The Economy of AI Agents: Why Crypto May Hold the Key to Financial Management

AI agents – autonomous systems designed to make decisions, perform tasks and interact in digital environments – are being seen as a game changer for various industries, including finance. These agents work independently, follow predetermined or adaptive goals, and perform tasks ranging from customer service to financial management.

Investor interest in AI startups has increased recently: in the past 12 months, there have been 156 deals in the AI ​​agent space, marking an 81.4% year-on-year increase, according to PitchBook. So far in 2024, AI agents alone have raised more than $1 billion according to CB Insights. Across the AI ​​sector as a whole, investment levels are reaching record highs, with $18.9 billion raised in Q3 2024 alone, comprising 28% of all venture funding – highlighted by the unprecedented OpenAI It was worth $6.6 billion, which is the biggest business of all time, according to. Crunchbase.

As the capabilities of autonomous agents become more apparent, crypto is emerging as a promising tool to help AI agents manage funds safely and autonomously, with the potential to overcome the limitations of traditional financial systems. .

The Challenge of Traditional Finance for Autonomous AI Agents

In traditional finance, regulations such as Know Your Customer (KYC) and Anti-Money Laundering (AML) are important to ensure transparency, accountability and proper use of funds. However, these regulations assume that the person is responsible for any financial account and has passed accurate information and background checks. But in the case of AI agents, no one person or one legal entity can control the account directly, creating gray control areas.

In addition, financial instruments and traditional banking protocols are designed to serve human users. From online banking applications to investment accounts, every financial service is built on the assumption that there is a person or business responsible, authorized or of trade after each trade. An autonomous AI agent does not fit easily into these frameworks, making compliance challenging and legal uncertainty. Thus, for AI-driven currencies to work effectively, a solution that overcomes the limitations of traditional currencies while addressing security and regulatory issues is needed.

“Credit card processing is not designed for machine-to-machine payments,” it said If Levinco-founder and CPO of OpenCommerce. “It is riddled with inefficiencies, high transaction fees, and privacy issues, making it unsuitable for independent brokers. Stablecoins are a much better alternative, especially when bypass many of these pain points, allowing for smoother, more reliable interactions.”

Why Crypto Wallets are the Best Solution for AI Agents

Crypto wallets are a powerful solution to the challenges of automated money management by AI. Unlike traditional bank accounts, which often require personal information and human intermediaries, crypto wallets can be created and managed by software without direct human involvement. This independence makes crypto wallets an attractive option for AI agents who need to manage funds independently.

Crypto wallets are also very organized. The AI ​​agent can interact with the wallet’s API, set transaction rules, manage permissions, and even connect to decentralized finance (DeFi) protocols, allowing it to perform a variety of financial operations. This program empowers AI to act as a fully autonomous agent, capable of managing assets without manual intervention, a capability rarely found in traditional currencies.

“Freelancers can get out of the way, and with access to money, the stakes are even higher,” Levin said. “Keeping these agents on target is a big challenge. You need monitoring systems, budgets, and policies to prevent agents from delivering bad results that can put a lot of money at risk. Anonymity well when agents cause unique problems, and without proper infrastructure, the risks grow exponentially with each operation. That is why strong monitoring methods and control is essential in this area.”

In addition, the blockchain’s transparency and immutability provide a unique advantage. Every operation performed by the AI ​​is recorded in the chain, creating a transparent process that provides transparency and accountability – features that are highly valued by investors and regulators. This makes crypto wallets ideal tools for independent agents in the financial world, as long as certain security and regulatory measures are in place.

A Key Ownership Problem for AI Agents: Who Controls the Wallet?

