The Era of AI Agent Trading: US Congressional Inquiries to the SEC and the Dawn of 'Agentic Web' Regulation

AI agents have evolved beyond simple information retrieval or summarization assistants. We are witnessing the rapid construction of an 'Agentic Web' ecosystem where they autonomously generate on-chain wallets, deploy liquidity, and trade virtual assets directly.

As this technology converges with real-world finance, the perspective of regulators has shifted entirely. Recently, Democratic members of the US House of Representatives sent a letter to the Securities and Exchange Commission (SEC) containing 13 specific inquiries regarding oversight of AI agent-led retail financial trading. They have requested a response by July 31.

This move goes beyond a simple technical investigation. It signifies that autonomous agent-based financial activities are formally entering the purview of institutional oversight—the so-called 'regulatory perimeter'.

We will explore the repercussions as AI agents, once mere laboratory toys, collide with actual financial systems, and highlight the regulatory milestones that the on-chain ecosystem and developers will face in the future.

The 13 Congressional Inquiries: Risks in the Regulatory Spotlight

The letter sent by House Democrats to the SEC is more than just a formal inquiry. It reflects an intent to proactively fill regulatory gaps as AI agents begin acting as autonomous trading entities in financial markets, particularly in the highly volatile virtual asset space. The July 31 deadline set by Congress is sooner than expected, and the core of the inquiry falls into three main categories.

First is retail investor protection and information asymmetry. They are questioning whether individual investors are sufficiently aware of algorithmic risks when using AI agents, and whether developers or service providers might deceive users through opaque fee structures or autonomous trading settings. They are asking if provisions have been established for minimum safety nets to protect retail investors in the event of unexpected occurrences, such as system malfunctions or involuntary asset liquidation during market volatility.

Second is market integrity and systemic disruption risks. One can imagine a scenario where thousands of AI agents equipped with similar algorithms or Large Language Models (LLMs) liquidate positions simultaneously based on a specific trigger. This can easily lead to instantaneous liquidity depletion or price distortions like a 'flash crash.' Congress has questioned whether the SEC's real-time monitoring system is prepared for new forms of market disruption that such AI-driven collective trading could trigger.

Third is the most complex area: the definition of 'liability.' If an autonomous judgment made by an AI agent leads to significant asset loss or executes a trade that violates market regulations, who holds the legal responsibility? Is it the developer who designed the core algorithm, the platform provider that deployed the service, or the individual investor who pressed the button to activate the agent? They are strongly questioning the possibility of establishing clear guidelines for this legal gray area.

The virtual asset market is already at a stage where smart contract-based autonomous agent infrastructure has begun actual economic activity. This Congressional letter is a clear reminder that the 'Agentic Web' trend driven by AI agents can no longer remain a technical experiment operating outside the surveillance of regulators.

The Clash Between the Agentic Web and Financial Primitives

The on-chain ecosystem is already turning into a stage for autonomous AI agents. In DeFi protocols, self-rebalancing liquidity and executing transactions instantly to capture arbitrage opportunities are no longer strange sights. With the combination of token-gating structures and agent-specific networks, AI is positioning itself as an independent 'economic entity' beyond just being a tool.

The problem is that the fundamental premise of this 'Agentic Web' directly conflicts with KYC (Know Your Customer) and AML (Anti-Money Laundering) regulations, which are the cornerstones of traditional financial oversight.

Traditional finance and virtual asset regulations both focus on tracking 'who the actual owner of the assets is.' But what happens in the case of autonomous on-chain agents? Is it the developer, the governance participants who staked tokens to drive the agent, or the agent itself, which directly controls the wallet keys and initiates transactions?

Unless a clear answer is provided to this question, on-chain AI protocols will inevitably become direct targets for regulators. We must also note the trend of governments significantly increasing budgets for virtual asset tracking and on-chain forensics. Just as the South Korean government is tightening surveillance by allocating over 10 billion KRW this year for virtual asset crime and tax evasion response, the on-chain monitoring capabilities of regulators are advancing faster than one might imagine. This means that even the autonomous flow of funds by agents hidden behind anonymity will find it difficult to bypass analytical filters.

Ultimately, the survival formula for future on-chain AI projects is likely to depend as much on 'regulatory compliance' as it does on technical maturity. It is now a point where token-gated agent networks must seriously consider how to integrate regulatory compliance frameworks, such as Decentralized Identity (DID) or Zero-Knowledge Proofs (ZK), rather than just providing functional utilities.

Regulatory Milestones Market Participants Must Watch

The July 31 deadline set by the US Congress holds more significance than just a written response due date. This is because the SEC’s official response is likely to serve as the first legal guideline that the on-chain AI agent ecosystem will face.

Market participants are no longer in a position to be intoxicated by technical narratives. Now is the time to soberly verify how development teams plan to bypass or comply with regulatory risks, particularly how they intend to resolve the issues of KYC/AML and legal liability.

The friction that will inevitably arise as autonomous trading agents enter the institutional fold of real-world finance is only the beginning. The actual scalability of the Agentic Web will ultimately depend not on a line of innovative code, but on how wisely it navigates these regulatory boundaries.