Everyone Sees AI’s Growth — Few Notice Crypto Infrastructure Rising With It

3-Point Summary

• AI’s explosive growth creates upstream demand for physical infrastructure, followed by digital infrastructure such as blockchains.
• For AI to participate in economic activity, it requires decentralized data, payments, and trust layers — making blockchain integration structurally inevitable.
• As AI-generated traffic surges, demand for crypto infrastructure accelerates, with SharpLink, Coinbase, and Venice AI already signaling this convergence.

As AI scales at an explosive pace, crypto infrastructure rises as its inevitable downstream industry.

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The Future of Crypto Infrastructure in the Age of Explosive AI Growth — Why AI’s Rise Pulls Crypto With It

Fundstrat’s Tom Lee recently said on CNBC that “in 12 months, markets will see crypto as a downstream story of AI.” Today, crypto still feels undervalued, much like memory semiconductors were just before the AI boom.

His remark is not just a market call, but a precise description of a structural link: AI → infrastructure → crypto. As AI scales, demand for crypto infrastructure grows almost inevitably. This article breaks that down into three key flows.

1) Explosive AI Growth → Primary Market Demand: Physical Infrastructure Expansion (Memory & Compute)

As AI models grow, they demand more compute, more memory, more power, and more data access. That’s why the first major beneficiaries of the AI era were memory chips and compute infrastructure.

AI growth directly creates more computation → more memory demand → more data center expansion. In other words, AI first pulls up the physical infrastructure market, and then the digital infrastructure market (blockchains) follows.

2) Explosive AI Growth → Secondary Market Demand: Structural Coupling Between AI and Crypto for Economic Activity

For AI to move beyond pure computation and directly participate in economic activity, it needs several things:

• Trustworthy access to data
• Automated payments, settlement, and asset movement
• Verifiable proofs of actions
• A decentralized trust layer

These requirements are difficult to meet with Web2 infrastructure alone and naturally point toward blockchain integration.

For AI to operate economically, it needs three layers:

• A decentralized data layer
• A decentralized payment layer
• A decentralized trust layer

The only technology stack that can provide all three at once is Ethereum-centric blockchain infrastructure. As AI grows and starts to act as an economic agent, blockchains become AI’s base operating layer.

3) As AI Grows, Crypto Infrastructure Demand Grows With It

The expansion of AI leads directly to rising demand for crypto infrastructure. This can be summarized in four main flows.

① Infrastructure Expansion Demand — AI Generates Millions of On-Chain Calls per Second

AI repeatedly reads data, verifies states, executes payments, and updates on-chain status. This creates massive volumes of on-chain calls, driving demand for RPC, data indexing, MEV routing, and verification infrastructure.

Example — SharpLink
SharpLink is no longer just a gaming company. It is being redefined as an ETH-based infrastructure provider that handles AI, RWA, and L2-era traffic. ( Related article: In the L2·RWA·AI Era, Core Peripheral Infrastructure Providers Are Emerging )

② Institutional Adoption — AI Services Directly Use Blockchain Infrastructure

When AI automates finance, payments, and data verification, institutions begin to rely directly on blockchain infrastructure.

Example — Coinbase Developer Platform
Coinbase has built a flow where AI can handle wallet creation, payments, trading, and verification through a single API pipeline. AI only needs to call the Coinbase API, while Coinbase’s servers handle communication with the Base blockchain. ( Related article: Adding a Payment Layer on Top of HTTP: x402 and the Dawn of Autonomous AI Payments )

③ Rising Demand for Decentralized Computing — AI Needs Verifiable Computation

For AI’s actions to be trusted, they must produce verifiable results (Proof). This is where DA (Data Availability), ZK (Zero-Knowledge), decentralized computing, and receipts structures become critical.

Example — Receipts
Every transaction executed by AI leaves receipts, enabling services like Etherscan, The Graph, and wallets to provide accurate data. The receiptsRoot in the block header summarizes the execution results of the entire block and is a key element for verification. ( Related article: What Bitcoin Doesn’t Have but Ethereum Does: The Real Meaning of Receipts and Blobs )

④ Structural AI–Crypto Convergence — As AI Engages in Economic Activity, Blockchains Become the Base Layer

For AI to autonomously handle payments, authentication, and interactions, it needs decentralized identity, on-chain payments, and non-custodial data flows.

Example — Venice AI
Venice AI is a Privacy‑First Web3 AI that combines wallet signatures, on-chain payments, and non-storage data architecture. Inference is processed off-chain, while trust and payments are handled on-chain, offering a realistic model for Web3-native AI. ( Related article: The Convergence of AI and Blockchain: How Venice AI Is Building a Privacy‑First Future )

Conclusion — When AI Grows, Crypto Infrastructure Inevitably Grows Too

AI’s growth leads to:

• Increased demand for physical infrastructure (memory and compute)
• A structural need for blockchain integration so AI can participate in economic activity
• Exploding demand for crypto infrastructure driven by AI-generated traffic

SharpLink, Coinbase, and Venice AI are early signals that this shift is already underway.

As AI continues to grow, crypto will emerge as the inevitable downstream industry that scales alongside it.

Younchan Jung
Researcher exploring structural shifts in AI, blockchain, and the on‑chain economy.

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