AI Agents Are Repricing Crypto as Machine-Native Infrastructure Takes Shape

Several AI- and privacy-linked crypto assets are repricing sharply as the market starts paying more attention to the connection between artificial intelligence, blockchain infrastructure, payments, and compute. The bigger question is not simply whether “AI coins” move higher, but which networks and tokens can actually capture economic value if autonomous AI agents become real participants in the digital economy.

In One Minute

The major development here is the growing connection between AI and crypto infrastructure. The basic idea is straightforward: AI provides machine-native intelligence, crypto provides machine-native money, and blockchains can provide the programmable infrastructure connecting intelligence, payments, ownership, data, and compute.

That puts NEAR, Venice, and Zcash into focus, but for very different reasons. NEAR has one of the clearest infrastructure connections to autonomous AI agents, Venice directly connects token ownership with AI inference capacity, and Zcash represents the privacy side of a future machine economy. The opportunity is significant, but token-level value capture still has to be proven.

The Setup

The larger setup is the possibility that AI agents evolve beyond answering questions and begin acting independently.

An autonomous agent may eventually need to buy data, call an API, pay another agent, purchase services, acquire computing power, or move assets without waiting for a human to approve every individual transaction. That creates a need for programmable payment rails.

Stablecoins are especially important here because machines still need predictable units of account. Ethereum and other permissionless networks can provide settlement infrastructure, while systems such as x402, MCP, A2A and ACP are beginning to create standards for how agents communicate, transact and interact.

There is another piece that could become much larger: compute itself.

Claims on GPU capacity or computing resources could eventually become digital assets that can be purchased, traded, financed, or even pledged as collateral. Combined cloud revenue from AWS, Microsoft Intelligent Cloud, and Google Cloud has been estimated at around $1.1 trillion by 2030, so the potential economic base is enormous.

What Changed

The important change is that the AI-plus-crypto argument is moving beyond the simple idea of attaching an AI label to a token. The real discussion is increasingly about infrastructure.

If AI agents become economic actors, they need payment systems, identity, privacy, data access, cross-chain execution, and compute. That creates a much more serious investment question: which networks actually provide those services, and does activity on those networks translate into demand for the underlying token?

That second question matters. More blockchain usage does not automatically mean proportional token appreciation. Fee structures, staking systems, gas sponsorship, and token economics determine whether network activity actually creates value for token holders.

Digital Assets and Crypto

NEAR

NEAR has one of the strongest direct connections to this theme.

The network has moved heavily toward AI-agent infrastructure, including NEAR Intents, private inference, confidential execution, and the IronClaw agent environment.

NEAR Intents is particularly interesting because an agent does not necessarily need to understand every blockchain, bridge, or route. The agent specifies the result it wants, and competing solvers determine how to execute the transaction.

That structure makes sense in an autonomous-agent economy.

NEAR is also connected directly to private AI inference infrastructure being used by Venice, so the relationship between the two projects is not simply narrative.

The market has already started repricing NEAR. Its market capitalization was around $5.8 billion on September 23, compared with approximately $2.5 billion earlier this month.

NEAR has also recently moved toward the $3 area and beyond, so this is no longer an asset sitting completely unnoticed.

Venice and VVV

Venice may be one of the more interesting examples because VVV is not simply another token carrying an AI label. VVV launched in January 2025 with an initial supply of 100 million tokens.

The original allocation was:

• 50% to Venice users and the AI community

• 35% to Venice development and growth

• 10% to ecosystem incentives

• 5% for liquidity

The important mechanism is:

VVV → staked VVV → DIEM → AI inference capacity. DIEM represents $1 per day of Venice API credit per token.

That means Venice is effectively experimenting with turning future AI inference capacity into something that can be owned and transferred. That is very close to the broader idea of tokenizing claims on compute. Venice also uses part of its revenue to buy and burn VVV, which attempts to create a connection between actual platform activity, revenue, and token supply.

The market has already noticed. Venice reached roughly a $1.54 billion market capitalization on September 23, while the market cap was below $1 billion at the beginning of September.

VVV closed on September 22 around $31.91. So while this remains small compared with the largest crypto assets, I would not call it completely undiscovered anymore.

Zcash

Zcash is a different type of trade. ZEC is primarily a privacy asset, not an AI-compute network.

Its relevance comes from the possibility that autonomous agents eventually need private financial activity. If machines are constantly transacting on public blockchains, those transactions could expose commercially sensitive information, strategies, counterparties, and financial behavior.

