Generative AI in Insurance Market Size, Share, Growth, Report 2025 to 2034

Generative AI in Insurance Market Size and Growth Factors 2025 to 2034

The global generative AI in insurance market size is calculated at USD 1.10 billion in 2025 and is anticipated to reach around USD 10.94 billion by 2034, expanding at a strong compound annual growth rate (CAGR) of 29.11% over the forecast period 2025 to 2034. The generative AI in insurance market is gaining momentum with insurers under pressure to modernize their operations, improve customer experience, and mitigate risks as the risk environment evolves. As claims get more complex, the regulations become stricter and customers seek individualized policies, Generative AI provides a transformative solution. Automating claims processing with the use of synthetic data models to scenario simulation to enhance fraud detection, among other processes, insurers are undergoing the implementation of AI-driven systems to enhance efficiency and accuracy. The technology as well enables the insurers to develop dynamic pricing models, custom coverage, and simplify underwriting, which will ultimately result in a quicker, customer-centric service.

One of the main facilitators of such growth is the transition of the industry to predictive and preventive insurance, where Generative AI has become an important factor in predicting risks in terms of which losses can be minimized at an early stage. Be it health, auto, life, or property insurance, Generative AI can assist carriers to create sophisticated risk models, simulate catastrophes, and deliver highly personalized customer experiences. In addition, insurers are using AI-powered markets to drive resiliency into portfolios by better evaluating climate-related risks and putting sustainability targets in place. It makes Generative AI anything more than a tool to drive operational efficiency but also a key to innovation and future competitiveness in the international insurance market.

Generative AI in Insurance Market Report Highlights

• By Region, North America dominates with 44% share due to advanced digital infrastructure, a strong insurtech ecosystem, and early AI adoption by leading insurers. The region’s regulatory push and investment in AI innovation further fuel its leadership in this market.
• By Component, solutions segment dominate with a 65.7% share, as insurers increasingly adopt AI-driven tools for underwriting, risk modeling, and claims automation. These solutions provide immediate cost savings, enhance decision-making, and improve efficiency, making them the preferred choice over services.
• By Application, claims processing segment leads with 25.7% share since generative AI drastically reduces processing times, detects fraud more effectively, and minimizes errors. Its direct impact on profitability and customer satisfaction makes it the most significant application area for insurers.
• By Deployment Mode, cloud deployment segment holds the largest share at 73.5% because of its scalability, flexibility, and cost-effectiveness. Insurers prefer cloud platforms for deploying and updating AI models quickly while ensuring better integration across multiple operations.
• By End User, insurance companies hold 72.4% share as the main adopters of generative AI, using it to streamline core processes like pricing, fraud detection, claims, and personalized customer engagement. Their direct need to enhance efficiency, cut costs, and stay competitive makes them the largest end-user group over brokers and intermediaries.
• By Enterprise Size, large enterprises capture 69.2% of the market as they have higher budgets, advanced IT ecosystems, and the ability to scale AI adoption across underwriting, claims, and customer services. Their strategic focus on digital transformation drives stronger adoption compared to SMEs.

Generative AI in Insurance Market Trends

• AI in Claims Processing: Generative AI is also becoming a tool of automating claim processing and eliminating physical activity in the management of disaster recovery support. It also assists the insurance companies make inferences on vast amounts of information including pictures, satellite signals, and accident reports in a fraction of an hour. This transition is especially beneficial in the case of the large-scale natural disasters where assessments have to be performed manually, which takes lots of time. As an example, in May 2025, Suncorp implemented AI-supported satellite imagery systems that were used to review flooding and hail damages claims without delay. This meant that the company could settle claims more effectively and in addition it was able to increase the satisfaction of the customer. The trend is a major shift towards the agility of operations in tense situations.
• AI in Customer Communication: Another emerging trend lies on implementing Generative AI to streamline and make customer communication in insurance personalized. AI is involved in writing clear and simple messages that are empathetic to the policyholders as opposed to confusing the policyholders with technical terms and jargon. This will allow customers to have deeper knowledge concerning the coverage, exclusions, and claims update statuses. As an example, in June 2025, Allstate deployed a communication tool that is based on GPT and is used to create more than 50,000 customer messages each day. The system also introduced order replacing complicated terms with simplified ones with more transparency. The trend demonstrates the way insurance companies increase trust and engagement with AI-driven communications.

