ID: MRFR/ICT/6993-HCR | February 2021 | Region: Global | 111 pages
Machine learning and deep learning algorithms aid in the development of intelligent, automated applications such as healthcare diagnostics, predictive maintenance, customer service, automated data centers, self-driving automobiles, and smart homes. The growing demand to provide tailored insurance services, as well as the growing need to automate the operational process, are driving the expansion of AI in insurance market share. When compared to people, AI technologies are capable of managing large amounts of client and company data as well as diverse jobs more quickly and correctly, allowing insurance experts to focus on more complicated and high-value operations. With the aid of technologies such as NLP and computer vision, AI is becoming competent at identifying faces, pictures, and spoken language, providing an intuitive experience. Furthermore, the growing usage of IoT technology is projected to drive market development. The adoption of IoT is projected to increase the amount and pace of data creation, driving the need to automate the process of providing actionable insights utilizing advanced machine learning and deep learning algorithms.
This report contains all the information on the global AI in insurance market trends and its strengths. The report also contains the culmination of dynamics, segmentation, key players, regional analysis, and other important factors. And a detailed analysis of the artificial intelligence (AI) in insurance market analysis and forecast for 2025 is also included in the report.
AI in Insurance Market Covid 19 Analysis:
Due to the extreme pandemic's compulsory work-from-home (WFH) policy, the COVID-19 outbreak is projected to promote AI in insurance market growth in next-generation tech areas like artificial intelligence. For example, LogMeIn, Inc., a U.S.-based provider of Software as a Service (SaaS) and cloud-based client interaction, remote connection, and collaboration services, has seen a large spike in new sign-ups across its entire product range as a result of the epidemic. In addition, IT businesses are expanding their product offerings and services to make them more widely available throughout the world.
The growing use of digital technology to automate company operations and improve customer experience is propelling AI in insurance market growth expansion.
Advancements in machine learning and deep learning algorithms are seen favorably by the artificial intelligence (AI) in insurance market.
Blockchains and big data analytics are likely to have the greatest impact on AI in insurance market sales.
Cumulative Growth Analysis:
Artificial intelligence in the insurance market is spreading to a larger variety of countries at a quicker rate. Insurance firms such as Insurify, CCC, Lemonade, Zest Finance, Clear cover, and Fly reel have already begun to use AI technology in an insurance claim, payment, and recommendation processing. AI may alter an insurer's business model by increasing the speed with which activities can be completed via Robotic Process Automation (RPA). RPA aids in the reduction of repeated activities from decision-makers and the execution of more complicated actions.
Despite the fact that it is difficult to predict the full implementation of Artificial Intelligence (AI) in the Insurance Market and the replacement of specific actions with automated intelligent machines, market leaders are optimistic and confident about the benefits they can derive from its involvement. By 2035, artificial intelligence will enhance labor productivity by 30 to 35 percent in 11 Western developed countries and Japan. By 2035, economic growth is anticipated to have more than doubled. According to the current situation, AI-based goods will include insurance coverage for self-driving vehicles, smart sensors and factories, and cybercrime damages.
Furthermore, AI will be used to improve critical insurance operations such as claims processing, asset management, risk assessment, and prevention. For example, the image processing function of Artificial Intelligence in Insurance may be used to estimate property damage. The same machine may be used to make an educated choice on smart system expenditures.
Value Chain Analysis:
According to the reports, the worldwide AI in insurance market has been divided into components, technologies, deployment, applications, sectors, and regions. The market has been divided into three components: hardware, software, and services. The market has been divided into four technological segments: machine learning and deep learning, natural language processing (NLP), machine vision, and robotic automation. The AI in insurance market has been divided into two segments based on deployment: on-cloud and on-premise. The industry has been divided into applications such as claims processing, risk management and compliance, personalized recommendations, chatbots, and others. The AI in insurance market has been divided into sectors such as life insurance, health insurance, title insurance, vehicle insurance, and others. The market has been divided into five regions: North America, Europe, Asia-Pacific, the Middle East and Africa, and South America.
