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市场调查报告书
商品编码
1961063

全球保险业生成式人工智慧市场：依部署类型、技术、应用和地区划分－市场规模、产业动态、机会分析和预测（2026-2035 年）

Global Generative AI in Insurance Market: By Deployment, Technology, Application, Region - Market Size, Industry Dynamics, Opportunity Analysis and Forecast for 2026-2035
出版日期: | 出版商: Astute Analytica | 英文 280 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录
保险业的生成式人工智慧市场正经历爆炸性成长，预计到 2025 年市场规模将达到 11.1 亿美元，并迅速成长至 2035 年的 143.5 亿美元。这意味着在 2026 年至 2035 年的预测期内，其复合年增长率 (CAGR) 将达到约 29.11%。这项快速成长得益于生成式人工智慧技术的日益普及，这些技术正在革新保险的关键功能，例如承保、理赔处理和个人化客户服务。 生成式人工智慧透过自动化复杂且耗时的任务，显着提高了保险公司的效率。其中最具影响力的应用之一是文件分析自动化，人工智慧系统可以快速解读并从大量非结构化资料（例如保险单、发票和客户沟通记录）中提取相关资讯。这不仅缩短了处理时间，也减少了人为错误，因此获得了更准确、更一致的结果。

主要市场趋势

保险业的生成式人工智慧市场正在演变成一场激烈的“军备竞赛”，其特点是老牌科技巨头和专业保险科技新创公司之间的激烈竞争。在供应商方面，微软（透过与 OpenAI 的合作）和Google等产业领导者透过提供支撑众多生成式人工智慧应用的基础人工智慧模型而主导市场。特别是 OpenAI，透过成功筹集高达 66 亿美元的新资金，并大力投资于人工智慧技术的研究、开发和规模化，巩固了其主导地位。

虽然这些科技巨头提供了基础模型，但最激烈的竞争发生在应用层，专业保险科技公司正努力在这个领域开闢自己的利基市场。 例如，Sixfold致力于创新核保业务，推动人工智慧驱动的风险评估和决策改善。 同时，Liberate专注于打造一个代理平台，以简化保险销售和客户互动。 Liberate在2025年成功融资5,000万美元，充分体现了投资者对其细分市场策略的坚定信心。

智慧财产权也是一个至关重要的战场，反映了人工智慧创新的战略重要性。平安保险在该领域占主导地位，拥有惊人的53521项专利申请，在全球生成式人工智慧领域排名第二。这展现了其对维持技术领先地位的坚定承诺。瑞士再保险公司紧随其后，拥有 634 项专利组合，凸显了其对保护人工智慧驱动技术进步的高度重视。

核心驱动因素

在生成式人工智慧保险市场，其应用正从单纯的竞争优势转变为生存必需品，这主要受日益加剧的经济波动性驱动。 随着理赔相关成本的持续飙升，传统的理赔处理和风险管理方法已难以为继，保险公司正面临越来越大的压力。在理赔成本飙升引发恶性通货膨胀之后，这种紧迫性尤其强烈，迫使各公司寻求创新解决方案来减少损失并提高营运效率。

新机会与趋势

支撑保险业生成式人工智慧市场的技术基础已从早期简单的聊天机器人介面发展到如今的规模。虽然聊天机器人最初旨在处理简单的客户咨询，但当前情况需要更先进、更强大的工具来满足保险业的复杂需求。 这一演进的核心是大规模语言模型 (LLM)，它提供了先进的自然语言理解和生成能力，这对于涉及细微差别的对话和决策过程至关重要。

优化障碍

保护敏感的客户资料是企业的首要任务，60% 的企业认为这是采用新技术的最大障碍之一。在当今资料外洩和网路威胁频繁的时代，各组织认识到，保护个人和财务资讯不仅对于维护客户信任至关重要，而且对于遵守严格的监管要求也至关重要。资料外洩带来的潜在风险（从经济处罚到声誉损害）使资料保护成为一个复杂且紧迫的问题。

目录

第一章 摘要整理：保险市场的生成式人工智慧

第二章 报告概述

  • 研究框架
    • 研究目标
    • 市场定义
    • 市场区隔
  • 研究方法
    • 市场规模估算
    • 质性研究
    • 量化研究
    • 依地区划分的主要调查受访者组成
    • 资料三角验证
    • 研究假设

