The Day Trading Died: Why AGI Might Be the Last Market Maker

Summary:

The rapid advancement of Artificial General Intelligence (AGI) and autonomous trading systems is reshaping financial markets, particularly in crypto trading. With over 70% of trading on platforms like Binance and Coinbase already driven by algorithms, human traders are increasingly outperformed by AI-driven systems. Analysts predict that AGI could lead to the “Perfect Efficiency Paradox,” where markets become so efficient that traditional day trading strategies become obsolete. This shift threatens retail traders’ profitability while enhancing market liquidity and speed.

What This Means for You:

• Retail traders face diminishing alpha: With AI systems dominating trading, human traders must adapt by leveraging AI tools or shifting to alternative investment strategies.
• Automation accelerates market efficiency: Expect tighter spreads, faster executions, and reduced opportunities for arbitrage, especially in volatile markets.
• AGI could redefine market dynamics: AGI systems may integrate global macro trends, blockchain data, and supply chain insights, making human traders reactive rather than proactive.
• Prepare for a liquidity black hole: As AI-driven liquidity providers dominate, traditional trading advantages may disappear, requiring a focus on risk management and strategic oversight.

Original Post:

A growing wave of research and market data is reshaping long-held assumptions about the future of trading. Analysts across traditional finance and crypto markets are now debating a possibility once considered far-fetched: the gradual disappearance of day trading as Artificial General Intelligence (AGI) moves closer to reality. AGI does not yet exist, but progress in advanced multimodal systems and autonomous trading agents is pushing markets toward an environment where machines dominate price discovery and leave little room for human reactions.

As Algorithms Dominate 70% of Crypto Trading, Analysts Say AGI Could End Retail Alpha

High-frequency trading transformed equities years ago, and its logic expanded into crypto markets with the rise of firms such as Jump, Wintermute, and GSR. By 2024, Kaiko reported that more than 70% of trading flow on exchanges like Binance and Coinbase was generated by algorithms rather than humans.

This shift has reshaped market structure from the bottom up, reducing spreads and accelerating execution speed while also making it harder for retail traders to profit during high-volatility periods. Researchers point to these trends as early evidence of rising efficiency. During the Solana memecoin surge in 2024, trading bots, particularly “sniper” and “AI” bots, generally outperformed human traders due to their superior speed, automation, and lack of emotional bias.

Small AI systems designed to detect whale behavior and monitor blockchain flows reacted faster than discretionary traders and often positioned themselves before human participants understood what was happening. Each advance in automation has consistently reduced the opportunities available to retail participants, and analysts argue that AGI would push this pattern to its logical endpoint.

The difference between today’s narrow AI and future AGI sits at the center of this debate. Current models excel at specific tasks such as scanning order books, reading market sentiment, or identifying arbitrage. They cannot generalize across domains or apply human-like reasoning. AGI, by contrast, is expected to learn new tasks with minimal instruction, adapt to unfamiliar environments, and combine information from many unrelated sources. In financial markets, this would mean reading blockchain flows, interpreting global macro signs, assessing political risk, identifying whale movements, and evaluating supply-chain disruptions, all within a unified system capable of producing real-time forecasts.

AI Market Makers Move From Theory to Practice as Automation Surges

Warnings about this shift have circulated for years. DWF Labs noted in July that AI-driven market makers will increase liquidity, especially in smaller crypto assets with historically thin order books and wide spreads. Economist Alex Krüger described a future of hyper-efficient markets with little room for mistakes. BitMEX founder Arthur Hayes wrote that AI would eventually trade better than any human, while Ethereum co-founder Vitalik Buterin expressed concern that advanced systems could dominate MEV extraction and reduce human participation in core market functions.

These observations were treated as hypotheticals at the time, but rising levels of automation have since given them more weight. As automation accelerates, the human role on trading desks is already changing. Experts argue that humans will not disappear completely but will shift toward risk supervision, regulatory oversight, and interpreting unusual events that fall outside model expectations. Execution itself moves to autonomous systems. The growth of AI trading agents reflects this transition. These tools can research markets, choose strategies, adjust risk parameters, execute trades through APIs, and learn from outcomes without manual input. Forecasts suggest the AI trading bot market could reach approximately $75.5 billion by 2034.

Extra Information:

Kaiko’s Report on Algorithmic Trading: Provides detailed insights into the dominance of algorithms in crypto trading. AI Trading Market Forecast: Offers projections on the growth of AI-driven trading platforms. Vitalik Buterin’s Thoughts on Decentralization: Explores the implications of AI on decentralized systems.

People Also Ask About:

• What is AGI in trading? AGI refers to Artificial General Intelligence, a system capable of learning and adapting across diverse tasks, potentially revolutionizing financial markets.
• How does AI affect crypto trading? AI automates trading strategies, improves execution speed, and reduces opportunities for retail traders to gain an edge.
• Will AGI replace human traders? While AGI will likely handle execution, humans will focus on oversight and interpreting complex market events.
• What is the Perfect Efficiency Paradox? It describes a scenario where markets become so efficient that traditional trading strategies become obsolete.
• Can retail traders survive in AI-dominated markets? Retail traders must adapt by using AI tools or shifting to alternative strategies.

Expert Opinion:

“The rise of AGI in trading marks a paradigm shift. Markets will become faster and more efficient, but the human edge—the ability to interpret nuance and adapt to unpredictability—will remain invaluable. The challenge lies in integrating human intuition with machine precision.”

Key Terms:

• Artificial General Intelligence in trading
• AI-driven market makers
• Algorithmic trading dominance
• Perfect Efficiency Paradox
• AI trading bot market forecast
• Crypto trading automation
• Liquidity black hole in markets

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