Imagine getting your claims processed in a few minutes, similar to the ease of making UPI transactions without any hassle. That’s what AI insurance coverage is doing today. AI is changing the insurance industry. It’s not just about its strong abilities. It’s also helping insurers boost customer service easily. A key aspect of growth in 2025. Given the rapid adoption of AI in insurance, companies will continue to grow its applications. Experts project that by 2032, its value will reach approximately $4.59 billion, and they expect it to rise sharply to nearly $80 billion.
Let’s dive deeper to understand the positive wave of change that AI has brought in the insurance claims handling and coverage processes.
How can AI be Used in Claims Handling?
It’s time to face the most challenging question: How can AI process faster claims while maintaining accuracy?
Enterprise-level AI will undergo multiple testing phases to offer accurate results. It streamlines operations by automating tedious tasks, which frees agents to focus on providing personalized customer service. This is in claims processing where automation reduces the risk of errors and eliminates operational bottlenecks by consolidating data from diverse sources into a unified platform.
Hop on to the next section to decode some of the keyways that AI will be transforming the claims processing process in the near future.
How Claims Handling will be Changing Shortly- The Top 3 AI Insurance Claims Trends
AI is unlocking the automated workhorses and enhancing the efficiency of the claims handling processes. With the accuracy that it’s introduced in the operational processes, insurers are able to curb up to 50% of claims leakage.
Here’s a closer look at how AI can tap into the three crucial processes in claims handling and transform the claims handling process:
Claims Filing
This is the most important step in the claims processing process. This process contains a lot of information that the claim handlers need to process during the First Notice of Loss (FNOL). Claim handlers must sift through a huge pile of claims information and perform tasks such as extracting key details, entering information, and cross-referencing with policy records in a conventional manner.
Can you imagine the amount of time that this entire process takes?
AI adds a twist to the FNOL process. It uses its strong abilities to process large amounts of claims documents. It extracts key data, summarizes the content, and flags items that may need closer inspection. It can detect any potential issues that might require extra attention. With AI in the claim filing process, insurers can improve 95% of claims accuracy.
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Policy Checking
Another one of the tedious processes in the claims management process is policy checking. Policy checking requires claim handlers to conduct a thorough cross-reference of each claim with the specific policy details. This review process takes a lot of time and effort. It is important for getting accurate claims outcomes. However, it slows down the process for policyholders.
Did we paint an exhausting picture of a claim handler in your mind? Time to flip it with AI. AI streamlines this entire process and simplifies policy checking, reducing the time and effort required. This is one of the most hidden processes in the entire claims management process where AI can unlock improving customer satisfaction much faster.
With AI, claim handlers can verify the policy terms, limits, and exclusions in a timely manner while also streamlining the tedious policy-checking process. AI takes care of routine policy checks. This gives claim handlers more time to focus on complex cases instead of repetitive manual tasks.
Intake Processing
Claim handlers often deal with delays. This happens because claim documents can be messy or unclear. Such issues slow down progress. Claim handlers sift through these documents to identify relevant information and ignore any outdated or unnecessary data, a process that often becomes tedious and leads to errors.
AI can take over intake processing steps using specialized models such as Strikethrough recognition and multi-document recognition. Strikethrough recognition makes sure only relevant data goes to the handlers. This helps avoid clutter. This ensures more accurate claims processing from the start.
In a similar manner, a multi-document recognition model separates multiple receipts or invoices in a single image, saving a lot of time for the claim handler. By leveraging AI in these repetitive tasks, claim handlers can accelerate the review process and enhance customer experience.
Looking Beyond: Spinning Around the Claim Handler’s Role with AI
AI is playing a pivotal role in turning around the claim handler’s role while shifting their focus from paperwork to direct customer interaction and expert guidance. This is especially true during complex events such as natural disasters where AI manages initial data. This evolution is enhancing the efficiency of the insurer to deliver more personalized and customer-centric services.
