Recently, a phenomenon worth noting has emerged: several major cryptocurrency exchanges are simultaneously promoting AI agent trading tools. It may seem like coincidence, but it reflects a deeper trend: AI is becoming the main trading force in the crypto market.

However, there's an important distinction to clarify. Many people confuse AI trading with traditional quantitative robots, but they are fundamentally different. Traditional bots follow preset rules, such as "buy when RSI drops below 30," operating at microsecond speeds but completely lacking market understanding. AI agents, on the other hand, are based on large language models that can read news, understand what Federal Reserve rate hikes mean, and make judgments accordingly. Simply put, bots execute rules, while agents make decisions.

But there are two practical issues here. First is speed. Traditional quantitative bots have latency measured in milliseconds, whereas AI agents take hundreds of milliseconds to seconds to reason, making them thousands or even millions of times slower. Therefore, agents can't keep up with high-frequency arbitrage. Their advantage lies in decision quality, suitable for making one or two well-thought-out trades per hour.

Second is cost. Developing a traditional bot only involves server expenses, but each AI agent's judgment requires calling large model APIs, which costs money. For example, with GPT, if an agent analyzes the market every five minutes, the reasoning cost could be over $100 per month. For retail investors, this expense, combined with trading fees, makes achieving net profit quite challenging.

A 2025 AI trading competition illustrates this issue well. Multiple large models-driven agents competed simultaneously, resulting in extreme divergence: some lost 62%, others gained over 20%, but overall performance was highly unstable. In the second quarter, out of 15 bots, only one achieved positive returns; most lost money. PANews simulated the top-performing large models at that time, and the long-term profit expectation was negative across the board.

That's not all. AI agents' decisions can produce "hallucinations," where seemingly logical judgments are actually absurd. Although crypto exchanges have launched these tools, they also include cautious disclaimers, with some explicitly labeling them as "early experimental software."

There are also security risks. Agents hold private keys and trade autonomously. If the environment is compromised, assets could be entirely lost. Cases have already emerged where malicious skills were injected into platforms to steal user keys. While exchanges are indeed designing products around AI agents, this doesn't mean that simply accessing these tools guarantees automatic profits.

When many agents use the same skills and models to analyze the same market, their judgments tend to be highly correlated. Buy signals trigger simultaneously, pushing prices up rapidly, leaving little room for latecomers.

Ultimately, AI is just a tool. Data from 2023 shows that automated systems contributed over 70% of trading volume in the crypto market, and this proportion is still rising. But AI agent trading is still in the early experimental stage, with institutions that have extensive strategies and quantitative experience also using the same tools.

For ordinary investors, rather than rushing to build their own AI agents, it's better to control FOMO, understand the limits and weaknesses of these tools. The era of agent trading has indeed arrived, but whether you can make money ultimately depends on human strategic decision-making behind it. Don't be fooled by superficial technological progress. While crypto exchanges have launched these tools, relying on them to automatically generate profits is much more brutal in reality.