Generative AI in Insurance Market Size predicted to reach a 34.0% CAGR during the forecast period for 2025-2034.
A generative AI in the insurance sector is the application of powerful machine learning models to boost efficiency and accuracy in decision-making. This is essential for producing synthetic data, personalized products, and recommendations. Two key factors driving the industry ahead are the need for more efficient operations and the growing demand for personalized experiences. Responding to client demand for tailored insurance solutions, more and more insurers rely on AI technology to deliver specific suggestions and packages. Furthermore, modernization and international trade agreements might open new prospects for businesses worldwide, which can further promote market expansion. In addition, the market is anticipated to be propelled by increased government investments in research and development to optimize production & services processes.
However, the market growth is hindered by obstacles such as data privacy worries, expensive implementation expenses, a shortage of trained AI experts, problems with regulation and compliance, and the difficulty of incorporating AI into preexisting systems. Several variables can hinder adoption in this market. Global markets expanded during the coming years due to technological developments, widespread adoption of digital platforms, and the ever-increasing desire among consumers for novel goods and services.
The generative AI in the insurance market is segmented based on application and end-user. Based on application, the market is segmented into underwriting automation, risk assessment and management, fraud detection, customer service and engagement, and claim processing. By end-user, the market is segmented into insurance carriers, brokers and agents, and third-party administrators.
The underwriting automation generative AI in the insurance market is expected to hold a major global market share in 2023. Automating processes like risk evaluation, policy costs, and qualification decisions is made possible by generative AI, which allows insurers to make faster and more accurate decisions. Underwriting automation is the most lucrative market area because it allows insurers to optimize underwriting procedures, decrease human actions, and increase overall efficiency through sophisticated machine-learning models and the industry's overall market growth.
The insurance carriers segment is projected to grow rapidly in the global generative AI in the insurance market because better risk assessment models, faster claims processing, and customized insurance policies are becoming increasingly important. Carriers may improve their decision-making, fraud detection, and customer service by leveraging massive volumes of data with the help of generative AI. This boosts their efficiency and competitiveness in the market, especially in countries like the US, Germany, the UK, China, and India.
The North American generative AI in the insurance market is expected to register the highest market share in revenue in the near future. This can be attributed to the fact that for several reasons, including a highly developed healthcare IT infrastructure, increased spending by market participants, and supportive government programs. In addition, Asia Pacific is projected to grow rapidly in the insurance market's global artificial intelligence because of the growing funding for cutting-edge research and development in this area and growth in the middle class, which drives up demand for insurance. Insurance companies are increasingly turning to generative AI due to technological developments, and the trend toward digitalization will boost the market's growth.
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Report Attribute |
Specifications |
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Growth Rate CAGR |
CAGR of 34.0% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Application, By End-user, By Region |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
Microsoft Corporation, Amazon Web Services Inc., IBM Corporation, Avaamo Inc, Cape Analytics LLC, MetLife, Prudential Financial, Wipro Limited, ZhongAn, Acko General Insurance and Other Prominent Players |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Generative AI in the Insurance Market Snapshot
Chapter 4. Global Generative AI in the Insurance Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Application Estimates & Trend Analysis
5.1. by Application & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Application:
5.2.1. Underwriting Automation
5.2.2. Risk Assessment and Management
5.2.3. Fraud Detection
5.2.4. Customer Service and Engagement
5.2.5. Claim Processing
Chapter 6. Market Segmentation 2: by End-users Estimates & Trend Analysis
6.1. by End-users & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End-users:
6.2.1. Insurance Carriers
6.2.2. Brokers and Agents
6.2.3. Third-Party Administrators
Chapter 7. Generative AI in the Insurance Market Segmentation 3: Regional Estimates & Trend Analysis
7.1. North America
7.1.1. North America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
7.1.2. North America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2021-2034
7.1.3. North America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
7.2. Europe
7.2.1. Europe Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
7.2.2. Europe Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2021-2034
7.2.3. Europe Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
7.3. Asia Pacific
7.3.1. Asia Pacific Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
7.3.2. Asia Pacific Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2021-2034
7.3.3. Asia Pacific Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
7.4. Latin America
7.4.1. Latin America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
7.4.2. Latin America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2021-2034
7.4.3. Latin America Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
7.5. Middle East & Africa
7.5.1. Middle East & Africa Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
7.5.2. Middle East & Africa Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2021-2034
7.5.3. Middle East & Africa Generative AI in the Insurance Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
Chapter 8. Competitive Landscape
8.1. Major Mergers and Acquisitions/Strategic Alliances
8.2. Company Profiles
8.2.1. Microsoft Corporation
8.2.2. Amazon Web Services Inc.
8.2.3. IBM Corporation
8.2.4. Avaamo Inc
8.2.5. Cape Analytics LLC
8.2.6. MetLife
8.2.7. Prudential Financial
8.2.8. Wipro Limited
8.2.9. ZhongAn
8.2.10. Acko General Insurance
8.2.11. Other Prominent Players
Generative AI in the Insurance Market By Application
Generative AI in the Insurance Market By End-User
Generative AI in the Insurance Market By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
Rest of the Middle East and Africa
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