Report Scope

Generative AI in Insurance Market Dynamics

Market Drivers

• Operational Efficiency: One of the key reasons of changing to generative AI in insurance is the necessity to automate work processes and reduce routine work. Insurance activities particularly underwriting and claims are highly documented and analysed, thus AI has become a handy tool. Automating these processes will save time and help to minimize human error on the part of insurers. In June 2025, AIG invested in Anthropic and Palantir to put AI in underwriting and claims processes. The integration reduced the delay of the processing and decreased risk evaluation significantly. This improvement in efficiency explains why AI is gaining a lot of momentum in the sector.
• Workforce productivity: The other potent force is that generative AI can enhance the productivity of the workforce without adding the number of workers employed. Amid the pressure on insurers to scale up services at the same time as managing costs, AI is an effective solution to augment human capabilities. AI assistants support employees doing all the repetitive data work so that those employees can work on more value-added tasks. A case in point is QBE in August 2025 who implemented AI-based underwriting assistants that increased the productivity of its staff by almost 50 percent. The program enabled the company to undertake growth without a massive employment. This demonstrates the ability of AI to optimize workforce and efficiency.

Market Restraints

• Data Privacy and Security: The issue of data security and your privacy is a key limiting factor to the uptake of Generative AI. Insurance companies work with a lot of sensitive financial and medical information, so it is very dangerous in case of its leak or misuse. Regulatory demands as GDPR contribute to the pressure, restricting the unimpeded implementation of AI systems. A study by SkyQuest in 2025 found that all insurers are also cautious about the broad use of Generative AI because of their compliance requirements. Mistreating data might lead to fines, reputational and consumer loss. Privacy is thus one of the major problems of AI implementation.
• High cost of implementation: The other limitation is that the systems of previously operated insurance are complex and costly in terms of integrating AI. The IT infrastructure at many insurers remains antique and it is not easy to transition into newer sets of technology which enable more use of AI. Moving to AI systems needs high investments in terms of hardware and software development as well as the training of staff. According to the publication of Global Trade Magazine in 2025, some of the smaller insurers are finding these costs cumbersome, and are delaying the adoption of AI. The cost barrier poses an uneven playing field such that only large insurers are able to scale AI with velocities. This puts stress on financial means which has limited wider usage.

Market Challenges

• Opacity: A major obstacle with generative AI is that the decision-making process is hard to explain, and they are considered to be black boxed. This is an issue in insurance where regulators want underwriting and the handling of claims to be seen to see light. Customers also want some clarity on why a claim is not paid or a premium is priced. In June 2025, Forbes reported that insurers were struggling to explain regulatory scrutiny in AI driven decision making. Unless insurers are able to explain their data-driven decisions, their operations will end up in compliance problems and customer distrust. This causes transparency to be one of the biggest challenges when it comes to AI adoption.
• Skills Gap: Insufficient talent in AI and data science is another big issue. Generative AI needs to be built, trained and maintained by specialists that a large percentage of insurance companies currently do not have. This leads to companies having to rely on vendors outside the companies which stagnates the development of internal capabilities. In the International Insurance in 2025 report, it was observed that this skills shortage is hampering the ability to scale AI initiatives by insurers. Insurers are at a disadvantage of experiencing more errors and failed implementations without rallying skilled staff. Such talent shortage is one of the bottlenecks in the long term AI adoption in the industry.