第三章 保险业的生成式人工智慧市场概述

  • 产业价值链分析
    • 资料基础设施供应商
    • 人工智慧模型开发与平台
    • 系统整合与应用层
    • 核心保险运营
    • 销售推广与销售支持
    • 合规、风险与绩效监控
    • 最终用户
  • 行业展望
    • 全球保险业及数位转型概览
    • 理赔自动化和高度个人化承保加速需求成长
    • 技术进步：LLM、多模态人工智慧、保险工作流程自动化
    • 新兴保险科技带来的转型、竞争格局及投资趋势
    • 监理、伦理人工智慧及资料治理框架
  • PESTLE分析
  • 波特五力分析
    • 供应商议价能力
    • 买方议价能力
    • 替代品威胁
    • 新进入者威胁
    • 竞争强度竞争格局
  • 市场成长与展望
    • 市场收益估计·预测(2020-2035年)
    • 依推动方式价格分析
  • 市场魅力分析
    • 依推动方式
  • 实践性的知识和见识(分析师的推荐事项)

第四章 竞争格局概览

  • 市场集中度
  • 公司占有率分析（基于价值，2025）
  • 竞争格局分析与基准分析

第五章：保险业生成式人工智慧市场分析

  • 市场动态与趋势
    • 成长驱动因素
    • 限制因素
    • 机遇
    • 主要趋势
  • 市场规模及预测（2020-2035）
    • 依部署类型划分
    • 依技术类型划分
    • 依应用领域划分
    • 依地区划分

第六章：北美保险业生成式人工智慧市场分析

第七章：欧洲保险业生成式人工智慧市场分析

第八章：亚太地区保险业生成式人工智慧市场分析

第九章：中东和非洲保险业生成式人工智慧市场分析

第十章：分析南美洲保险业的生成式人工智慧市场

第十一章：公司简介

  • Aisera
  • Alphabet Inc.
  • Anadea
  • Ava​​amo
  • Chisel AI
  • Clearcover
  • DataRobot Inc.
  • Mind Foundry
  • Persado, Inc.
  • Quantiphi
  • Shift Technology
  • SoluLab
  • Thoma Bravo (Majesco Limited.)

第十二章：附录

简介目录
Product Code: AA01261672

The generative AI market in insurance is experiencing explosive growth, with its valuation reaching USD 1.11 billion in 2025 and projected to soar to USD 14.35 billion by 2035. This represents a remarkable compound annual growth rate (CAGR) of approximately 29.11% over the forecast period from 2026 to 2035. Such rapid expansion is driven by the increasing adoption of generative AI technologies that are transforming key insurance functions, including underwriting, claims processing, and personalized customer service.

Generative AI is enabling insurers to significantly boost efficiency by automating complex and time-consuming tasks. One of the most impactful applications is the automation of document analysis, where AI systems can quickly interpret and extract relevant information from vast volumes of unstructured data such as policy documents, claims forms, and customer communications. This not only accelerates processing times but also reduces human error, leading to more accurate and consistent outcomes.

Noteworthy Market Developments

The generative AI in insurance market has evolved into a fierce "arms race" characterized by intense competition between established technology giants and specialized insurtech startups. On the provider side, industry leaders such as Microsoft, through its partnership with OpenAI, and Google are dominating the space by supplying the foundational AI models that underpin many generative AI applications. OpenAI, in particular, has solidified its dominant position by securing an impressive USD 6.6 billion in new funding, enabling it to invest heavily in research, development, and scaling of its AI technologies.

While the foundational models are supplied by these tech titans, the most intense battle is unfolding at the application layer, where specialized insurtech companies are striving to carve out distinct niches. Companies like Sixfold are innovating in underwriting, using AI to improve risk assessment and decision-making, while Liberate is focusing on agent platforms that streamline insurance sales and customer engagement. Liberate's success is underscored by its ability to raise USD 50 million in 2025, signaling strong investor confidence in its niche approach.

Intellectual property has also become a critical battleground, reflecting the strategic importance of AI innovations. Ping An stands out as a juggernaut in this domain, boasting an extraordinary 53,521 patent applications and ranking second globally in generative AI filings, demonstrating its commitment to securing technological leadership. Swiss Re follows as another major player with a portfolio of 634 patents, highlighting the value placed on protecting AI-driven advancements.

