Morningstar(US:MORN) Morningstar晨星·2025-08-21 01:05Core Viewpoint - The main challenge for AI applications in the financial industry is not the technology itself, but the internal digital transformation readiness of institutions, particularly in data governance and the deep integration of business processes [1][10]. Group 1: Current State of AI Applications and Industry Opportunities - AI is penetrating the entire process of wealth management, from customer acquisition to post-investment services, with many institutions focusing on internal efficiency improvements [9]. - AI technologies are enhancing content creation and user experience in the financial sector, with tools like digital humans and large models optimizing content consumption [9]. - The transformation driven by AI is evident in the creation of personalized recommendations based on deep analysis of customer behavior data [9][10]. Group 2: Overcoming Native Barriers in AI Applications in Finance - The low tolerance for error in the financial industry necessitates a human-in-the-loop approach, where AI serves as a tool to enhance efficiency but human oversight remains essential [13]. - Key challenges include ensuring data security, achieving high accuracy in wealth management queries, and leveraging the data-intensive nature of the financial sector for AI applications [13]. Group 3: Enhancing Investor Experience through AI - AI can effectively correct irrational investment behaviors and provide continuous support to clients, enhancing trust and emotional reassurance [15]. - As AI models evolve, they are expected to take on more tasks traditionally performed by humans, although the journey towards full automation remains lengthy [15].