国泰海通证券研报提到，险资将持续巩固债券"压舱石"地位，并逐步向长期地方债与跨境债延伸；权益 配比稳步提升，并通过私募证券基金与举牌等方式加速入市，整体呈现出"债券更追求性价比、权益配 置趋强"的趋势。 权益投资方面，险资将显现出怎样的偏好？苏商银行特约研究员付一夫预测，一方面，高股息板块（如 银行、公用事业）仍是压舱石；另一方面，新质生产力相关领域（如人工智能、高端制造、新能源、生 物医药）有望获增量配置。政策扶持、技术突破及国产替代逻辑强的板块，如半导体、新材料等，也可 能吸引险资逐步加仓。整体上，险资将更聚焦基本面扎实、符合国家战略方向的优质企业。 "险资的建仓节奏非常审慎，通常会等待估值回归合理区间、市场情绪降温后，再逐步配置。因此，短 期股价的波动更多反映市场情绪，而非险资的长期配置意图。"岳翔宇补充表示。 进入2026年，股市实现"开门红"，保险资金调研热情高涨，马不停蹄地寻找市场投资机会。东方财富 Choice数据显示，截至2月1日，保险公司、保险资管公司自2026开年来合计调研上市公司751次，涉及 数百家上市公司。险资动向一直是市场投资风向标，新的一年，险资看好哪些板块投资机会，又将有怎 样 ...

Core Viewpoint - The pre-calculation power sector is expected to experience continuous growth in 2025 due to ongoing Capex from major CSPs, increasing token demand, and enhanced product capabilities, with structural highlights in AI applications such as AI fintech, AI healthcare, and AI data [1][4] Revenue Side - The pre-calculation power sector is projected to maintain high growth in 2025, driven by sustained Capex from major CSPs and the release of token demand, with notable performance in AI applications across various fields [1][4] Profit Side - Profit growth in the pre-calculation power sector is expected to align with revenue growth in 2025, with some AI application companies showing high profit elasticity, and most previously loss-making companies either narrowing losses or turning profitable, indicating a significant improvement in overall profitability [2] 2026 Investment Outlook - The competition in domestic AI is transitioning from single-card performance to system-level capabilities, with super-node systems becoming crucial for future competition; the development of computing power is highly certain due to ongoing Capex investments and token demand [2] - AI applications are anticipated to reach a turning point, with model capability enhancements and new overseas opportunities, as domestic AI companies accelerate their international market presence [2] - Domestic policies are expected to continue supporting technology in sectors like satellites, healthcare, and consumer markets, marking a significant turning point for domestic AI [2]

Group 1: AI Applications in Banking - AI credit applications are crucial for banks, focusing on improving efficiency and quality in loan processes [2] - AI marketing utilizes user characteristics for intelligent modeling and enhances marketing strategies [3] - AI data capabilities help clients improve data analysis through natural language processing and data language conversion [3] - AI regulatory tools establish a bridge between raw data and final metrics for compliance and reporting [3] - AI knowledge bases assist clients in visualizing workflows and addressing specific business queries [3] Group 2: Challenges in AI Implementation - The accuracy of large models is generally high, but measures are in place to manage potential inaccuracies in client applications [4] - Implementing AI in client systems is complex due to existing architecture and processes, requiring a phased, modular approach [5] - Continuous technological advancements necessitate ongoing evaluation of new AI technologies for compatibility and application [5] - Communication barriers between technical and business teams can lead to mismatched requirements, which the company addresses by integrating algorithm personnel into business research [6] Group 3: Talent and Capability Development - Transitioning from IT product capabilities to business empowerment requires hybrid talent that understands both business needs and AI technology [6] - Product managers are essential for designing AI solutions that enhance client business capabilities and drive growth [6] Group 4: Risk Awareness - The content discussed in the investor relations activity does not constitute a substantive commitment from the company regarding future development plans or performance expectations [6]