example, processed only $28,000 in daily transactions last week—dwarfed by Visa’s 50 million daily transactions.
This suggests we’re in the early innings of this transition. The infrastructure is being built, but mass adoption and meaningful transaction volumes are likely still years away.
Infrastructure Developments: The Race to Become the New Visa
The convergence of multiple developments within a compressed timeframe is significant:
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Tempo’s Mainnet Launch: The Stripe/Paradigm-backed blockchain for high-volume stablecoin settlement, paired with the Machine Payment Protocol (MPP), provides a concrete solution for AI agent payments.
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Major Ecosystem Participation: The list of design partners for Tempo reads like a who’s who of modern finance—Visa, Mastercard, OpenAI, Stripe, Shopify, Standard Chartered. This indicates the entire payment ecosystem recognizes this structural shift.
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Strategic Acquisitions and Investments: Mastercard’s $1.8B acquisition of BVNK, Visa’s crypto CLI tool, and Circle’s Nanopayments testnet demonstrate that legacy players are not standing still.
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Identity Solutions: Sam Altman’s World project launching AgentKit for cryptographic identity verification addresses a critical component of AI commerce.
What’s remarkable is that these developments are not happening in isolation but represent coordinated efforts across the ecosystem. The question is whether traditional payment networks can successfully extend their existing advantages into the AI economy, or whether entirely new infrastructure will emerge to replace them.
Investment Implications and Opportunities
For crypto investors, this represents a multi-year narrative with several distinct investment angles:
1. Stablecoin Infrastructure
The transition to AI agent payments will heavily favor stablecoins for their price stability. Projects like USDC (Circle) that are actively developing nanopayment solutions have a first-mover advantage. The ability to process sub-cent transactions without gas fees will be critical for AI infrastructure micro-payments.
2. AI Agent Payment Protocols
Protocols like Tempo and x402 that position themselves as the backbone of machine-to-machine commerce could see significant growth. The key differentiators will be:
– Transaction speed and cost
– Developer experience and tooling
– Network effects among AI agents and merchants
3. Cross-Chain Solutions
As AI agents interact with multiple services across different blockchains, solutions that enable seamless cross-chain payments will capture value. This includes bridging infrastructure and interoperability protocols.
4. Identity Verification
Verifying that AI agents represent legitimate users or entities is a critical component of this ecosystem. Projects that can provide secure, privacy-preserving identity solutions for AI agents will have significant value.
5. Merchant Onboarding Infrastructure
Tools that make it easy for merchants to accept AI agent payments—similar to how Stripe simplified payment acceptance for traditional commerce—will be essential.
Risks and Challenges
1. Timeline Uncertainty
While the thesis is compelling, the timeline for widespread adoption remains uncertain. McKinsey’s estimate of $3-5 trillion in AI-facilitated transactions by 2030 may be overly optimistic. Investors should position for a longer time horizon than current market sentiment suggests.
2. Regulatory Headwinds
Payment systems face significant regulatory scrutiny globally. As AI agent payments gain traction, regulators will likely impose new requirements that could slow adoption.
3. Network Effects
Visa’s massive network effect—acceptance at 80 million merchants globally and 3.6 billion cards—creates a formidable barrier to entry. Disrupting this requires a compelling value proposition that overcomes significant switching costs.
4. Scalability Issues
Current blockchain solutions may struggle to handle the volume of transactions that traditional payment networks process daily. Solving the trilemma of decentralization, security, and scalability remains a challenge.
5. Adoption Barriers
Merants may be reluctant to accept payments from AI agents without clear benefits, while consumers may be hesitant to cede purchasing decisions to AI systems. Building trust will take time.
Strategic Outlook: The Battle for the AI Payment Layer
The most likely outcome is not the immediate destruction of Visa but rather a gradual erosion of its market share in specific segments. The initial impact will be in AI infrastructure micro-payments—where the economics of traditional interchange fees don’t work—before expanding to larger transactions.
For crypto investors, the key is identifying protocols that can capture value from this shift without relying on displacing Visa overnight. The most successful projects will be those that:
1. Solve immediate pain points for AI developers and merchants
2. Generate revenue in the near term
3. Build network effects that become increasingly valuable over time
4. Maintain flexibility as the technology and use cases evolve
The fact that Visa is actively participating in building this infrastructure (through Tempo and its crypto CLI tool) suggests that traditional players recognize the threat and are attempting to adapt. However, their ability to successfully transition remains an open question.
Conclusion: A Multi-Year Narrative
The disruption of traditional payment networks by AI agents represents a multi-year narrative that will play out gradually. While the market may be pricing in this transition more quickly than the actual timeline warrants, the underlying infrastructure developments are real and accelerating.
For crypto investors, the opportunity lies in identifying protocols that can provide the critical infrastructure for AI agent commerce—particularly in stablecoin settlements, micropayments, and identity verification. The most successful projects will be those that can build network effects among AI agents while solving real problems for merchants and developers.
As this ecosystem develops, we’ll likely see a bifurcation between consumer commerce (where traditional networks may maintain dominance longer) and machine-to-machine transactions (where crypto-based infrastructure could capture significant market share). Investors should position accordingly.