The stablecoin market is currently valued at over $140 billion, but could see substantial growth as new use cases emerge. When combined with artificial intelligence (AI)—another billion-dollar market—stablecoins could quickly rise in demand.
This will likely be the case, as a recent trend the Web3 sector is witnessing is the combination of stablecoins and AI-agents. Rebecca Liao, CEO of Layer-1 network Saga, told Cryptonews that autonomous payments and transactions are perhaps the most direct and widespread use case.
“AI agents are being designed to make payments, settle transactions, and manage funds on behalf of users or even autonomously,” Liao said. “A recent example of this is Mastercard’s Agent Pay and Visa’s Intelligent Commerce platform, allowing verified AI-agents to make tokenized payments.”
Stablecoins: The Missing Link For AI-Agents
Given the increasing use of stablecoins by AI-agents, it’s important to understand why these tokens matter.
Illia Otychenko, lead analyst at CEX.IO, believes that stablecoins are a missing link for AI-agents. He noted that stablecoins are capable of addressing several issues that AI-agents may face when performing financial transactions without human support.
“Stablecoins typically operate in networks that don’t rely on user expectations or behavior to confirm transactions,” Otychenko said. “Furthermore, bots already play a key role in this space. In 2024, bots accounted for 70% of all stablecoin transfer volume, and this trend has continued into 2025. These networks and infrastructures are already designed with machines in mind.”
Otychenko explained that traditional payment rails are human-centric, where a human user exists at one or both ends of a transaction. However, he pointed out that AI-driven transactions don’t resemble this process.
Echoing this, Jesse Shrader—co-founder of Bitcoin payment platform Amboss—told Cryptonews that AI agents require a digital form of value to transact, and traditional payment systems simply don’t work in these instances.
“Traditional payments like wires, ACH, and card payments don’t scale for micropayments and take too long to settle. Stablecoin payments are better positioned to have rapid settlement, which work within the timeframes of AI queries,” Shrader said.
Otychenko added that the combination of stablecoins and AI-agents has the most potential for use cases like micropayments, subscriptions, and investment activities such as arbitrage, liquidity provision, or portfolio rebalancing.
“These transactions are fee and value sensitive, making predictability paramount,” he said. “Moreover, using altcoins instead of stablecoins would require hedging against price volatility, introducing an inefficient and unnecessary layer.”
How Stablecoins Allow AI-Agents To Transact
Although this is still an emerging concept, a few use cases are being applied today.
Erik Reppel, head of engineering at Coinbase Developer Platform (CDP), told Cryptonews that stablecoins allow AI-agents the ability to transact instantly, globally, and autonomously—without human intervention.
For example, Reppel explained that CDP recently introduced “x402.” This is an open standard that leverages the original HTTP “402 Payment Required” status code. The x402 standard from CDP embeds stablecoin payments directly into web integrations.
“Tools like x402 enable agents to pay for data, APIs, and services,” Reppel said. “And because stablecoins are programmable, they come with powerful built-in security primitives—like signed intents and scoped approvals – that will be critical as agents scale their autonomy and capabilities.”
While x402 only recently went live, Reppel explained that the standard is already being leveraged. For instance, he shared that Amazon Web Services (AWS) is exploring how x402 could be used for paid compute.
This could be a game changer, as statistics show the global Cloud Computing Market is expected to reach $1902.66 billion by 2030. This growth is being driven by the increasing adoption of advanced technologies like AI and machine learning (ML).
Reppel added that the decentralized compute and AI-as-a-Service platform Heurist is using x402 to pay for deep research. Web3 file storage platform Pinata is also using x402 to pay per file stored.
“We’ve seen solo developers build everything from monetized music playlists to research bots that pay per article. It’s still early, but the momentum is real—x402 is unlocking a whole new class of apps and agents that can pay as they go,” Reppel said.
AI-Agents Integrate Stablecoins With The Lightning Network
Shrader pointed out that the next wave of AI-agents may also see an integration with stablecoins on the Bitcoin Lightning Network.
“Tether’s recent announcement of issuing USDT on the Lightning Network signals a shift away from crypto’s everything-on-the-blockchain mindset to unbounded scalability through Lightning’s off-chain scaling,” he stated.
Shrader added that the Lightning Network already maintains the “L402 protocol,” which provides a universal HTTP-based payment flow. According to the L402 protocol document, this combines the strengths of Macaroons for better authentication with the strengths of the Lightning Network for better payments. Macaroons are described as “bearer authentication tokens.”
Shrader shared that Amboss, along with a handful of other companies, are already combining the Lightning Network and AI in anticipation of stablecoin issuance on the Lightning Network.
A Financial Institution Powered Entirely By AI
In addition to HTTP payment flows, Circle co-founder and Catena Labs CEO Sean Neville recently launched a project that seeks to create a financial institution powered entirely by AI.
Neville said in a news release that AI agents will soon conduct most economic transactions. Catena Labs will therefore use its recent $18 million led by a16z crypto to develop the “first fully regulated AI-native financial institution (FI).”
Catena Labs further remarked that while AI-agents can use traditional systems and financial rails, stablecoins should be viewed as “AI-native money.” The company mentioned that regulated stablecoins like USDC allow near-instant, low-cost, global transactions, which are essential for agents.
Challenges To Consider
While there is huge potential behind stablecoins and AI-agents, a number of challenges remain.
Reppel believes that the biggest challenge with agentic payments is making sure agents act accordingly. He thinks that stablecoins can help ensure this.
“Stablecoins are natively programmable, which makes it easy to add guardrails like spend limits or keeping a human in the loop,” he said.
Yet Reppel commented that the tradeoff for this type of programmability is that it introduces a wallet, which can be tricky to implement or secure properly.
Liao further told Cryptonews that fragmentation, regulatory uncertainty, and on-and-off ramp limitations are problematic. Liao explained that Saga is addressing these challenges in different ways.
For example, she elaborated that Saga has a “chainlet infrastructure” tool that provides infinite horizontal scalability and dedicated blockspace for applications. “This is crucial for AI agents, as it means they won’t be bogged down by network congestion or unpredictable gas fees, allowing them to execute high-frequency transactions with stablecoins reliably,” she said.
Additionally, Saga has built a “Liquidity Integration Layer” designed to create a unified liquidity environment across different blockchain ecosystems. This is meant to facilitate seamless and automated asset movement.
“For AI agents, this means they can more easily access and utilize stablecoins from various sources and move them where needed without complex bridging,” Liao said.
Challenges aside, stablecoin and AI-agent use cases are expected to thrive. Reppel commented that on-chain tools that handle key management can make it easier for developers to build safe and reliable agentic systems.
“In short, these challenges are being solved with tools that bridge AI and Web3, making them more accessible, intuitive, and developer-friendly,” Reppel said.
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