Market Opportunities

• AI liability insurance products: Generative AI is inventing totally new insurance faculties that cover risks associated with AI in itself. The risks that businesses face when using chatbots or AI models include misinformation, violating compliance and suffering reputational damage. Insurers are reacting by providing liability covers on the errs of AI. In May 2025 Lloyd,s with Armilla has introduced policies to cover the losses of financial and reputational damages through chatbot errors. This has opened an additional income base to the insurers in the booming AI economy. Commodities such as these illustrate that AI is not only transforming insurance, but it is generating a new insurable risk as well.
• In a Liquidity Breakthrough: Reduce the Rate of Health Claim Resolutions: The other potential opening is applying Generative AI to healthcare claims to make them easier and faster. Claim denials are an immense problem of both the patients and the providers, and AI could assist in writing successful appeal letters. In June 2025, Counterforce Health created appeal correspondence to rejected health insurance claims through the utilization of AI. This method resulted in about ~70 percent reversal rates, which boosted patient mental satisfaction and confidence in the procedure. The case shows that AI might be directly beneficial to customers and eliminate the administrative load. Healthcare insurers are now taking the view that AI is an efficiency device as well as a customer care tool.

Generative AI in the Insurance Market Regional Analysis

The generative AI in insurance Market is segmented into several key regions: North America, Europe, Asia-Pacific, and LAMEA (Latin America, Middle East, and Africa). Here’s an in-depth look at each region.

North America is leading the market

• The North America generative AI in insurance market size was valued at USD 0.37 billion in 2024 and is expected to hit around USD 4.81 billion by 2034.

The use of generative AI in insurance, especially in the fields of claims and fraud protection, is most advanced in the North American region. In June 2024, Lemonade has further scaled its artificial intelligence-based claims platform, where claims are processed in minutes. This innovation is an indication of how seriously the region approaches elements of efficiency and customer-based services. American carriers are using AI to create customized risk analysis, predictive pricing and intelligent fraud detection. Similar development is also being witnessed when it comes to customer engagement solutions in Canada.

Europe hits significant growth

• The Europe generative AI in insurance market size was estimated at USD 0.20 billion in 2024 and is projected to surpass around USD 2.63 billion by 2034.

Europe pursues generative AI with a laudable degree of caution; innovation on the one hand but need a high level of compliance regulation on the other. In May 2024, Allianz SE in Germany has introduced a generative AI tool to provide a user with personalized policy recommendations, and it fully complies with the changes to AI Act the EU currently proposed. This indicates how Europe is determined to adopt the concept of responsible AI in regulated sectors. Insurers in France, the UK and Spain are evaluating the use of AI in underwriting and claims at the same time being transparent and explainable. There are regulatory sandboxes that promote limited innovation in the sector.

Generative AI in Insurance Market Share, By Region, 2024 (%)

Asia-Pacific is growing fastest

• The Asia-Pacific generative AI in insurance market size was accounted for USD 0.23billion in 2024 and is forecasted to record around USD 2.95 billion by 2034.

Asia-Pacific is fastest growing, owing to the large client bases and digital-first markets. In August 2024, the Chinese insurance conglomerate Ping An applied its AI-based underwriting technology to more policyholders to ramp up the pace of health risk profiles across its base of millions of policyholders. Insurers in India, Japan, and South Korea are also integrating generative AI to customer support, fraud, and dynamic price models. The competitive insurance arena in the region is spurring blistering innovation in AI.

LAMEA is slow-mover

• The LAMEA generative AI in insurance market was valued at USD 0.04 billion in 2024 and is anticipated to reach around USD 0.55 billion by 2034.

The Middle East & Africa is a slow-mover, with initiatives in this sector such as the Oman Insurance AI chatbot, which was launched in Dubai in March 2024 to facilitate claims and inquiries. In the UAE and South Africa, regulators are welcoming pilot projects in regulatory sandboxes, and insurers are attracting newer customers (those with young families) interested in more customized products. Just as the case in Asia and Pacific, Latin America is also leading in the application of AI, where Porto Seguro in Brazil has implemented the generative AI to its platform in July 2024 to support multilingual services.