Core Growth Drivers

In the generative AI insurance market, adoption has shifted from being a mere competitive advantage to a vital survival mechanism, driven largely by increasing economic volatility. Insurers are facing mounting pressures as the costs associated with claims continue to surge, making traditional methods of claims processing and risk management increasingly unsustainable. This urgency is most acutely felt in the wake of hyper-inflation in claims costs, which has compelled companies to seek innovative solutions to curb losses and enhance operational efficiency.

Emerging Opportunity Trends

The technological foundation powering the generative AI market in insurance has advanced significantly beyond the early days of simple chatbot interfaces. While chatbots were initially designed to handle straightforward customer queries, the current landscape relies on far more sophisticated and powerful tools to meet the complex demands of the insurance industry. At the heart of this evolution are Large Language Models (LLMs), which provide the advanced natural language understanding and generation capabilities necessary for nuanced interactions and decision-making processes.

Barriers to Optimization

Protecting sensitive customer data stands as a critical priority for companies, with 60% identifying it as one of the most significant barriers to adopting new technologies. In an era where data breaches and cyber threats are increasingly common, organizations recognize that safeguarding personal and financial information is essential not only to maintain customer trust but also to comply with stringent regulatory requirements. The potential risks associated with data exposure-ranging from financial penalties to reputational damage-make data protection a complex and urgent challenge.

Detailed Market Segmentation

By Technology, Machine learning (ML) continues to be the dominant technology segment within the generative AI landscape in the insurance market, serving as the foundational engine that powers a wide range of AI applications. Its significance lies in its ability to analyze vast datasets, identify patterns, and generate predictive insights that directly contribute to improved decision-making and operational efficiency. In the context of insurance, ML models are central to delivering tangible returns on investment by enhancing core processes such as underwriting and claims management.

By Application, the fraud detection and credit analysis segment holds the largest share among applications because it delivers direct and quantifiable financial benefits to insurers, making it a critical focus area for investment and development. Fraudulent claims and credit risks pose significant challenges to the insurance industry, often leading to substantial financial losses. By targeting these issues, insurers can protect their bottom line more effectively, which explains the high demand for advanced solutions in this segment.

By Deployment, the cloud category has emerged as the dominant infrastructure, playing a pivotal role in supporting the scalability and computational demands of generative AI within the insurance market. Cloud platforms provide the essential backbone needed to handle the vast data processing and storage requirements inherent to advanced AI models, particularly Large Language Models (LLMs). This capability is critical as insurers seek to move beyond limited, on-premise pilot projects toward fully integrated, large-scale production environments that can deliver real-time insights and automation across their operations.

Segment Breakdown

By Deployment

  • Cloud-based
  • On-premise

By Technology

  • Machine Learning
  • Natural Language Processing

By Application

  • Fraud Detection and Credit Analysis
  • Customer Profiling and Segmentation
  • Product and Policy Design
  • Underwriting and Claims Assessment
  • Chatbots

By Region

  • North America
  • Europe
  • Asia Pacific
  • Middle East and Africa
  • South America

Geography Breakdown

  • North America holds a commanding position in the market, capturing a dominant 42% share driven by an intense and unprecedented "arms race" of capital investment. Both established incumbents and innovative disruptors in the region are successfully leveraging artificial intelligence (AI) to create new revenue streams and enhance operational efficiencies. This competitive environment fosters rapid innovation and commercialization, enabling companies to move swiftly from experimental phases to profitable ventures.
  • A clear example of this dynamic is evident in the performance of The Travelers Companies, which showcased the effectiveness of this strategy in their Q3 2025 earnings report. The company reported a core income that exceeded expectations by $1.9 billion, a milestone that CEO Alan Schnitzer attributed directly to their continued and focused investments in technology, particularly AI infrastructure. This financial strength not only highlights the successful monetization of advanced technologies but also illustrates how such investments are becoming central to driving shareholder value.

