보험용 AI 시장 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

The global AI in insurance market size is expected to reach USD 308.50 Billion in 2034 from USD 21.72 Billion in 2025, growing at a CAGR of 34.29% during 2026-2034.This market is growing as insurers increasingly adopt artificial intelligence to process large datasets, automate workflows, assess risks, detect fraud, and improve customer interactions. Insurance companies manage substantial volumes of structured and unstructured information, creating opportunities for machine learning and natural-language technologies. AI can support underwriting, claims processing, customer service, and document analysis. The growing availability of digital customer data and the pressure to improve operational efficiency are encouraging insurers to evaluate AI-based solutions across multiple stages of the insurance lifecycle.

Claims automation is an important application because AI can assist with document classification, image assessment, fraud detection, and initial claims evaluation. In underwriting, machine-learning models can analyze relevant data to support risk assessment and pricing workflows. Natural-language processing can also help insurers extract information from policies, forms, correspondence, and other documents. Customer-facing applications such as virtual assistants and personalized communication are expanding as insurers seek faster service. These applications can reduce manual workloads while helping organizations manage increasingly complex information flows.

Future prospects are supported by continued insurance digitization and advances in predictive and generative AI. Insurers are likely to expand AI use in risk modeling, claims management, customer engagement, and operational analytics. Greater attention will be required for explainability, data governance, cybersecurity, bias management, and regulatory compliance. Human oversight will remain important for high-impact insurance decisions. As insurers develop stronger data infrastructure and governance frameworks, AI can become more deeply integrated into workflows while supporting automation and more data-driven operational processes.

Our reports are carefully developed to deliver comprehensive and actionable insights across a wide range of industries and markets. Each report includes several essential components designed to provide a complete understanding of the market environment:

Market Overview: This section provides a clear introduction to the market, including key definitions, classifications, and an overview of the current industry landscape.

Market Dynamics: A detailed evaluation of the primary drivers, restraints, opportunities, and challenges shaping market growth. It covers factors such as technological developments, regulatory frameworks, and evolving industry trends.

Segmentation Analysis: A structured breakdown of the market into key segments based on product type, application, end-user, and geographic region. This section highlights the performance, growth potential, and contribution of each segment.

Competitive Landscape: An in-depth assessment of leading market participants, including their market positioning, product portfolios, strategic initiatives, and financial performance. It provides valuable insights into competitive dynamics and the strategies adopted by key players.

Market Forecast: Data-driven projections of market size and growth patterns over a defined forecast period. This section incorporates historical trends, current market conditions, and quantitative analysis to illustrate expected future developments.

Regional Analysis: A comprehensive review of market performance across major geographic regions, identifying high-growth areas and regional trends to better understand localized market opportunities.

Emerging Trends and Opportunities: Identification of significant market trends, technological advancements, and new investment opportunities. This section highlights potential growth areas and future industry developments.

Customization Options: We offer flexible customization services to tailor reports according to specific client requirements. This may include additional segmentation, country-level analysis, competitor profiling, customized data points, or focused insights on particular market segments to better support strategic decision-making.

MARKET SEGMENTATION

By Offering

• Hardware
• Software
• Services

By Deployment Mode

• Cloud
• On-Premises

By Enterprise Size

• SMEs
• Large Enterprises

By End-User

• Life and Health Insurance
• Property and Casualty Insurance

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision

COMPANIES PROFILED

• IBM Corporation, Microsoft Corporation, SAP SE, OpenText Corporation, Oracle Corporation, Guidewire Software Inc., SAS Institute Inc., Salesforce Inc., Pegasystems Inc., Applied Systems Inc., Cape Analytics Inc., Shift Technology SA, Tractable Ltd., Lemonade Inc., Ping An Insurance (Group) Company of China

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL AI IN INSURANCE MARKET: BY OFFERING 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Offering
• 4.2. Hardware Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Software Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.4. Services Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL AI IN INSURANCE MARKET: BY DEPLOYMENT MODE 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Deployment Mode
• 5.2. Cloud Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. On-Premises Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL AI IN INSURANCE MARKET: BY ENTERPRISE SIZE 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast Enterprise Size
• 6.2. SMEs Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Large Enterprises Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL AI IN INSURANCE MARKET: BY END-USER 2022-2034 (USD MN)

