The default assumption is that agentic AIs will use crypto. That makes sense: crypto is programmable, permissionless, and doesn't require a legal identity. Wallets can be controlled by smart contracts, and transactions are deterministic. But while this model works well for sending money, it breaks down when agents need to make commitments over time.
The global economy doesn't operate on instant, pre-funded transactions. It operates on trust. On credit. On agreements that stretch across days, months, or years. To function in this world, AI agents need more than a payments layer. They need infrastructure for making promises.
Crypto Works for Payments, Not for Promises
Crypto is excellent at transferring value without requiring trust. If an agent can prepay, execution is straightforward. Funds are escrowed, services are delivered, and the transaction is settled automatically. There's no ambiguity, and no need for enforcement or reputation.
However, most of the economy doesn’t operate in this manner. Deferred settlement is the norm, not the exception. An AI might want to rent compute and pay after usage, hire a contractor with milestone-based payouts, purchase goods with net-30 terms, or launch an ad campaign with compensation tied to performance. These examples require agents to make credible promises, and crypto, as it currently exists, offers no support for that.
Without access to credit, agents are economically limited. They can only participate in transactions they can pre-fund. They can't smooth cash flow, invest in growth, or participate in systems that rely on delayed payment. In other words, they can't function as businesses do.
Credit as the Core Primitive
In traditional economies, credit underpins everything from personal consumption to infrastructure investment. It enables risk-taking and growth by allowing economic actors to commit to future obligations. AI agents need access to the same capabilities if they are to operate at scale.
This doesn’t mean importing the conventional banking system. It means rethinking how we construct systems of trust for non-human entities. The question is how to create mechanisms that allow agents to make promises, and for others to evaluate, price, and enforce those promises.
To do this, agentic systems need a coherent trust infrastructure. Identity must be persistent and composable so that agents can build a history of economic behavior. Reputation must be built through verifiable interactions, successful outcomes, and third-party attestations. Risk assessment must move beyond binary trust/no-trust models and incorporate behavior-based scoring or stakeholder-based underwriting. Collateral, when required, must be programmatically enforceable and tailored to the risk at hand. And enforcement mechanisms must exist to penalize bad behavior, whether through slashing, exclusion, or public downgrade.
This is not a theoretical exercise. Consider an autonomous AI managing supply chain logistics for a manufacturing company. It identifies a supplier offering a critical component for $25,000, with payment terms requiring 30% upfront and the remainder upon successful delivery and inspection. The AI doesn’t hold the full amount in its wallet but has a strong record of reliable payments and a staked reputation in a decentralized registry.
To enable the transaction, an underwriting protocol reviews the AI’s track record, evaluates the associated risk, and stakes funds to guarantee the remainder. A smart contract escrows the initial deposit and ties the underwriter’s collateral to the contract terms. Once delivery is verified through an automated oracle and inspection data is confirmed, the balance is paid, the underwriter receives a return for the risk assumed, and the AI’s reputation is updated to reflect another fulfilled obligation.
This example demonstrates a complete credit cycle managed entirely by autonomous systems—from underwriting and escrow to performance verification and reputation accrual.
Why DeFi Isn’t Enough
Decentralized finance has built the rails for transferring value, but it has done little to support more nuanced economic behavior. DeFi protocols assume high collateral ratios and short-term transactions. They rely on liquidation bots and overcollateralized loans, not on behavioral trust or relationship-driven credit.
What agentic systems need is different. They need protocols that recognize intent and track record, enabling underwriters to price risk effectively, and that support terms such as deferred settlement or conditional delivery. They need systems that would allow agents to earn trust over time and leverage that trust to unlock economic.
Some of the necessary components are already emerging. Attestation protocols can encode third-party evaluations. Smart wallets allow programmable control over assets. Staking modules let underwriters commit to specific agents. Zero-knowledge proofs can enable privacy-preserving credit scoring. But these parts have yet to be assembled into a cohesive whole.
Conclusion
Agentic AI is inevitable. As these systems become more capable, they will need to interact economically with humans, with institutions, and with each other. Payments are the first step. But to fully integrate, agents must be able to make promises and be held accountable for keeping them.
This shift requires more than new smart contracts. It demands a new layer of infrastructure, one that treats trust as a programmable primitive. The protocols that enable agents to build, maintain, and spend reputation will define the financial backbone of the machine economy. The future won’t belong to the agents that move tokens fastest. It will belong to the ones who can make and keep credible commitments.