Ethereum prepares the platform for the autonomous machine economy

Ethereum is positioning its foundational layer to coordinate autonomous agents (, paving the way for machine-to-machine ) commerce with the capability for direct on-chain ( payments in the coming year.

This month, the Ethereum Foundation has established a dedicated team called the dAI Team, responsible for developing identity, reputation, and payment for agents, including support for ERC-8004 – a draft standard for the authentication and verification of agent identity, aimed at anchoring identity and confirming it at the protocol level.

This initiative shapes Ethereum as a coordination and payment layer for the "agent economy", with the core goal of censorship resistance and open access. Community drafts on ERC-8004 present how on-chain identity and reputation can enable an automated system to negotiate, stake, and execute escrow )escrow( without the need for a managing intermediary.

The short-term goal is to promote research and standards for wallets, middleware, and dApp applications by 2026, creating a common reputable platform for agent applications.

) AI market signs in cryptocurrency

The token line has reflected a trend leaning towards AI. AI-focused tokens like Bittensor, Fetch.ai, Internet Computer, and Render have maintained stable on-chain activity and relatively solid prices in Q3, outperforming other altcoins in the recent market downturn.

Koinly's reports indicate a continuous demand for decentralized computing, inference, and frameworks for agents, while ICP drives native application storage and Render provides a stable GPU marketplace for AI workloads.

According to Token Metrics, the value of locked DeFi (TVL) has recovered from around 72 billion USD at the beginning of 2025 to nearly 100 billion USD, with AI-native DeFi platforms like Blackhole DEX on Avalanche, Sahara AI, and Moby AI contributing to trading volume and fees throughout the period of volatility. Token Metrics suggests that this is a trend towards automated liquidity and the execution of cross-chain agents through messaging and omnichain abstractions.

Automatic payment for agents

The payment system is converging on the use cases of agents at the protocol boundary. Last September, Google launched the Agents to Payments protocol (AP2), allowing agent software to request and confirm consumer payments through a standardized process – laying the foundation for the payment model and machine-to-machine registration integrated with crypto payment channels.

According to Google Cloud, AP2 is designed with clear user consent, verifiable agent identity, and reversible transactions to comply with regulations. The initial tests integrate Ethereum and ICP through third-party connectors linking fiat accounts to on-chain transfers.

When maturing the testing, the wallet can treat the agent as an official entity, with ERC-8004 style authentication that allows spending limits over time, restricts trading partners, or requires co-signing by humans for high-value transactions.

Forecast network pressure and TVL

Forecast models link infrastructure upgrades with actual network demand. Token Metrics predicts that AI agents could account for 15–20% of DeFi trading volume by the end of Q4 2025. If Ethereum effectively implements the dAI roadmap, AI-integrated protocols could achieve a TVL of 200–300 billion USD by the end of 2026.

The widespread adoption of ERC-8004 will cause gas usage for identity and contract execution agents to increase by 30–40% each quarter in 2026, as standards are implemented across wallets, custody, and middleware DAOs.

In fact, this means that governance, fund balancing, fee coordination, and inter-chain liquidity can be managed by software agents with risk limits, insurance, and on-chain verification certificates.

( Smart security with AI

Academic and industrial research shows that AI-assisted smart contracts can significantly reduce the risk of attacks. Systems that combine rule-based controls and machine learning algorithms can reduce successful attacks by up to 70% compared to static contracts, provided that transparent updating policies and on-chain behavior can be monitored.

) Legal and Human Resources Context

The legal proposal in the US and Europe is examining automated financial agents, transparent adaptive contracts, and model risk. The requirements for identity, usage policies, and exception handling must be transparent to regulators and partners, in line with the ERC-8004 direction of Ethereum.

Recruitment data remains positive: Recruitblock reports a 22% increase in AI x blockchain positions in 2025, including protocol engineers, data infrastructure, and application cryptography – which are crucial for deploying agent frameworks at scale.

Cross-chain competition and cooperation

The machine economy is not limited to a single stack: Avalanche focuses AI liquidity through Blackhole DEX, Ethereum for identity and settlement, NEAR & ICP for native application storage and low-latency inference, Render provides GPUs for training and model serving. These platforms complement each other, not directly replacing, expanding the need for decentralized inference and coordinating the market as agents become the default entities in payments, fulfillment, and protocol operations.

If the ICP model for native AI hosting is successful, the on-chain inference cycle could reduce latency by half by 2026, enabling agents to interact directly in user applications such as intent routing, real-time risk mitigation, and supply chain/IoT payments.

Summary table of some main AI protocols ### TVL/on-chain, September 2025###

| Protocol | Main AI Function | On-chain Volume / TVL | Future Focus | | --- | --- | --- | --- | | Ethereum | Identity & payment agent, ERC-8004, dAI Team | 38 billion USD+ | Trust & coordination layer for agents | | Bittensor, TAO | Decentralized training & inference market | Estimated 1.4 billion USD | Open AI compute exchange | | Fetch.ai, FET | Autonomous economic agents, dApp infrastructure | Estimated 640 million USD | Machine-to-machine coordination | | Render, RNDR | Decentralized GPU & inference fee | ~985 million USD | Backbone compute for AI on-chain | | Internet Computer, ICP | Hosting AI app on-chain | 800 million USD+ | Reduce latency for dApp agents | | Blackhole DEX, Avalanche | AMM & AI-managed liquidity | 193 million USD | Unauthorized agent trading limit |

Three growth scenarios

1. Base case: Ethereum strengthens the identity and trust layer; at least 25% of new dApps will adopt agent automation by 2026, governance, funds, fees, and payments are programmed based on attestations.
2. Bull case: A fully equipped machine economy, agents conducting bilateral negotiations and fulfillment, DeFi TVL exceeding 300 billion USD, decentralized AI marketplace API reaching significant volume.
3. Bear case: Regulations for licensing agents and concentrating compute/AI, limiting open participation and innovation to only a few teams with significant resources.

ERC-8004, AP2 and practical data on adaptive control will be the monitoring points to evaluate practical application, rather than just relying on token price.

If identity, attestations, and policies live on-chain, the machine economy will by default operate on a public ledger, turning DeFi into an operating system for non-human economic activities. Conversely, if these checks remain on a closed platform, the role of crypto will diminish to that of bridges and payment channels.

With Ethereum's dAI roadmap, AP2 for agent payments and AI x crypto recruitment trends, the focus is shifting towards verifiable on-chain coordination, viewing agents as official components in the market.

Qin Shi Huang