从过去的实践效果看，人工智能与保险业的结合，可以在至少3个方面发挥效能。 其一，人工智能为行业客户运营、核保核赔、风险评估、产品迭代等各个经营环节赋能，有望显著 提升全要素生产率。全要素生产率是在所有其他要素投入数量保持不变的条件下，通过技术进步、组织 创新、专业化等方式增加的产出，是行业持续稳定增长的基本保障。人工智能及相关数字技术是当前提 升全要素生产率最具潜力的抓手。特别是，保险业的服务对象包括广泛、异质性的企业和个人，为其提 供服务大多有赖于专业人员"量体裁衣"式的工作，人工智能技术应用有利于以更低成本提供个性化产品 和服务，对保险业全要素生产率提升意义重大。 当前，我国保险企业正加速拥抱技术革新，多家保险机构践行"人工智能+"战略，以夯实核心能 力，优化既有业务，前瞻性布局创新业务，开拓增量空间。 通过持续探索与实践，人工智能等新技术的价值会逐步释放。保险企业应高度重视新技术发展趋 势，在战略上积极筹划数智化转型，明确短期侧重点和长期目标，特别是要结合机构自身特点，更冷静 地研判潜在成本与收益，恰当选择技术采用路径。已具备技术领先转型优势的企业，可深化技术应用以 巩固竞争力；起步滞后的企业，可考虑借 ...

Core Viewpoint - Insurance companies should prioritize the development of new technologies and strategically plan for digital transformation, balancing short-term focus and long-term goals while avoiding both "safe but mediocre" and "outstanding but risky" approaches [1][4] Group 1: Impact of Artificial Intelligence on the Insurance Industry - The integration of artificial intelligence (AI) in the insurance sector can enhance operational efficiency across various functions such as customer operations, underwriting, claims processing, risk assessment, and product iteration, significantly improving total factor productivity [1] - AI helps the insurance industry adapt to changing risk structures, promoting service function upgrades and innovative service models through proactive risk management systems that transition from passive compensation to active loss reduction [2] - The insurance sector is increasingly involved in AI governance, rule-making, and ecosystem building, which supports the development of new productive forces while ensuring the safe advancement of new technologies [2] Group 2: Challenges and Opportunities - The exploration of AI in the insurance industry represents a technology-driven innovation activity that is crucial for high-quality development, presenting both opportunities and challenges such as the disruption of traditional workforce structures and the high costs associated with AI implementation [3] - Issues such as incomplete coverage, insufficient accuracy, and high training costs of large models pose challenges to the practical application of AI in insurance, alongside concerns regarding algorithm reliability and potential biases [3] - The insurance industry is beginning to explore new insurance products like "generative AI content infringement liability insurance" to support technological advancements, but the penetration of technology insurance remains limited due to a lack of knowledge and experience [3]