Mastercard Just Built A Payment Network For AI Agents — And It Runs On Crypto

bitcoinistPublished on 2026-06-10Last updated on 2026-06-10

Abstract

Mastercard has launched "Agent Pay for AI," a new payment protocol enabling AI agents to conduct small, automated, machine-to-machine transactions. The system addresses a gap in traditional payment infrastructure, which is poorly suited for such micropayments. A key feature is the storage of human-granted permissions on the Polygon blockchain, allowing for decentralized verification without a central authority. Mastercard is developing the protocol with partners Adyen, Coinbase, and Cloudflare. It enters a competitive field where Visa, Stripe, and Google have also introduced similar AI payment tools. While Mastercard's Chief Product Officer, Jorn Lambert, does not expect significant near-term revenue, he views it as a strategic infrastructure investment for an anticipated future where AI agents facilitate a meaningful share of commerce. This move follows Mastercard's recent integration of stablecoins, signaling a broader shift towards incorporating crypto into its core systems.

Mastercard has launched Agent Pay for AI, a new protocol designed to enable artificial intelligence agents to pay each other and send micropayments — storing the permissions that humans grant their AI agents on Polygon, a blockchain network built on top of Ethereum, according to an exclusive report by Fortune published June 10.

Related Reading: Trump’s Crypto Deals May Have Increased The Family Fortune By $2 Billion—At Investors’ Expense

The protocol is built around a specific use case that existing payment infrastructure handles poorly: small, automated, machine-to-machine transactions. When an AI agent needs to access data piecemeal from a website, or pay another service incrementally for a task it is performing on a user’s behalf, traditional card rails — built for human-initiated, merchant-facing transactions — are poorly suited for the job. Agent Pay for AI is designed to fill that gap, per Fortune’s reporting.

The decision to log permissions onto a public blockchain rather than a private database is a deliberate architectural choice. Multiple parties that want to verify whether an agent is acting within the boundaries a human has authorized can access that information directly on-chain, without relying on a single centralized authority to confirm it, per Fortune. Mastercard selected Polygon for the initial deployment.

ETH's price trends to the downside on the daily chart. Source: ETHUSD on Tradingview

The Partners And The Crypto Competition

Three companies are working with Mastercard to develop the protocol: fintech platform Adyen, crypto exchange Coinbase, and web infrastructure giant Cloudflare, per Fortune’s reporting. The combination of a payment processor, a crypto-native exchange, and the company that handles a significant share of the internet’s traffic signals that Mastercard is building Agent Pay for AI as interoperable infrastructure rather than a proprietary walled garden.

The competitive landscape is already crowded. Visa and Stripe have each built tools anticipating a world where AI bots buy groceries, manage bank accounts, and pay for subscriptions. Coinbase launched the x402 protocol for AI payments, Stripe collaborated with Tempo to develop the Machine Payments Protocol, and Google released its own standard in September 2025, per Fortune.

Jorn Lambert, Mastercard’s Chief Product Officer, was measured about near-term commercial expectations in his conversation with Fortune. He does not expect Agent Pay for AI to be a significant revenue driver in the next twelve months. Over five years, however, he described it as a meaningful new addressable market. Lambert separately predicted that AI chatbots will eventually sit between a meaningful share of e-commerce transactions — framing the protocol not as a speculative bet but as infrastructure being built ahead of an inevitable shift in how commerce flows.

Related Reading: Japan’s SBI Bank Expands Crypto Push With BTC, ETH, XRP Rewards Program For Depositors

This development marks a pivotal moment for the nascent sector’s convergence with artificial intelligence. Mastercard choosing a public blockchain to anchor the permissions layer of its AI payment infrastructure — one week after opening its global settlement rails to six regulated stablecoins across eight blockchain networks — confirms that the world’s second-largest card network is systematically rebuilding its core architecture around crypto rails rather than alongside them.

Cover image from Grok, ETHUSD chart from Tradingview

Related Questions

QWhat is the name of the new protocol launched by Mastercard for AI agents, and what problem does it aim to solve?

