The reporter conducted research on a number of fund companies, including E-Fangda Fund, Huatai Berry Fund, Huitianfu Fund, Ping An Fund, Tianhong Fund, Jianxin Fund, Morgan Fund, Southern Fund, and China Merchants Fund. The fund company interviewed believes that AI has moved from concept to practice in ETF operations, but it is positioned as an “auxiliary enhancement” rather than a “core replacement”, that is, AI is still a “supporting role” in the core aspects of ETF operations such as PCF production and IOPV calculation. Meanwhile, in processes that rely on pattern recognition such as liquidity management, redemption prediction, and risk monitoring, AI's efficiency advantages are gradually being unleashed. There are also companies that confess that AI has not yet been used in ETF operations. However, most fund companies believe that looking ahead to the next three to five years, AI breakthroughs in ETF real-time risk control, operation automation, and investor services are most worth looking forward to. However, risks such as data security, model interpretability, automation pitfalls, and degradation of human capabilities are also thresholds that the industry must carefully cross when embracing AI.

The reporter conducted research on a number of fund companies, including E-Fangda Fund, Huatai Berry Fund, Huitianfu Fund, Ping An Fund, Tianhong Fund, Jianxin Fund, Morgan Fund, Southern Fund, and China Merchants Fund. The fund company interviewed believes that AI has moved from concept to practice in ETF operations, but it is positioned as an “auxiliary enhancement” rather than a “core replacement”, that is, AI is still a “supporting role” in the core aspects of ETF operations such as PCF production and IOPV calculation. Meanwhile, in processes that rely on pattern recognition such as liquidity management, redemption prediction, and risk monitoring, AI's efficiency advantages are gradually being unleashed. There are also companies that confess that AI has not yet been used in ETF operations. However, most fund companies believe that looking ahead to the next three to five years, AI breakthroughs in ETF real-time risk control, operation automation, and investor services are most worth looking forward to. However, risks such as data security, model interpretability, automation pitfalls, and degradation of human capabilities are also thresholds that the industry must carefully cross when embracing AI.