Crypto’s New Best Friend: AI, and Why It’s Taking Over Finance

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Crypto’s always-on, programmable design fits AI agents, signaling a shift away from human-centered financial systems.

A shift is forming at the intersection of artificial intelligence and finance. Systems built around human limitations are beginning to show strain. As AI agents step into economic roles, long-standing financial structures appear increasingly outdated. Crypto, once seen as niche, is now being reframed as foundational infrastructure for machine-driven economies.

Human-Centric Finance Meets Machine Reality as Crypto Steps In

Speaking ahead of Consensus Miami, Nikil Viswanathan, co-founder of Alchemy, argued that modern finance was never designed for autonomous systems. Traditional banking reflects human routines-fixed hours, geographic limits, and identity verification tied to physical presence. AI agents operate outside those constraints.

Banks close because people sleep. Payments depend on borders because people live within them. Credit systems rely on identity tied to physical existence. None of these assumptions apply to AI agents, which function continuously, exist digitally, and transact without physical interaction.

“All transactions for agents are online. They’re inherently global,” Viswanathan said in an interview with CoinDesk.

Such differences expose friction in legacy finance. Cross-border payments still involve intermediaries, delays, and conversion costs. For humans, that friction is accepted. For machines executing tasks in real time, it becomes a barrier.

Crypto systems, by contrast, operate continuously and without centralized gatekeepers. Transactions settle globally, and value moves similarly to data across networks. That structure aligns more closely with how AI agents function.

AI Agents Favor Digital Assets as Global, Programmable Finance Layer Emerges

At a practical level, AI agents require financial systems with specific capabilities:

  • Continuous operation without downtime or manual intervention.
  • Native support for global transactions without geographic restrictions.
  • Ability to handle microtransactions efficiently at scale.
  • Direct programmability, allowing money to be controlled through code.

Viswanathan argued that crypto already meets these conditions. Blockchains provide an always-on financial layer where transactions execute automatically, without reliance on traditional intermediaries.

Complexity, often viewed as a drawback in crypto, is an advantage in this context. Human users struggle with private keys, seed phrases, and direct interaction with code. AI agents, however, operate natively in digital logic.

“Agents read in zeros and ones. That’s their native language,” Viswanathan said. “That’s also the language of crypto.”

Attempts to simplify crypto for human use have dominated the past few years. Wallet abstractions, custodial services, and user-friendly interfaces aimed to reduce friction. Yet the underlying architecture remains code-driven, aligning naturally with machine-based actors rather than people.

Viswanathan compared the current moment to the transition from postal systems to email. Physical mail requires time, effort, and infrastructure tied to human activity. Digital communication removed those constraints by operating in a computer-native environment.

Crypto, in his view, follows a similar trajectory. Instead of adapting fully to human limitations, it may find its strongest use case in systems run by machines.

Crypto + AI Could Reshape Global Finance, Nikil Viswanathan Says

Looking ahead, Viswanathan described a layered financial model. Crypto and traditional finance would form the base layer. Above that, AI agents would manage execution, handling wallets, routing transactions, and allocating capital in real time. Humans would interact through simplified interfaces, delegating complexity to automated systems.

“You can write code to manage a crypto wallet,” he said. “You can’t write code to manage a bank account in the same way.”

Such a structure suggests a shift in how financial systems are used. Rather than individuals directly managing every transaction, agents could act on their behalf, responding instantly to market conditions and operational needs.

Implications extend beyond convenience. A machine-driven financial system could reshape liquidity flows, reduce latency in global payments, and change how capital is allocated across markets.

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2026-04-26 16:22