The report from exchange MEXC, which surveyed 3,708 participants, reveals a clear hierarchy of trust in automated systems. Traders favor AI for market analysis and research, where nearly 60% report improved outcomes. Conversely, direct trade execution remains a point of friction; only 20% of users have attempted fully automated trading without manual approval for each transaction. Even among those open to automation, 54% would restrict the AI to managing less than 20% of their total account balance, underscoring a persistent fear that automated agents might fail to flag or halt errors in volatile conditions.

Risk management remains the primary catalyst for wider adoption. When platforms provide robust safeguards—such as limits on leverage, position sizing, and automated loss thresholds—the willingness to employ AI agents jumps from 55% to nearly 72%. Technical analysis from the security firm Hacken suggests these localized controls are critical. Without independent boundaries, traders remain vulnerable to agents being manipulated into high-risk asset purchases or excessive exposure, regardless of withdrawal restrictions. Ultimately, the data indicates that demand for AI in crypto is not a push for total hands-off management, but a request for sophisticated, user-defined boundaries that balance efficiency with human oversight.