A framework for understanding the success of the internet is to view it from the perspective of coordination. Fundamentally, we can attribute the success of the most valuable internet applications to their ability to coordinate human intentions more finely. Amazon coordinates commercial intentions; Facebook, Instagram, and Twitter coordinate social intentions; Uber and Doordash coordinate ride-hailing and delivery intentions, while Google coordinates the intention to search for information by matching queries with relevant online content.

An obvious trend is that AI agents represent the next logical evolution of large-scale coordination. While today, our “intentions” are achieved through searching, downloading, and interacting with applications on the internet, it is reasonable to assume that shortly, our “intentions” will be executed by a network of AI agents working on our behalf.

Importantly, this shift to an agent-coordinated economy raises a fundamental question: what kind of infrastructure will ultimately support this evolution?

In this article, we will (1) explore the bull and bear cases for AI agents transacting via cryptocurrency; (2) outline the logical path of AI agent adoption; and (3) investigate value capture in this emerging agent economy.

The Role of Cryptocurrency

There has been much speculation about why blockchain could become the economic foundation for the agent economy. However, as with most emerging crypto verticals, the bull case has been reduced to an oversimplified, popular narrative. Today, a common argument posits that “agents cannot own bank accounts, so they will switch to crypto wallets,” which seems to overlook the fundamental value proposition of cryptocurrency. Access is not the issue; agents can fully own bank accounts under FBO (For Benefit Of) account structures. For example, companies like PayPal already manage millions of sub-accounts under a single FBO structure. They could manage AI agents in the same way: each agent has its virtual sub-account, tracked by the platform but pooled at the banking level. Notably, Stripe recently announced they will add support for agent transactions under a similar structure.

https://twitter.com/jeff_weinstein/status/1857161398943642029

Additionally, the argument that “this undermines the autonomy of AI agents” is somewhat simplistic. Ultimately, someone will manage the private keys of AI agents, so they are not fully autonomous anyway. While theoretically, the private keys of AI agents could be stored in a Trusted Execution Environment (TEE), this is both operationally expensive and impractical. Moreover, even if agents were allowed 100% autonomy, it would not bring substantive freedom as they ultimately need to serve humans.

Instead, the real pain points driving agent transactions in traditional domains and blockchain are as follows:

• Settlement Time: Traditional payments face delays of several days and batch processing limitations, especially in cross-border transactions. The lack of instant settlement significantly hinders AI agents that need real-time responses to operate efficiently. Blockchain Solution: Public blockchains provide near-instant settlement finality through atomic transactions, enabling real-time agent-to-agent interactions without counterparty risk. These transactions settle 24/7, unrestricted by geography or banking hours.
• Global Accessibility: Traditional banking infrastructure creates significant barriers for global developers, with 70% of developers outside the U.S. facing challenges using payment channels. Blockchain Solution: Public blockchain infrastructure is inherently borderless and permissionless, allowing global agent deployment without traditional banking. Anyone with internet access can participate in the network, unrestricted by geography.
• Unit Economics: The fee structure of traditional payment systems (3%+ fixed fees) makes microtransactions economically infeasible, creating barriers for AI agents requiring frequent small-value transactions. Blockchain Solution: High-performance blockchains enable microtransactions at minimal cost, allowing agents to perform high-frequency, low-value transactions efficiently.
• Technical Accessibility: Traditional payment infrastructure lacks programmable APIs and requires strict PCI compliance. Systems designed for human interaction through web forms and manual inputs create significant barriers to automated agent operations. Blockchain Solution: Blockchain infrastructure offers native programmable access through standardized APIs and smart contracts, eliminating the need for forms or manual inputs. This facilitates reliable automated interactions without PCI compliance overheads.
• Multi-Agent Scalability: Traditional systems struggle to manage multiple AI agents requiring independent funds and accounts, leading to costly banking relationships and complex accounting requirements. Blockchain Solution: Blockchain addresses can be easily programmatically generated, enabling efficient fund segregation and multi-agent architectures. Smart contracts provide flexible, programmable fund management without the administrative costs of traditional banking.

Adoption Path

While the technical advantages of cryptocurrency are indeed compelling, they are not necessarily prerequisites for the wave of intermediary agent commerce. Despite the limitations of traditional payment methods, they benefit from massive network effects. Any new infrastructure must offer convincing advantages, not just marginal improvements, to drive adoption.

Looking ahead, we anticipate the adoption of agents to unfold in three distinct phases, with each phase bringing progressively higher levels of autonomy for agents:

Phase 1: Transactions Between Humans and Agents (Present)

We are currently in the first phase. The recently launched “Buy with Pro” feature by Perplexity provides a glimpse into how humans are beginning to transact with AI agents. Their system integrates AI bots with traditional credit cards and digital wallets like Apple Pay, enabling them to research products, compare options, and make purchases on behalf of users.

In theory, this process could use cryptocurrency, but there are no clear advantages at this stage. As Luke Saunders pointed out, the necessity of cryptocurrency boils down to the required autonomy level of agents. Currently, these agents lack sufficient autonomy. They do not independently manage resources, assume risks, or pay for other services; they simply act as research assistants who help before users make decisions. It is not until subsequent phases of agent adoption that the limitations of traditional channels become apparent.

Phase 2: Transactions Between Agents and Humans (Emerging)

The next phase involves agents autonomously initiating transactions with humans. This is already happening on a small scale: AI trading systems execute transactions, smart home systems purchase electricity at optimal prices via time-based pricing, and automated inventory management systems place replenishment orders based on demand forecasts.

