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In unpredictable market environments, AI trading bots reliant on historical data may struggle.
Bitget CEO Gracy Chen remarks that AI trading applications currently function like interns; they will eventually transition into full-time roles.
Bitget CEO Gracy Chen (CoinDesk)
Key points:
- Uncommon market occurrences such as the 10/10 liquidations or even last week’s significant sell-offs will leave agentic trading models lacking.
- Human day traders and retail investors are too emotional to effectively compete with AI, stated the founder of an agentic trading venture.
Current AI trading bots operate on a limited set of historical data, which implies that completely novel market events like the 10/10 liquidations or even the severe sell-offs of last week will leave agentic trading models inadequate.
These AI models driven by historical data have not encountered substantial liquidations in a single day, making such events “very unfamiliar,” remarked Bitget CEO Gracy Chen during a discussion on agentic trading bots at Consensus Hong Kong 2026. Consequently, human involvement is essential.
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“As an exchange, we do not intend to develop our own LLM [large language model]. However, trading bots are significant,” Chen stated. “Present AI bots resemble interns: they are faster and more cost-effective, yet require some level of oversight.”
Nonetheless, in the future, these systems will evolve to function more like “full employees,” and within 3-5 years, AI could potentially take over many roles, Chen noted.
These notions are commonly expressed within the algorithmic trading sector regarding AI.
Although sophisticated LLM and machine learning trading technologies are advancing rapidly, there remains a widespread belief that human oversight is a crucial component of the process—especially during periods of extreme volatility, such as those recently experienced in the crypto markets.
Alongside Chen on the panel, Saad Naj, founder and CEO of the agentic trading startup PiP World, concurred that the technology is still in its early stages, which brings inherent risks. He emphasized that 90% of day traders and retail investors incur losses.
“As humans, we are too emotional. We cannot effectively compete with AI solutions,” Naj remarked.
