The adoption of cryptocurrency as a payment rail for AI agents is not a trend but a functional necessity. These digital channels provide the essential infrastructure—operating 24/7, globally accessible, and programmable—that aligns with the core operational model of autonomous AI. Traditional financial systems, designed for human interaction, rely on accounts, approvals, business hours, fragmented jurisdictions, slow settlement, and closed APIs. In contrast, AI agents inherently function around the clock, operate globally at internet speed, and can coordinate multiple services simultaneously. As AI agents evolve from offering advice to executing tasks, they are emerging as a new class of economic actors. They will identify opportunities, manage workflows, pay for services, route orders, and handle risk. A key limiting factor will be user trust. For instance, when a user delegates an overseas trip booking, they must trust the agent to act in their best interest. The payment process is merely the first point where this trust challenge manifests; the core issue is ensuring different systems can reliably interoperate and perform their intended functions. A recent case study is OpenClaw, an open-source agent that gained significant attention for automating tasks like email management and travel planning. However, its rapid rise also exposed critical security vulnerabilities, including incidents where it ran malicious plugins to exfiltrate user data. This highlights that the central challenge is not the agent itself, but its trust model. Granting an agent access to personal accounts represents unconditional, unverifiable trust. This trust deficit becomes a critical bottleneck as agents take on higher-value actions involving payments, legal work, and business operations. Users currently lack the ability to audit an agent’s actions, verify if they stayed within bounds, or prove authorization to counterparties. Major tech firms are attempting to build trust through brand reputation and closed ecosystems. However, their agents are constrained by isolated integrations, restricted partnerships, and centralized controls over what can be automated. APIs can be revoked, access throttled, or automation blocked if it threatens established interests. Cryptocurrency infrastructure, by contrast, is permissionless and peer-to-peer. An agent can discover a service, pay for it, and settle directly without platform approval. This makes crypto not just a lower-cost rail, but a neutral channel for autonomous commerce. Crypto transforms value transfer into a developer-friendly primitive. A wallet is a programmable entity capable of holding, sending, and receiving value. It enables 24/7 settlement, global interoperability, composability across services, and atomic execution (where action and payment occur in a single step). Crucially, it also provides verifiability. At a basic level, blockchains offer post-hoc verifiability and auditability. The greater potential, however, lies in preventive verifiability—where transactions cannot finalize unless they satisfy user-defined rules and constraints. This capability for policy-constrained execution is what will make it possible to trust agents with high-stakes economic activity. Users and businesses need mechanisms to constrain agent behavior within policy bounds, not just audit trails. Simple tools like spending limits mitigate risk but cannot capture nuanced intent. The real challenge and opportunity lie in integrating contextual data with policy into the settlement process in a scalable way without reintroducing intermediaries. In the long term, as AI models homogenize and infrastructure commoditizes, value will accrue to the control planes that agents rely on—systems managing identity, permissions, routing, settlement, and reputation. The enduring winners will be the systems that enable agents to operate reliably in the real world across interoperable channels. The “Uber moment” for agents will arrive not merely from superior intelligence, but from transforming trust from uncertainty to confident delegation within defined rules and safeguards. The largest agent companies will be those that make delegation safe. This shift presents a significant entrepreneurial opportunity. While incumbents may dominate distribution interfaces, their structural tendency is to build walled gardens. Startups can succeed by building the trusted execution layer between user intent and real-world outcomes: policy and permission control planes, neutral routers for optimal execution, and trust layers that secure autonomous workflows through escrow, guarantees, and dispute resolution. The primary market driver will be relieving user burden in workflows currently hampered by high trust and coordination costs, such as payments, cross-border commerce, invoicing, procurement, and personal task management. As AI agents become default operators of economic activity, cryptocurrency will serve as their settlement layer, enabling them to transact, coordinate, and prove their actions within an open ecosystem. The most lasting opportunities lie in building the layers of trust, execution, and interoperability that make delegation a practical reality.