Privacy infrastructure becomes much more valuable in that environment. Zcash uses zero-knowledge cryptography and shielded transactions to conceal transaction information while still allowing the network to verify that the transaction is legitimate.

The thesis makes sense, but it is more indirect than NEAR or Venice. Zcash has also already experienced a huge repricing. ZEC closed September 22 around $1,628, compared with roughly $1,023 on September 4, and its market capitalization reached approximately $27.6 billion.

The important areas I have been watching throughout this move have included $1,000, $1,200, $1,300, and $1,500. ZEC has already moved through all of those zones, which tells me this is no longer an early-stage move from a technical standpoint.

Bitcoin, Ethereum and Stablecoins

Bitcoin remains relevant to the broader machine-economy discussion, but the transactional side of this thesis probably has more immediate implications for programmable settlement networks and stablecoins.

Stablecoins have an obvious advantage because autonomous agents need predictable units of account.

Ethereum also matters because permissionless settlement can allow machines, applications, and agents to transact without requiring every interaction to pass through a traditional banking relationship.

This is why I would not reduce the entire AI-plus-crypto thesis to three speculative altcoins. The infrastructure layer matters just as much as the individual tokens people are chasing.

Why It Matters

This could eventually become much larger than another crypto narrative cycle.

If AI agents begin purchasing data, compute, services, and financial assets independently, they need an economic system designed for machines.

That means payments need to be programmable. Assets need to be digitally transferable. Compute may need to become tradable. Privacy may become more important. Cross-chain execution needs to become easier.

NEAR, Venice, and Zcash each attack a different part of that problem. NEAR is primarily infrastructure and execution. Venice connects crypto economics directly with AI inference capacity. Zcash represents privacy.

The opportunity is real, but the ecosystem is still early. Agentic payments and compute-market liquidity remain limited, so there is a major difference between identifying a powerful narrative and proving long-term token value.

Key Levels

ZEC is clearly the most extended of these moves based on the price progression already completed. NEAR and Venice are more directly connected to AI-agent infrastructure, but both have also already undergone meaningful repricing.

Bull Case

The bullish case is that autonomous AI agents become real economic actors rather than remaining primarily conversational software.

If agents increasingly purchase data, APIs, compute, and other digital services, programmable payments and blockchain settlement could become much more important. NEAR benefits if agent execution, intents, private inference and cross-chain activity grow.

Venice benefits if demand for AI inference expands and its VVV-to-DIEM model creates sustained demand for token ownership and staking. Zcash benefits if privacy becomes increasingly important as machine-generated transactions expand.

The larger bull case is simple: AI creates enormous machine-driven economic activity, and crypto becomes part of the infrastructure that settles it.

Bear Case

The biggest risk is confusing a powerful narrative with guaranteed token appreciation. The technology can succeed while individual tokens fail to capture much of the economic value.

Networks can generate transactions without creating proportional token demand. Gas sponsorship can weaken direct token usage. Fee structures may direct value elsewhere. Competing networks can offer similar services. Stablecoins may capture most transactional demand.

ZEC also carries a different risk because much of the AI connection depends on privacy becoming a major requirement for autonomous agents rather than on Zcash providing AI infrastructure directly.

And after moving from roughly $1,023 to $1,628 in less than three weeks, ZEC is clearly no longer entering this narrative from an untouched technical position.

What to Watch Next

I am watching whether AI agents actually begin generating measurable economic activity rather than simply attracting speculative capital. For NEAR, I want to see whether Intents, private inference, and autonomous-agent usage continue expanding.

For Venice, the important question is whether VVV staking, DIEM usage, API demand, and the buy-and-burn mechanism create sustainable token economics. For Zcash, I am watching whether privacy becomes a real component of machine-to-machine commerce or remains primarily a separate crypto narrative.

And across the entire sector, the most important confirmation would be growing real-world demand for stablecoin settlement, autonomous payments, and tokenized compute.

Bottom Line

The biggest story here is not simply NEAR, Venice or Zcash. It is the possibility that AI agents eventually require their own economic infrastructure, including programmable money, blockchain settlement, private transactions and access to tokenized compute.

NEAR and Venice have direct technological connections to that future. Zcash represents the privacy side of the same potential economy. But the narrative is developing faster than proof of long-term token value, so I am watching adoption, token economics, and price discipline rather than simply chasing the story.

The opportunity could be substantial, but price still matters, and I would rather understand where the value is actually being captured than buy a narrative after the market has already repriced it.