• 7.1. Market Analysis, Insights and Forecast End-user
• 7.2. Life and Health Insurance Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.3. Property and Casualty Insurance Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL AI IN INSURANCE MARKET: BY TECHNOLOGY 2022-2034 (USD MN)

• 8.1. Market Analysis, Insights and Forecast Technology
• 8.2. Machine Learning Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 8.3. Natural Language Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 8.4. Computer Vision Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 9. GLOBAL AI IN INSURANCE MARKET: BY REGION 2022-2034 (USD MN)

• 9.1. Regional Outlook
• 9.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.2.1 By Offering
  • 9.2.2 By Deployment Mode
  • 9.2.3 By Enterprise Size
  • 9.2.4 By End-user
  • 9.2.5 By Technology
  • 9.2.6 United States
  • 9.2.7 Canada
  • 9.2.8 Mexico
• 9.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.3.1 By Offering
  • 9.3.2 By Deployment Mode
  • 9.3.3 By Enterprise Size
  • 9.3.4 By End-user
  • 9.3.5 By Technology
  • 9.3.6 United Kingdom
  • 9.3.7 France
  • 9.3.8 Germany
  • 9.3.9 Italy
  • 9.3.10 Spain
  • 9.3.11 Russia
  • 9.3.12 Rest Of Europe
• 9.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.4.1 By Offering
  • 9.4.2 By Deployment Mode
  • 9.4.3 By Enterprise Size
  • 9.4.4 By End-user
  • 9.4.5 By Technology
  • 9.4.6 China
  • 9.4.7 Japan
  • 9.4.8 South Korea
  • 9.4.9 India
  • 9.4.10 Australia
  • 9.4.11 South East Asia
  • 9.4.12 Rest Of Asia Pacific
• 9.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.5.1 By Offering
  • 9.5.2 By Deployment Mode
  • 9.5.3 By Enterprise Size
  • 9.5.4 By End-user
  • 9.5.5 By Technology
  • 9.5.6 Brazil
  • 9.5.7 Argentina
  • 9.5.8 Peru
  • 9.5.9 Chile
  • 9.5.10 Rest of Latin America
• 9.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.6.1 By Offering
  • 9.6.2 By Deployment Mode
  • 9.6.3 By Enterprise Size
  • 9.6.4 By End-user
  • 9.6.5 By Technology
  • 9.6.6 Saudi Arabia
  • 9.6.7 UAE
  • 9.6.8 Israel
  • 9.6.9 South Africa
  • 9.6.10 Rest of the Middle East And Africa

Chapter 10. COMPETITIVE LANDSCAPE

• 10.1. Recent Developments
• 10.2. Company Categorization
• 10.3. Supply Chain & Channel Partners (based on availability)
• 10.4. Market Share & Positioning Analysis (based on availability)
• 10.5. Vendor Landscape (based on availability)
• 10.6. Strategy Mapping

Chapter 11. COMPANY PROFILES OF GLOBAL AI IN INSURANCE INDUSTRY

• 11.1. Top Companies Market Share Analysis
• 11.2. Company Profiles
  • 11.2.1 IBM Corporation
  • 11.2.2 Microsoft Corporation
  • 11.2.3 SAP SE
  • 11.2.4 OpenText Corporation
  • 11.2.5 Oracle Corporation
  • 11.2.6 Guidewire Software Inc
  • 11.2.7 SAS Institute Inc
  • 11.2.8 Salesforce Inc
  • 11.2.9 Pegasystems Inc
  • 11.2.10 Applied Systems Inc
  • 11.2.11 Cape Analytics Inc
  • 11.2.12 Shift Technology SA
  • 11.2.13 Tractable Ltd
  • 11.2.14 Lemonade Inc
  • 11.2.15 Ping An Insurance (Group) Company Of China