AI in Insurance Market Segmentation Overview:
The AI in insurance market is segmented on the basis of components, technologies, deployment, applications, sectors, and regions. The global AI in insurance market is expected to witness decent growth during the forecast period.
Based on the application, the AI in insurance market is segmented into claims processing, risk management and compliance, personalized recommendations, chatbots, and others.
Based on the propulsion types, the AI in insurance market is segmented into life insurance, health insurance, title insurance, vehicle insurance, and others.
AI in Insurance Market Regional Analysis:
According to the reports, the global AI in insurance market is divided into the United States, Canada, and Mexico in North America. Europe includes Germany, the United Kingdom, France, Spain, Norway, the Benelux countries, and Italy. In Asia-Pacific, there are China, Japan, India, South Korea, Australia, Malaysia, Indonesia, and the Philippines. Saudi Arabia, Israel, Turkey, and South Africa are in the Middle East and Africa, whereas Brazil, Peru, Chile, and Argentina are in South America. Currently, North America dominates the worldwide AI in insurance industry. The region is a pioneer in new technology and a centre for numerous AI solution providers. The United States has the highest market share in the area, owing to a highly trained workforce in companies and research and development skills targeted at creating AI technologies to improve the quality of the insurance process. Europe is anticipated to have a significant increase in the worldwide AI in the insurance industry, behind North America in terms of market share. The growing use of digital technology to automate company operations and improve customer experience is propelling market expansion in Europe.
During the projection period, Asia-Pacific is expected to be the fastest-growing region. Government measures to encourage digitization, as well as increased investments in sophisticated technologies such as AI and IoT, are driving higher demand for AI in insurance market. The global AI in insurance market in the Middle East and Africa, as well as South America, is expected to grow at a significant rate during the forecast period, owing to the increasing need to optimize the insurance process and offer personalized insurance services, which help companies preserve a competitive edge in the market.
The AI in insurance market is fragmented, and this trend will continue over the projection period. To enhance their market position, competitors must work on distinguishing their product offers through unique value propositions. Market suppliers must also capitalize on current growth opportunities in fast-growing areas while retaining their positions in sluggish parts.
AI in Insurance Market Players:
The following report comprises of –
Google LLC will deploy an AI-enabled chatbot for contact centers dubbed Rapid Response Virtual Agent in April 2020. This chatbot is designed to answer concerns that consumers may be having as a result of the COVID-19 outbreak via voice, chat, and other social media.
AI in Insurance Market Segments:
|Market Size||2027: Significant Value|
|Forecast Units||Value (USD Million)|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, and Trends|
|Segments Covered||by Component, by Technology, By Deployment|
|Geographies Covered||North America, Europe, Asia-Pacific, and Rest of the World (RoW)|
|Key Vendors||Microsoft Corporation (US), Amazon Web Services Inc. (US), IBM Corporation (US), Avaamo Inc (US), Cape Analytics LLC (US), Wipro Limited (India), ZhongAn (China), Acko General Insurance (India), Shift Technology (France), BIMA (UK), Quantemplate (US), Zurich Insurance Group (Switzerland), Lemonade (US), Trov (Japan), and Slice (US).|
|Key Market Opportunities||The market seeks opportunities from advancements in machine learning and deep learning algorithms.|
|Key Market Drivers||Increasing adoption of digital technologies to automate business processes and enhance customer experience is driving the market growth in Europe.|
Frequently Asked Questions (FAQ) :
Rising demand for personalized insurance services to spur the growth of the market in the coming years.
The different technology based segments of the market are machine learning and deep learning, machine vision, natural language processing (NLP), and robotic automation.
The different regional segments profiled are North America, Asia-Pacific, Europe, the Middle East and Africa, and South America.
Based on component, the segments covered are - software, hardware, and services.
The segments of the market, based on sector, are insurance, title insurance, auto insurance, health insurance, and others.
The AI technologies are capable of handling huge volumes of customer and enterprise data and various tasks more quickly and accurately as compared to humans, which allows the insurance professionals to focus more on complex and high-value activities
Machine learning and deep learning algorithms help to drive smart, automated applications such as healthcare diagnosis, predictive maintenance, customer service, automated data centers, self-driving cars, and smart homes.