The combination of AI and Crypto is moving from "storytelling" into the real execution phase.​​​​​​​

In the past, discussions about AI+Crypto were more focused on AI tokens, computing power, and data concepts.

But now, model capabilities, on-chain data, and Agent tools are gradually connecting.

On September 22, Anthropic released Claude Opus 5.5. Officially, the model emphasizes enhanced capabilities in coding, Agents, and long-cycle task execution, reducing the cost of typical workloads by about 40%.

Models are becoming cheaper and more capable of autonomously invoking tools to complete complex tasks.

This aligns perfectly with another layer of capability that Crypto can provide:

On-chain data is public, assets can be executed programmatically, and payments can also be completed via smart contracts.

This means AI may not only help users "analyze the market" but can further complete operations on behalf of users.

The real landing point of AI+Crypto is emerging

Currently, there are three main clear directions.

The first is on-chain analysis.

AI can read on-chain data such as wallets, transactions, and fund flows, transforming data that originally required manual analysis into more easily understandable information.

The second is automated strategies.

Agents can read market data, execute trades, or perform asset rebalancing according to preset rules.

The third is AI payment agents.

AI is no longer just recommending products but can complete payments under user authorization and regulatory constraints.

This pathway has already begun to enter traditional payment systems.

Visa and Mastercard recently announced a partnership with Ant International to establish an AI Agent payment trust framework, focusing on solving issues of identity recognition, authorization, and security when AI agents conduct transactions.

India is also promoting a UPI-based Agent payment framework, allowing AI to complete some small payments on behalf of users within certain limits and rules.

If AI can ultimately identify needs, invoke data, manage assets, and complete payments independently, it will create new use scenarios for the open financial infrastructure provided by Crypto.

But the real difficulties have not yet been resolved

AI+Crypto is still in its early stages.

Models may make erroneous judgments, and on-chain data may not equal real-world information; once an Agent has execution authority, issues of fund security, permission management, and responsibility attribution will arise.

Regulators also need to answer a question:

When AI completes a financial transaction on behalf of a user, who should bear the responsibility?

Rather, it is whether models can increasingly reliably read data, invoke tools, and complete actual tasks under clearly defined permissions.

If this path continues to mature, the combination of AI and Crypto may no longer be just a market narrative but may gradually form new application layers:

AI is responsible for understanding and decision-making, while the on-chain infrastructure is responsible for data, assets, and execution.

This is also where AI+Crypto deserves long-term tracking.

With the infrastructure of traditional payment systems.

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