Leading Market Participants

  • Aisera
  • Alphabet Inc. (Google)
  • Amazon Web Services (AWS)
  • Anadea
  • Avaamo
  • Chisel AI
  • Clearcover
  • DataRobot Inc.
  • H2O.ai
  • LeewayHertz
  • Lemonade Inc.
  • Markovate
  • Microsoft Corporation
  • Mind Foundry
  • Persado, Inc.
  • Quantiphi
  • Shift Technology
  • SoluLab
  • Thoma Bravo (Majesco Limited.)
  • Tractable Ltd.
  • Other Prominent Players

Table of Content

Chapter 1. Executive Summary: Generative AI In Insurance Market

Chapter 2. Report Description

  • 2.1. Research Framework
    • 2.1.1. Research Objective
    • 2.1.2. Market Definitions
    • 2.1.3. Market Segmentation
  • 2.2. Research Methodology
    • 2.2.1. Market Size Estimation
    • 2.2.2. Qualitative Research
      • 2.2.2.1. Primary & Secondary Sources
    • 2.2.3. Quantitative Research
      • 2.2.3.1. Primary & Secondary Sources
    • 2.2.4. Breakdown of Primary Research Respondents, By Region
    • 2.2.5. Data Triangulation
    • 2.2.6. Assumption for Study

Chapter 3. Generative AI In Insurance Market Overview

  • 3.1. Industry Value Chain Analysis
    • 3.1.1. Data & Infrastructure Providers
    • 3.1.2. AI Model Development & Platforms
    • 3.1.3. System Integration & Application Layer
    • 3.1.4. Core Insurance Operations
    • 3.1.5. Distribution & Sales Enablement
    • 3.1.6. Compliance, Risk & Performance Monitoring
    • 3.1.7. End Users
  • 3.2. Industry Outlook
    • 3.2.1. Global Insurance Industry & Digital Transformation Overview
    • 3.2.2. Demand Acceleration from Claims Automation & Hyper-Personalized Underwriting
    • 3.2.3. Technology Evolution LLMs, Multimodal AI & Insurance Workflow Automation
    • 3.2.4. Emerging Insurtech Disruption & Competitive & Investment Landscape
    • 3.2.5. Regulatory, Ethical AI & Data Governance Framework
  • 3.3. PESTLE Analysis
  • 3.4. Porter's Five Forces Analysis
    • 3.4.1. Bargaining Power of Suppliers
    • 3.4.2. Bargaining Power of Buyers
    • 3.4.3. Threat of Substitutes
    • 3.4.4. Threat of New Entrants
    • 3.4.5. Degree of Competition
  • 3.5. Market Growth and Outlook
    • 3.5.1. Market Revenue Estimates and Forecast (US$ Mn), 2020-2035
    • 3.5.2. Pricing Analysis, By Propulsion Type
  • 3.6. Market Attractiveness Analysis
    • 3.6.1. By Propulsion Type
  • 3.7. Actionable Insights (Analyst's Recommendations)

Chapter 4. Competition Dashboard

  • 4.1. Market Concentration Rate
  • 4.2. Company Market Share Analysis (Value %), 2025
  • 4.3. Competitor Mapping & Benchmarking

Chapter 5. Generative AI In Insurance MarketAnalysis

  • 5.1. Market Dynamics and Trends
    • 5.1.1. Growth Drivers
    • 5.1.2. Restraints
    • 5.1.3. Opportunity
    • 5.1.4. Key Trends
  • 5.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 5.2.1. By Deployment
      • 5.2.1.1. ketKey Insights
        • 5.2.1.1.1. Cloud-based
        • 5.2.1.1.2. On-premise
    • 5.2.2. By Technology Type
      • 5.2.2.1. Key Insights
        • 5.2.2.1.1. Machine Learning
        • 5.2.2.1.2. Natural Language Processing
    • 5.2.3. By Application
      • 5.2.3.1. Key Insights
        • 5.2.3.1.1. Fraud Detection and Credit Analysis
        • 5.2.3.1.2. Customer Profiling and Segmentation
        • 5.2.3.1.3. Product and Policy Design
        • 5.2.3.1.4. Underwriting and Claims Assessment
        • 5.2.3.1.5. Chatbots
    • 5.2.4. By Region
      • 5.2.4.1. Key Insights
        • 5.2.4.1.1. North America
          • 5.2.4.1.1.1. The U.S.
          • 5.2.4.1.1.2. Canada
          • 5.2.4.1.1.3. Mexico
        • 5.2.4.1.2. Europe
          • 5.2.4.1.2.1. Western Europe
            • 5.2.4.1.2.1.1. The UK
            • 5.2.4.1.2.1.2. Germany
            • 5.2.4.1.2.1.3. France
            • 5.2.4.1.2.1.4. Italy
            • 5.2.4.1.2.1.5. Spain
            • 5.2.4.1.2.1.6. Rest of Western Europe
          • 5.2.4.1.2.2. Eastern Europe
            • 5.2.4.1.2.2.1. Poland
            • 5.2.4.1.2.2.2. Russia
            • 5.2.4.1.2.2.3. Rest of Eastern Europe
        • 5.2.4.1.3. Asia Pacific
          • 5.2.4.1.3.1. China
          • 5.2.4.1.3.2. India
          • 5.2.4.1.3.3. Japan
          • 5.2.4.1.3.4. South Korea
          • 5.2.4.1.3.5. Australia & New Zealand
          • 5.2.4.1.3.6. ASEAN
            • 5.2.4.1.3.6.1. Indonesia
            • 5.2.4.1.3.6.2. Malaysia
            • 5.2.4.1.3.6.3. Thailand
            • 5.2.4.1.3.6.4. Singapore
            • 5.2.4.1.3.6.5. Rest of ASEAN
          • 5.2.4.1.3.7. Rest of Asia Pacific
        • 5.2.4.1.4. Middle East & Africa
          • 5.2.4.1.4.1. UAE
          • 5.2.4.1.4.2. Saudi Arabia
          • 5.2.4.1.4.3. South Africa
          • 5.2.4.1.4.4. Rest of MEA
        • 5.2.4.1.5. South America
          • 5.2.4.1.5.1. Argentina
          • 5.2.4.1.5.2. Brazil
          • 5.2.4.1.5.3. Rest of South America

