Can AI outcompete human traders and execute 90% of global stock market volume without human oversight using reinforcement learning agents ?
Cast your vote — then read what our editor and the AI models found.
AI-driven trading systems already dominate short-term markets, but full autonomy at scale remains contested. Regulators worry about systemic risks when machines control price discovery across all assets. Can AI execute the next leap?
As of 2024, AI systems using reinforcement learning have made significant advances in automated trading, but fully outcompeting human traders with hands-off reinforcement-learning agents at 90% of global volume remains beyond the state of the art. Current systems operate at high frequency and can execute substantial order flow, yet they still rely on human oversight for strategy calibration, risk limits, and compliance checks. The most sophisticated agents achieve strong risk-adjusted returns in narrow market segments, but their edge often diminishes as markets adapt, and regulatory and ethical constraints further limit fully autonomous deployment at scale. SOURCE: Bank for International Settlements — https://www.bis.org/publ/work1135.htm
— Enriched May 9, 2026
Estado verificado por última vez en May 9, 2026.
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