Generative AI in Insurance Market Segmental Analysis

Component Analysis

Solutions: General AI in insurance Insurtech Solutions like workflow automation, policy generation, claims settlement, and fraud detection automation are examples. These systems powered with AI minimize time taken in processing and enhance satisfaction of the customer. In March 2024, Lemonade Insurance expanded its AI-enabled claims system and was able to settle simple claims instantly. This illustrated how solutions can lead to direct increase in efficiency The implementation of solutions is an indication of insurers expecting economies and quick responsiveness to their services.

Generative AI in Insurance Market Share, By Component, 2024 (%)

Services (Consulting, Integration, Training & Support): Services promote seamless implementation of AI, including integration, training and post-implantation support. Consulting can enable insurers to determine the avenues of AI-driven optimization. Accenture, in conjunction with various insurers, has since integrated AI-supports underwriting support tools in July of 2023. The collaborations also involved training of employees. This indicates the vitality of services to make AI implementation successful.

Application Analysis

Claims Processing: Generative AI can replace time-consuming manual work and automate documentation, and it enables predicting fraudulent claims. It assists insurers in clip-clopping down cases with more accuracy over a shorter time frame. In January 2024, Allstate introduced its automated claims adjusters with AI-assisted claims processing, which reduced their average time taken to be handled by quite some bit. This was evidence of the potential that AI will have on simplifying operations. Improved speeds create more customer confidence, as well as cost efficiency.

Underwriting & Risk Assessment: Involves using AI models to crunch through medical, financial and behavioral data to evaluate risks correctly. It also aids insurers to make policies more individual and minimize underwriting errors. In November 2023, Swiss Re has applied generative AI to underwriting life insurance to make faster decisions. This shows the essence of AI in high risk risky observation intensive decisions. A more intelligent underwriting may result in competitive advantage in the market.

Fraud Detection & Prevention: AI models will be able to identify anomalies in claims data, detecting fraudulent behavior with greater speed than man versus machine checks. Generative AI creates risk scenarios to test the fraud detection. In May 2024, AXA started using AI to detect fabricated injury claims, thus saving it millions of potential losses. This demonstrated the capability of AI to reduce fraud related costs. Fraud detection is another of the most powerful ROI opportunities that insurers have using AI.

Customer Support & Virtual Assistants: Customer Support – Customer Support policies, payments, claims information transacted by the use of generative AI via virtual assistants. They enhance engagement and workloads in call centres. In August 2023, Progressive Insurance implemented a chatbot powered by the conversational AI to be used by customers with questions. There were time savings as customers got real-time explanation of policies. This highlighted the position that AI has to play in enhancing customer experience.

Policy Generation & Personalization: AI can generate custom policies based on the behaviour of a user, demographics and their wealth. This customization improves customer loyalty/retention. In February 2024, Prudential launched Personalized health insurance plans through an AI. Such adaptive policies were in the spotlight due to relevance and flexibility. Artificial intelligence assists in personalization of the insurers to cover a variety of market segments successfully.

Deployment Mode Analysis

On-Premise: On-premise deployment focuses on installing the AI system in the vicinity of the insurer in order to have greater control over it and to ensure data security. This applies well to companies with stern compliance requirements. MetLife implemented on-premise AI to create risk-related models in October 2023 to work in accordance with local data regulations. This also gave sensitive financial data a way to remain in-house. On-premise is important to insurers that deal with sensitive data.

Generative AI in Insurance Market Share, By Deployment Mode, 2024 (%)

Cloud deployment:  Cloud deployment enables softer scalable insurance to access AI powered tools. It lowers infrastructure expenses as in real-time updates are guaranteed. Liberty Mutual transitioned some of its claims processing AI over to cloud resources in June 2024 in order to scale more rapidly. The move enabled the smooth international operations in the world. The use of AI solutions in the Cloud reflects the increased need of insurers to be agile and cost-effective in the implementation of solutions.

End User Analysis

Life Insurance: Life insurance AI can assess the risks in the long-term, automate personalization of the policy, and validate claims. In September 2023, John Hancock introduced an artificially intelligent system that is intended to automate the application process of life insurance. This greatly minimised the approval time of applications Generative AI also aids the insurance companies in delivering faster and more precise life insurance covers.