Despite their advantages, crypto wallets present a difficult challenge for AI agents: key owners. In order for an AI agent to manage a crypto wallet, it needs access to the private keys. However, once an agent has these keys, they effectively have unlimited control over the wallet’s assets, which poses several risks:

1. Unlimited Use: If the agent gets access to privacy, he may make transactions that violate the rules or investment guidelines, which may harm the interests of the participants.
2. Hacking Risks and Security: Storing private keys directly in AI systems makes them vulnerable to cyber attacks, especially if the AI ​​is running on the network.
3. Regulatory Agreement: Without a clear oversight plan, regulators may be reluctant to allow AI-controlled wallets to operate, especially if there is no way to mitigate unauthorized transactions.

“To reduce the risk, we combine the results from several AI models in the voting system, using different AI models and validators,” said Albert Castellana Lluís, co-founder and CEO of YeagerAI. “This helps us to separate the intelligence, reduce errors and malicious manipulation by relying on collective decisions. In fact, it is like putting AI decisions to court elections.”

To solve these problems, several basic control methods for AI agents have emerged, each with its own strengths and tradeoffs.

Investigating Key Management Solutions for AI Agents Wallets

Multi-signature wallets: Multi-sig wallets require multiple private keys to authorize transactions, which can be useful for AI agents. For example, an AI agent may obtain one key, while the relevant humans or an external security protocol hold the others. Funding will require multi-party approval, providing oversight and reducing agent autonomy for high expectations.

• Benefits: Multi-sig is straightforward, well supported in the crypto space, and provides transparency.
• Bad: It can slow down transaction performance, and syncing multiple signatures can be challenging for complex workloads.

The adoption of multi-sig wallets has seen significant growth, especially with platforms like Safe. Originally designed as a multi-sig wallet, Safe has evolved into a full smart contract wallet, offering enhanced security and convenience. This change allows for complex transaction logic and integration with separate applications, making it a powerful solution for managing crypto assets.

Trusted Execution Levels (TEEs): TEEs are secure areas in hardware, such as inside CPUs, that allow AI to securely process sensitive information such as private keys. By separating the key into devices, TEEs prevent unauthorized access, even if the AI ​​software environment is compromised.

• Benefits: TEE provides high security by physically separating the key.
• Bad: Resource limitations make scalability a challenge, and not all crypto wallets support TEE integration.

Multi-Party Computation (MPC): MPC, an encryption method where the private key is divided into many “shares” held by separate groups, appears as a promising solution for independent agents. In this model, the AI ​​has partial control over the wallet key. When a business proposal is made, the consent of other parties is required to re-create the key and authorize the sale. MPC provides a distributed but secure way to maintain control without fully restricting agent autonomy.

• Benefits: The MPC provides strong regulation and a strong compliance framework, as each action requires multi-party approval.
• Bad: MPC implementations can be expensive and demanding in terms of complexity, although continuous improvements improve performance.

Leading companies such as Fireblocks have driven significant advances in MPC fundamentals. Their platforms offer tools specifically designed for secure key management at the facility level, providing the speed and scale required for high-frequency transactions. This approach makes the MPC more efficient for AI-based funds, which enhances security and regulatory control.

Reflecting on his experience, Castellana Lluís added, “Our experience with StakeHound has taught us that even the best cryptographic solutions fail without solid protocols. To avoid mistakes of people is important, and we have incorporated that into our core management strategies. Involvement is critical in designing secure management strategies. Critical management systems are only as effective as processes which we have done to avoid human error and ensure compliance.”

Looking Ahead: Measuring Autonomy and Control for AI Agents

As AI agents advance in the financial world, it is important to find the right balance between autonomy and control. Crypto wallets provide a viable foundation for AI-based currencies, but effective asset management remains a challenge. Solutions such as multi-signature wallets, TEEs, and individual MPCs offer unique advantages, and a multi-solution approach can ultimately prove more efficient.

While these approaches make AI agents more efficient financially, regulatory questions remain. Organizations will need guarantees of accountability and transparency, and the crypto industry will need to provide mechanisms to protect against security risks and misuse. For those interested in opening up this space, exploring hybrid strategies and collaborating with regulatory agencies will be important to bring autonomous AI agents to maturity.