Over time, more complex human-agent business scenarios may emerge, such as:

• Payments and Banking: Optimizing bill payments and cash flow, fraud detection, dispute handling, automated expense categorization, and maximizing interest while reducing fees through smart account management.

• Shopping and Consumer Needs: Price tracking and automatic purchases, subscription optimizations, refund claims, and smart home inventory management.

  Travel and Transportation: Flight price tracking and rebooking, smart parking management, rideshare optimization, and automated travel insurance claims.

• Household Management: Smart temperature controls, predictive maintenance schedules, and automated consumable replenishment based on usage patterns.

• Personal Finance: Automatic tax optimization, portfolio rebalancing, and bill negotiations with service providers.

As agents begin to manage resources and make decisions autonomously, the limitations of traditional methods will become more evident. Most of these transactions could still theoretically operate under frameworks like Stripe’s Agent SDK. However, this phase marks the start of a fundamental shift: real-time optimization by agents will drive a move from flat-rate monthly or yearly service fees to finely tuned usage-based pricing. In a world where agents grow increasingly autonomous, they will need to pay for resources like computing power, API query fees, LLM inference costs, transaction fees, and other usage-based services.

As the inefficiencies of card payment models become more apparent, cryptocurrency evolves from offering marginal improvements to providing a transformative advantage over traditional channels.

Phase 3: Agent-to-Agent Transactions (Future)

The final phase represents a shift in how value flows within the digital economy. Agents will transact directly with other agents, creating complex autonomous commercial networks. While similar efforts have emerged in speculative corners of the cryptocurrency market, more sophisticated use cases will surface, including:

• Resource Markets: Computing agents negotiate data placement with storage agents, energy agents trade grid capacity with consumption agents, bandwidth agents auction network capacity to content delivery agents, and cloud resource agents conduct real-time arbitrage across providers.
• Service Optimization: Database agents negotiate query optimization services with computing agents, security agents purchase threat intelligence from monitoring agents, caching agents exchange space with content prediction agents, and load-balancing agents coordinate with scaling agents.
• Content and Data: Content creation agents license assets from media management agents, training data agents negotiate with model optimization agents, knowledge graph agents trade verified information and analytics agents purchase raw data from collection agents.
• Business Operations: Supply chain agents coordinate with logistics agents, inventory agents negotiate with procurement agents, and customer service agents contract with specialist support agents.
• Financial Services: Risk assessment agents trade insurance with underwriting agents, financial agents optimize returns with investment agents, credit scoring agents sell verification to loan agents, and liquidity agents coordinate with market-making agents.

This phase requires fundamentally new infrastructure designed for machine-to-machine commerce. Traditional financial systems rely on manual identity verification and oversight, which inherently impede an agent-to-agent economy. In contrast, stablecoins—with their programmability, borderless nature, instant settlement, and microtransaction support—will become essential infrastructure.

Value Capture in the Agent Economy

The evolution toward an agent economy will inevitably create winners and losers. In this new paradigm, several layers of the technical stack emerge as key-value capture points:

• Interface Layer: Similar to competition for end-users in traditional payment environments, players will compete for the interface layer where users express their “agent intentions.” These front ends will evolve into comprehensive platforms integrating identity, authentication, and transaction functionalities. Key players include: Device manufacturers like Apple, with hardware security and identity integration capabilities. Consumer fintech super apps like PayPal and Block’s Cash App, leverage large user bases and closed-loop payment networks. AI-native interfaces like ChatGPT, Claude, Gemini, and Perplexity, extend their chatbots into agent transactions. Existing crypto wallets, leverage their native crypto infrastructure, though their advantage may be less significant.
• Identity Layer: A key challenge in the agent economy is distinguishing human from machine participants. In a world where agents disproportionately manage valuable resources and make autonomous decisions, this becomes increasingly critical. While Apple has an advantage here, Worldcoin is pioneering intriguing solutions with its Orb hardware and World ID protocol. By providing verifiable proof of personhood, Worldcoin could indirectly become a significant winner by offering developers a platform to ensure all users are human.
• Settlement Layer (Blockchain): If blockchain replaces traditional channels as the standard settlement layer for AI agents, the blockchains facilitating agent transactions will capture significant value.
• Stablecoin Issuance Layer: Considering liquidity network effects, it is reasonable to assume that stablecoins used by agents will capture value. USDC appears well-positioned, as Circle is launchinga developer-controlled wallet and stablecoin infrastructure to support agent transactions.

Ultimately, the biggest losers may be applications that fail to adapt quickly to the agent economy. In a world where agents (not humans) drive transactions, traditional moats will vanish. Humans make decisions based on subjective preferences, brand loyalty, and user experience, but agents prioritize performance and economic outcomes. This means that as the lines blur between applications and agents, the value will flow to companies offering the most efficient and high-performing services—not those with the best user interfaces or strongest brands.

As competition shifts from subjective differentiation to objective performance metrics, users (both human and agent) stand to benefit the most.

Disclaimer:

1. This article is reprinted from Foresightnews. The copyright belongs to the original author [Robbie Petersen, a researcher at Delphi Digital]. If you have any objections to the reprint, please contact the Gate Learn team, which will handle the issue promptly according to relevant procedures.
2. Disclaimer: The views and opinions expressed in this article are those of the author alone and do not constitute any investment advice.
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