Top AI use & applications in the insurance industry 2025

This article is a submission by Fusion Business Solution (P) Ltd.-FBSPL. Fusion Business Solution (P) Ltd. (FBSPL) is a Udaipur, India-based company providing Business Process Outsourcing, management, consulting, and IT services, with operations in New York, USA.

One of the biggest hopes for the future of AI in reinsurance and insurance is that it will help them develop more accurate pricing and coverage. 

That is a fine objective for the long term but let us focus on how AI is making a real difference today and what it could bring to the insurance value chain shortly.  

“According to a Forbes article, AI in the insurance industry has already boosted operational efficiency by 60%. It’s also raised claims accuracy by a staggering 99.99% and improved customer experience by 95%.”  

Additionally, it is estimated that AI in insurance will increase tremendously to reach a value of USD 35.77 billion by 2030, growing at an annual growth rate of 33.06%.  

Let’s discover more about AI insurance applications, their manifold data management benefits, practical examples, and the industry’s most recent trends.  

So, how is AI shaping the future of the insurance industry?  

• Insurance used to involve complex paperwork and delays, but modern technology now streamlines the process through automation. This builds trust, cuts cost, reduces fraud, and boosts business efficiency.  

Insurance and customers are in a win-win situation for both sides. Why?  

• Thanks to new technology in the insurance world, insurers can better evaluate risks, spot fraud early, and minimize mistakes.  
• Customer service has improved, making claims easier and faster to process.  
• The underwriting process is becoming smoother, and there is less need for manual work.  
• Using modern data and insights, underwriters can better assess risks and offer more accurate, customized premiums.  

Also, the latest insurance technology has made it easier for an applicant to contact the insurance provider directly, speeding up the process.  

8 ways AI is changing the insurance game  

This range in the applicability of AI by insurance companies involves everything from risk assessment and fraud detection to even underwriting policies. 

A very simple principle drives the use of AI insurance applications: accelerating the pace, accuracy, and overall customer experience.  

1. Fraud detection 

Fraud is a major challenge for the insurance industry, leading to significant financial losses each year. Traditional methods often fall short in detecting complex or coordinated fraud. 

That’s where AI and machine learning make a difference. They help detect fraud early by analyzing large datasets, including social media, to identify suspicious patterns. 

This enables insurers to detect and stop fraudulent activity before payouts are made. The result? Faster fraud detection reduces financial risk and substantial cost savings. 

With AI, insurers can stay proactive and better protect their bottom line. 

2. Claims processing 

AI streamlines the insurance claims process by automating tasks like data entry, document scanning, and damage assessment. 

This speeds up claims handling, reduces errors, and cuts costs. Additionally, AI helps detect suspicious claims, preventing unnecessary payouts.  

3. Improving customer experience 

In the competitive insurance industry, excellent customer service is essential. AI-powered chatbots and virtual assistants provide 24/7 support, handling queries and claims efficiently. 

Additionally, AI analyzes feedback to help improve service quality over time.  

4. Underwriting 

Insurance underwriting assesses the risk of insuring a customer and determines the appropriate pricing. AI enhances this process by analyzing large datasets to make more accurate claim predictions. 

This helps insurers set better prices and avoid financial losses from underpriced policies.  

5. Risk management 

AI simplifies risk management in insurance by analyzing data from various sources to detect early risk indicators. 

Instead of relying solely on historical data, AI analyzes information from diverse sources—such as customer profiles, real-time events, and market trends—to detect early risk indicators. It helps predict potential impacts, enabling smarter decisions on policy pricing and claims. 

Ultimately, this leads to better risk assessment, more balanced portfolios, and a significant reduction in financial losses. 

6. Predictive maintenance 

Predictive maintenance anticipates equipment failures before they occur. By using AI to track performance and usage data, insurers can forecast potential issues. 

This allows for early maintenance, reducing costly breakdowns, and insurance claims.  

7. Disaster response planning 

AI is revolutionizing insurance by improving disaster response, risk assessment, and fraud detection through data-driven predictions and automation. It helps insurers optimize resources, personalize customer experiences, and streamline operations. 

Over 2,000 companies now use generative AI, highlighting its growing role in shaping a more efficient, customer-focused industry.  

8. Personalized insurance products 

AI empowers insurers to deliver highly personalized insurance products by analyzing individual customer data, preferences, and behavior. 

From driving habits and lifestyle choices to purchase history and digital interactions, AI processes it all to offer tailored policy recommendations and dynamic pricing. 

Customers receive quotes and coverage options that reflect their actual risk profiles and needs—rather than generic, one-size-fits-all plans. This level of personalization not only improves the customer experience but also builds trust and loyalty. 

For insurers, it means higher retention rates, better-targeted offerings, and a stronger competitive edge in a crowded market. 

How AI is making a difference in insurance  

Here is a summarized version of the content in bullet points:  

• Efficiency & customer satisfaction: Generative AI improves insurance processes and enhances customer experience.  
• Data insights: Analyzes large volumes of structured and unstructured data to uncover insights, such as new customer segments and product comparisons.  
• Hyper-personalization: Enables creation of personalized services that boost customer engagement.  
• Automation of routine tasks: Handles administrative work like data entry and email sorting, allowing staff to focus on higher-value tasks like quoting and claims.  
• Risk detection & fraud prevention: Identifies patterns and anomalies to assess risk and detect fraud, improving underwriting accuracy, and reducing losses.  
• Improved customer service: Supports agents with insight and automates basic tasks to deliver faster, more personalized responses.  

The next stages of AI 

AI is revolutionizing the insurance industry trends and making it much more efficient for firms to conduct business with reduced operational costs and improved customer service. AI and machine learning technologies form the backbone for fraud detection, claims handling, customer service, underwriting, and predicting potential risks. 

With emerging sophistication in AI technologies, an insurer would adopt these technologies to perform various services more effectively, ensuring lower costs and higher profitability.