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EY mentioned in the “White Paper on Financial AI Applications and Trusted Governance” released at the Expo on November 8 that artificial intelligence is driving financial functions from “recording, control, and reporting” to “forecasting, allocation, and co-creation.” According to EY global research, 68% of CFOs believe there is an urgent need to reassess how corporate value is measured; 80% of CFOs expect AI-driven business models to have a significant or moderate presence in the organization over the next 12 months. Financial AI has entered the critical stage of “can it have a real impact”. The value realization of financial AI follows the four-level path of “rule automation - intelligent assistance - agent collaboration - decision support”. The degree of AI autonomy should match business risk and operational irreversibility. Process restructuring rather than tool superposition is the key to hierarchical transition.
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EY mentioned in the “White Paper on Financial AI Applications and Trusted Governance” released at the Expo on November 8 that artificial intelligence is driving financial functions from “recording, control, and reporting” to “forecasting, allocation, and co-creation.” According to EY global research, 68% of CFOs believe there is an urgent need to reassess how corporate value is measured; 80% of CFOs expect AI-driven business models to have a significant or moderate presence in the organization over the next 12 months. Financial AI has entered the critical stage of “can it have a real impact”. The value realization of financial AI follows the four-level path of “rule automation - intelligent assistance - agent collaboration - decision support”. The degree of AI autonomy should match business risk and operational irreversibility. Process restructuring rather than tool superposition is the key to hierarchical transition.
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