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市場調查報告書
商品編碼
1961063

全球保險業生成式人工智慧市場：依部署類型、技術、應用和地區劃分－市場規模、產業動態、機會分析和預測（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個工作天內

價格
簡介目錄
保險業的生成式人工智慧市場正經歷爆炸性成長，預計到 2025 年市場規模將達到 11.1 億美元，並迅速成長至 2035 年的 143.5 億美元。這意味著在 2026 年至 2035 年的預測期內，其複合年增長率 (CAGR) 將達到約 29.11%。這項快速成長得益於生成式人工智慧技術的日益普及，這些技術正在革新保險的關鍵功能，例如承保、理賠處理和個人化客戶服務。 生成式人工智慧透過自動化複雜且耗時的任務，顯著提高了保險公司的效率。其中最具影響力的應用之一是文件分析自動化，人工智慧系統可以快速解讀並從大量非結構化資料（例如保險單、發票和客戶溝通記錄）中提取相關資訊。這不僅縮短了處理時間，也減少了人為錯誤，因此獲得了更準確、更一致的結果。

主要市場趨勢

保險業的生成式人工智慧市場正在演變成一場激烈的“軍備競賽”，其特點是老牌科技巨頭和專業保險科技新創公司之間的激烈競爭。在供應商方面，微軟（透過與 OpenAI 的合作）和Google等產業領導者透過提供支撐眾多生成式人工智慧應用的基礎人工智慧模型而主導市場。特別是 OpenAI，透過成功籌集高達 66 億美元的新資金，並大力投資於人工智慧技術的研究、開發和規模化，鞏固了其主導地位。

雖然這些科技巨頭提供了基礎模型，但最激烈的競爭發生在應用層，專業保險科技公司正努力在這個領域開闢自己的利基市場。 例如，Sixfold致力於創新核保業務，推動人工智慧驅動的風險評估和決策改善。 同時，Liberate專注於打造一個代理平台，以簡化保險銷售和客戶互動。 Liberate在2025年成功融資5,000萬美元，充分體現了投資者對其細分市場策略的堅定信心。

智慧財產權也是一個至關重要的戰場，反映了人工智慧創新的戰略重要性。平安保險在該領域佔主導地位，擁有驚人的53521項專利申請，在全球生成式人工智慧領域排名第二。這展現了其對維持技術領先地位的堅定承諾。瑞士再保險公司緊隨其後，擁有 634 項專利組合，凸顯了其對保護人工智慧驅動技術進步的高度重視。

核心驅動因素

在生成式人工智慧保險市場，其應用正從單純的競爭優勢轉變為生存必需品，這主要受日益加劇的經濟波動性驅動。 隨著理賠相關成本的持續飆升，傳統的理賠處理和風險管理方法已難以為繼，保險公司正面臨越來越大的壓力。在理賠成本飆升引發惡性通貨膨脹之後，這種緊迫性尤其強烈，迫使各公司尋求創新解決方案來減少損失並提高營運效率。

新機會與趨勢

支撐保險業生成式人工智慧市場的技術基礎已從早期簡單的聊天機器人介面發展到如今的規模。雖然聊天機器人最初旨在處理簡單的客戶諮詢，但當前情況需要更先進、更強大的工具來滿足保險業的複雜需求。 這一演進的核心是大規模語言模型 (LLM)，它提供了先進的自然語言理解和生成能力，這對於涉及細微差別的對話和決策過程至關重要。

優化障礙

保護敏感的客戶資料是企業的首要任務，60% 的企業認為這是採用新技術的最大障礙之一。在當今資料外洩和網路威脅頻繁的時代，各組織認識到，保護個人和財務資訊不僅對於維護客戶信任至關重要，而且對於遵守嚴格的監管要求也至關重要。資料外洩帶來的潛在風險（從經濟處罰到聲譽損害）使資料保護成為一個複雜且緊迫的問題。

目錄

第一章 摘要整理：保險市場的生成式人工智慧

第二章 報告概述

  • 研究框架
    • 研究目標
    • 市場定義
    • 市場區隔
  • 研究方法
    • 市場規模估算
    • 質性研究
    • 量化研究
    • 依地區劃分的主要調查受訪者組成
    • 資料三角驗證
    • 研究假設

第三章 保險業的生成式人工智慧市場概述

  • 產業價值鏈分析
    • 資料基礎設施供應商
    • 人工智慧模型開發與平台
    • 系統整合與應用層
    • 核心保險運營
    • 銷售推廣與銷售支持
    • 合規、風險與績效監控
    • 最終用戶
  • 行業展望
    • 全球保險業及數位轉型概覽
    • 理賠自動化和高度個人化承保加速需求成長
    • 技術進步：LLM、多模態人工智慧、保險工作流程自動化
    • 新興保險科技帶來的轉型、競爭格局及投資趨勢
    • 監理、倫理人工智慧及資料治理框架
  • PESTLE分析
  • 波特五力分析
    • 供應商議價能力
    • 買方議價能力
    • 替代品威脅
    • 新進入者威脅
    • 競爭強度競爭格局
  • 市場成長與展望
    • 市場收益估計·預測(2020-2035年)
    • 依推動方式價格分析
  • 市場魅力分析
    • 依推動方式
  • 實踐性的知識和見識(分析師的推薦事項)

第四章 競爭格局概覽

  • 市場集中度
  • 公司佔有率分析（基於價值，2025）
  • 競爭格局分析與基準分析

第五章：保險業生成式人工智慧市場分析

  • 市場動態與趨勢
    • 成長驅動因素
    • 限制因素
    • 機遇
    • 主要趨勢
  • 市場規模及預測（2020-2035）
    • 依部署類型劃分
    • 依技術類型劃分
    • 依應用領域劃分
    • 依地區劃分

第六章：北美保險業生成式人工智慧市場分析

第七章：歐洲保險業生成式人工智慧市場分析

第八章：亞太地區保險業生成式人工智慧市場分析

第九章：中東和非洲保險業生成式人工智慧市場分析

第十章：分析南美洲保險業的生成式人工智慧市場

第十一章：公司簡介

  • 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：附錄

簡介目錄
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