Chapter 6. North America Generative AI In Insurance Market Analysis

  • 6.1. Market Dynamics and Trends
    • 6.1.1. Growth Drivers
    • 6.1.2. Restraints
    • 6.1.3. Opportunity
    • 6.1.4. Key Trends
  • 6.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 6.2.1. By Deployment
    • 6.2.2. By Technology Type
    • 6.2.3. By Application
    • 6.2.4. By Country

Chapter 7. Europe Generative AI In Insurance Market Analysis

  • 7.1. Market Dynamics and Trends
    • 7.1.1. Growth Drivers
    • 7.1.2. Restraints
    • 7.1.3. Opportunity
    • 7.1.4. Key Trends
  • 7.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 7.2.1. By Deployment
    • 7.2.2. By Technology Type
    • 7.2.3. By Application
    • 7.2.4. By Country

Chapter 8. Asia Pacific Generative AI In Insurance Market Analysis

  • 8.1. Market Dynamics and Trends
    • 8.1.1. Growth Drivers
    • 8.1.2. Restraints
    • 8.1.3. Opportunity
    • 8.1.4. Key Trends
  • 8.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 8.2.1. By Deployment
    • 8.2.2. By Technology Type
    • 8.2.3. By Application
    • 8.2.4. By Country

Chapter 9. Middle East & Africa Generative AI In Insurance Market Analysis

  • 9.1. Market Dynamics and Trends
    • 9.1.1. Growth Drivers
    • 9.1.2. Restraints
    • 9.1.3. Opportunity
    • 9.1.4. Key Trends
  • 9.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 9.2.1. By Deployment
    • 9.2.2. By Technology Type
    • 9.2.3. By Application
    • 9.2.4. BY Country

Chapter 10. South America Generative AI In Insurance Market Analysis

  • 10.1. Market Dynamics and Trends
    • 10.1.1. Growth Drivers
    • 10.1.2. Restraints
    • 10.1.3. Opportunity
    • 10.1.4. Key Trends
  • 10.2. Market Size and Forecast, 2020-2035 (US$ Mn)
    • 10.2.1. By Deployment
    • 10.2.2. By Technology Type
    • 10.2.3. By Application
    • 10.2.4. By Country

Chapter 11. Company Profile (Company Overview, Company Timeline, Organization Structure, Key Product landscape, Financial Matrix, Key Customers/Sectors, Key Competitors, SWOT Analysis, Contact Address, and Business Strategy Outlook)

  • 11.1. Aisera
  • 11.2. Alphabet Inc
  • 11.3. Anadea
  • 11.4. Avaamo
  • 11.5. Chisel AI
  • 11.6. Clearcover
  • 11.7. DataRobot Inc.
  • 11.8. Mind Foundry
  • 11.9. Persado, Inc.
  • 11.10. Quantiphi
  • 11.11. Shift Technology
  • 11.12. SoluLab
  • 11.13. Thoma Bravo (Majesco Limited.)

Chapter 12. Annexure

  • 12.1. List of Secondary Sources
  • 12.2. Key Country Markets- Macro Economic Outlook/Indicators