AMastercard launched the Agent Pay for AI protocol. It aims to solve the problem of enabling small, automated, machine-to-machine (AI agent-to-agent) payments and micropayments, a use case poorly handled by traditional card payment infrastructure designed for human-initiated, merchant-facing transactions.

QOn which blockchain network is Mastercard storing the permissions for its Agent Pay for AI protocol, and why was a public blockchain chosen?

AMastercard is storing the permissions for its Agent Pay for AI protocol on the Polygon blockchain. A public blockchain was chosen so that multiple parties can directly verify on-chain whether an agent is acting within authorized boundaries, without relying on a single centralized authority.

QWhich three companies are partnering with Mastercard to develop the Agent Pay for AI protocol?

AThe three companies partnering with Mastercard are the fintech platform Adyen, the crypto exchange Coinbase, and the web infrastructure giant Cloudflare.

QAccording to Mastercard's Chief Product Officer Jorn Lambert, what is the commercial outlook for the Agent Pay for AI protocol in the near term and over a longer period?

AAccording to Jorn Lambert, Agent Pay for AI is not expected to be a significant revenue driver in the next twelve months. However, over a five-year horizon, he described it as a meaningful new addressable market.

QHow does Mastercard's recent launch of Agent Pay for AI, combined with another recent action, indicate its strategic direction regarding cryptocurrency infrastructure?

ACombined with its decision the week prior to open its global settlement rails to regulated stablecoins, the launch of Agent Pay for AI on a public blockchain confirms that Mastercard is systematically rebuilding its core architecture around crypto rails, rather than just operating alongside them.

Related Reads

Solana Real-World Assets Gain Momentum With Significant Spike In Transfer Activity

Solana's price has declined recently, breaking key support levels. However, the network's activity, especially in the Real-World Assets (RWA) sector, shows strong momentum. The ecosystem recorded its largest daily transfer volume ever, surpassing $1.49 billion—a more than 2x increase, led significantly by preSPAX. This signals growing adoption of tokenized assets on Solana. Analyst Zensei highlights Solana as the leading platform for spot trading, noting the SOL/USDC pair's 24-hour volume of over $4.9 billion far exceeds other major markets. Another analyst, Crypto Patel, points out that SOL is trading within a key Fibonacci Retracement Zone, similar to a past pattern that preceded a major rally. While an "Altcoin Season" is seen as necessary for a potential push toward $1,000, the current accumulation zone is between $40 and $60.

bitcoinist52m ago

Solana Real-World Assets Gain Momentum With Significant Spike In Transfer Activity

bitcoinist52m ago

AI Investors' 2026 Anxiety: When Models Devour Everything, What Moat Is Left for Startups?

In 2026, a wave of investor anxiety questions the defensibility of AI startups as models improve, fearing that most companies are just "thin wrappers" destined to be absorbed by foundation models or chipmakers. The author argues against this despair, positing that true moats lie not in benchmark performance but in areas models cannot easily reach. The logic of despair is that if models excel at all measurable tasks, only compute and cutting-edge model weights hold lasting value. However, the essay contends that the most valuable work is inherently "untrainable." Benchmarks measure what can be measured and thus optimized for, but real-world correctness often resides in private, complex systems. Examples include legacy codebases, intricate legal transactions, or hospital workflows. This kind of correctness is proprietary, costly to establish, and cannot be validated quickly—it requires time and trust within an organization. As models commodify visible, measurable tasks from both above (labs absorbing scaffolding) and below (saturation by cheaper models), value shifts to "untrainable ground." This encompasses work where correctness is a private truth, locked behind integration barriers, licenses, liability frameworks, and entrenched user habits. Trust and adoption are slow, human-centric processes that smarter models cannot accelerate. Successful companies defend their position by embedding deeply into client operations, owning the definition of "good" within a specific domain (e.g., Harvey in law, OpenEvidence in medicine), and pricing on outcomes rather than tokens. While labs compete fiercely, they are incentivized to keep the application layer vibrant. The future belongs not to those competing on generic benchmarks but to those navigating unscoreable terrain, doing the "unsexy work" of translation between models and messy human realities. The most cited benchmark scores are thus maps of territory about to become worthless, signaling who will lose the right to define what counts as good.

marsbit1h ago

AI Investors' 2026 Anxiety: When Models Devour Everything, What Moat Is Left for Startups?

marsbit1h ago

Three-Year High Smashes Rate-Cut Hopes, Who's Using CPI to Clean Out Whale Holdings?