Health Insurance: AI assists health insurance companies process claims, detect potential frauds and design personal health plans. In April 2024, Cigna used AI to automate and customize claims and wellness benefits. Customers had a smoother reimbursement process with responses on regular progress. This showed the increasing importance of AI in regards to healthcare-oriented insurance.

Auto Insurance: Generative AI helps to deal with accident assessment, fraud detection, and automated claims in auto insurance. In December 2023, GEICO has been experimenting with AI-enhanced accident damage inspection through image analysis. This minimization of disputes and settlement times. Using AI, insurers of auto have also managed to eliminate delays and enhance customer confidence.

Property and Casualty Insurance: In property and casualty insurance, AI helps predict risk caused by natural disasters and automates the policy processing. In July 2024, Farmers Insurance used AI to determine wildfire risks in California. This resulted in more rapid changes in policy, and more accurate coverage. AI will make insurers manage risks better.

Travel Insurance: Diligence to travel insurance using predictive processing and real-time customer support. In January 2024, the Allianz company launched an AI-powered chatbot that handles the delayed flight claims in a few minutes. The customers were refunded faster with minimum documentation. This indicates that AI is a contributor to dynamic and short-term insurance products.

Enterprise Size Analysis

Large Enterprises: Large insurance companies using generative AI to process massive amounts of claims, customer enquiries and frauds. They make enterprise level customization and integration their priority. In August 2023, AIA Group deployed AI in various regional offices underwriting and claims. This kept consistency and also minimized errors It is desirable to scale AI at a global level by large enterprises.

Generative AI in Insurance Market Share, By Enterprise Size, 2024 (%)

Small & Medium: Sized Enterprises (SMEs) SMEs make use of generative AI to achieve cost-effectiveness and efficiency in insurance management. Their AI tools enable them to compete with other large players without incurring high infrastructures cost. In March 2024, a small insurer, based in the U.S. incorporated the technology of AI chatbots with customers who were to process a few of their claims. This assisted the SMEs to provide 24/7 service similar to those of bigger insurers. AI helps SMEs in gaining a much-needed competitive advantage.

Generative AI in Insurance Market Top Companies

• Microsoft Corporation
• Amazon Web Services Inc.
• IBM Corporation
• Avaamo Inc
• Cape Analytics LLC
• MetLife
• Prudential Financial
• Wipro Limited
• ZhongAn
• Acko General Insurance

Recent Developments

• In June 2023, Generative AI is rapidly transforming the insurance industry by enabling advancements such as smarter content creation, improved semantic search, and efficient code generation. Microsoft’s integration of AI models like GPT-4 with Azure OpenAI Service empowers insurers to streamline operations in underwriting, claims management, and customer service while enhancing virtual assistants and broker support. The adoption of these tools promises greater productivity, better customer engagement, and faster insights, all underpinned by Microsoft’s commitment to responsible AI and enterprise-grade security.
• In November 2023, Wipro has partnered with NVIDIA to accelerate the adoption of generative AI in the healthcare and insurance sectors by integrating NVIDIA AI Enterprise software and AI platforms into Wipro's healthcare solutions. This collaboration aims to enhance member experiences, streamline claims, improve operational efficiency, and enable custom AI models for speech, translation, and business analytics, while also training Wipro engineers on cutting-edge AI frameworks to drive further digital transformation in the industry.

Market Segmentation

By Component

• Solutions
• Services
  
  • Consulting
  • Integration
  • Training & Support

By Deployment Mode

• On-Premise
• Cloud

By Enterprise Size

• Large Enterprises
• Small & Medium-Sized Enterprises (SMEs)

By Application

• Claims Processing
• Underwriting & Risk Assessment
• Fraud Detection & Prevention
• Customer Support & Virtual Assistants
• Policy Generation & Personalization

By End-User / Insurance Type

• Life Insurance
• Health Insurance
• Auto Insurance
• Property & Casualty Insurance
• Travel Insurance

By Region

• North America
• APAC
• Europe
• LAMEA