U.S. CPI inflation accelerated to 4.2% year-over-year in May, reaching a three-year high and dampening market expectations for Federal Reserve rate cuts in 2026. The surge was primarily driven by a sharp 23.5% annual increase in energy prices, fueled by geopolitical conflicts. While core CPI rose 2.9% year-over-year, showing relative moderation, the hotter-than-expected headline data prompted a repricing in interest rate markets. Traders now overwhelmingly expect the Fed to hold rates steady, with some even pricing in potential rate hikes for late 2026 or 2027. The report triggered declines in major U.S. stock indices and pressured risk assets like Bitcoin, which remained volatile around $61,000-$62,000. Analysts note that while the energy-driven inflation spike is concerning, the controlled core figures provide the Fed room for patience. However, the "higher for longer" interest rate narrative has solidified. For crypto markets, this translates to continued outflows from Bitcoin ETFs, heightened volatility, and a market seemingly in a "capitulation" phase, with leverage reset but sustained demand yet to materialize.

Foresight News1h ago

Three-Year High Smashes Rate-Cut Hopes, Who's Using CPI to Clean Out Whale Holdings?

Foresight News1h ago

The Ethereum Indicator That Never Missed A Bottom Is Signaling Again, This Time At $700

Ethereum (ETH) is trading around $1,606, down 70% from its all-time high. Analyst Ali Martinez points to the Delta Price indicator, which has historically signaled market bottoms and is now at $708. This suggests ETH could face another 56% drop from current levels to approximately $700 before a sustained recovery. Martinez identifies key support levels at $1,560 and $1,070. For a bullish reversal, ETH needs to reclaim the 200-week SMA near $2,500 and then the 50-week SMA near $3,100, conditions not currently met as selling pressure persists.

bitcoinist1h ago

The Ethereum Indicator That Never Missed A Bottom Is Signaling Again, This Time At $700

bitcoinist1h ago

Trump's Crypto Empire: A $2.3 Billion Wealth Transfer Experiment

In June 2026, Reuters investigations revealed that since Donald Trump's return to the White House, his family has accumulated roughly $2.3 billion in profits from four core crypto ventures: World Liberty Financial (WLFI), the $TRUMP meme coin, American Bitcoin, and ALT5 Sigma (later renamed AI Financial). Coincidentally, overall investor losses in these projects were estimated to be a similar amount. The businesses, spanning DeFi, stablecoins, meme coins, Bitcoin mining, and digital payments, largely relied not on technological innovation but on converting the political influence and notoriety of the Trump brand into financial assets sold to the market. This marks a dramatic shift from Trump's earlier skepticism of cryptocurrencies. The ventures operated on a similar logic: leveraging the Trump name to generate market hype and trust, attracting investment through token sales or public listings, and enabling the family to capture profits upfront through equity, token allocations, and fees, while later entrants often bore the brunt of the risk as markets cooled. WLFI, the most profitable venture, generated an estimated $1.6 billion for the family, primarily through sales of its locked, illiquid governance token and its USD1 stablecoin. The $TRUMP meme coin, a direct monetization of the presidential IP, brought in over $600 million for Trump-linked entities before its price crashed nearly 97% from its peak. American Bitcoin gained a "Trump stock" premium for its mining operations, and ALT5 Sigma/AI Financial combined Trump, AI, and crypto themes for a temporary valuation surge. The episode underscores how political influence can be packaged into financial assets, creating substantial wealth for promoters while highlighting the risks for investors who base decisions on hype and brand allegiance over fundamental business models and cash flows.

marsbit1h ago

Trump's Crypto Empire: A $2.3 Billion Wealth Transfer Experiment

marsbit1h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片

Top Questions