What’s the Real Value of Insurance Claims AI? It Depends

As a former claims supervisor with 18 years of carrier experience, I’m sure you can guess my response when asked about the value of claims AI: it depends. There are a wide range of AI types being used for claims analytics and an even wider gap in the quality of AI solutions available.

Let’s review key areas where AI can drive real improvement and bring value to your claims organization.

The Challenges Claims Professionals Face 

Today’s adjusters face a demanding set of responsibilities which require speed, precision, and sound judgment. One of the most persistent challenges is managing high claim volume while focusing on key performance indicators like cycle time reduction. Carriers place heavy emphasis on resolving claims efficiently and adjusters are expected to do so without compromising the accuracy or defensibility of their decisions. 

Some adjusters would even use a PTO day to pause new claim assignments and work their backlog to catch up.

In my years as a claims adjuster, specialist and supervisor, I experienced firsthand how clerical burdens, relentless volume, and rapidly evolving plaintiff tactics would strain the most experienced team members. Some adjusters would even use a PTO day to pause new claim assignments and work their backlog to catch up. This underscores the need for efficient, high-quality tools to support the adjuster's investigations, evaluations, and service requirements.

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Claim professionals must maintain high standards for file quality and compliance. This includes timely and thorough documentation of activity logs, diary entries, file notes, adherence to internal procedures, and regulatory requirements. Accurate liability and coverage determinations early in the claim lifecycle are critical as any errors can lead to increased litigation risk and financial exposure. 

Adjusters and specialists are responsible for controlling claim severity by setting appropriate reserves, identifying early resolution opportunities, and leveraging cost containment tools such as medical management and repair programs. The challenge lies in balancing all of these factors under significant time and workload pressure while prioritizing fairness, compliance, and technical excellence.

Rethinking Claims Processes and The Role of AI 

There are myriad challenges between implementing process improvements and employee change management dynamics at claims organizations. Maintaining the trust between AI solutions, insurers, and their fiduciary duties to customers continues to be a hot topic of debate. 

There has been a lot of resistance across the industry. Adoption of AI varies, with some departments prohibiting employee usage and others slowly embracing it. Not everyone is eager for change. They know their jobs, take pride in their efforts, and don’t see a need to fix what isn’t broken. 

AI adds value to claims processes and key performance indicators by reducing cycle time, increasing adjuster accuracy, and making workflows more efficient.

AI adds value to claims processes and key performance indicators by reducing cycle time, increasing adjuster accuracy, and making workflows more efficient. Adjusters have more time to focus on their high-impact work: comprehensive investigations, strategic evaluations, proactive communications, customer service, efficient claim resolutions.

Here are the areas where I think AI offers the most potential value for claims organizations:

• AI for Medical Record Reviews: Analyzing medical records is one of the most time-consuming and inefficient parts of the job. It’s also prone to inconsistency and errors. AI can streamline this process by automatically identifying and summarizing key information, removing duplicate pages, and surfacing the critical insights needed for liability decisions, injury evaluations, reserve rationales, and settlement reviews.
• AI for Demand Letter Analysis: Plaintiff attorneys are already using AI, and they’re using it to increase pressure by flooding carriers with conditional demands and tight response deadlines. AI can help level the playing field. The right tools can reduce the time spent reviewing complex demand packages, extract and organize key points, and support better, faster negotiation strategies. That means less time spent manually parsing documents, more time focused on strategic claim resolution.
• AI for Fraud Detection: Adjusters are expected to identify red flags and make timely SIU referrals, but spotting fraud amid a heavy caseload is challenging. AI can help detect patterns and anomalies that may indicate misrepresentation, inflated claims, or staged losses, flagging suspicious activity earlier and helping adjusters prioritize those files for deeper review.
• AI for Subrogation Opportunity Identification: Missed subrogation is a common source of leakage. AI can assist by scanning claim files for third-party involvement, liability indicators, or evidence of shared responsibility, surfacing recovery opportunities that might otherwise be overlooked.
• AI for Coverage Analysis: Understanding coverage applicability is foundational to every claim, but it’s not always straightforward. AI can assist by aligning claim facts with policy language, helping adjusters more quickly identify exclusions, limits, and applicable endorsements. This can reduce errors, speed up early determinations, and minimize unnecessary delays or disputes.

How DigitalOwl Earned My Trust—and Why I’m Helping Build What’s Next

It’s not a one-size-fits-all market, and not all vendors are created equal. It is critical to work with a partner who prioritizes trust, transparency, and compliance, and one that offers solutions trained specifically for P&C insurers.

It is critical to work with a partner who prioritizes trust, transparency, and compliance, and one that offers solutions trained specifically for P&C insurers.

Like many claims professionals, I had a healthy skepticism about AI tools and what they could realistically deliver. That skepticism remained until I started using DigitalOwl’s platform myself. Here’s what I found:

1. The AI is highly accurate and fully transparent: DigitalOwl’s AI links every insight directly to the source document through a click-to-evidence feature. In the beginning, I clicked on every piece of evidence to verify accuracy. It took time, but it was important to test the system. Eventually, I found that I didn’t need to check every data point. The AI consistently delivered accurate results, and that reliability earned my trust. Once I was able to rely on it without second-guessing, the efficiency gains skyrocketed.
2. The platform is tailored to claims professionals: Their enhanced Case Notes product includes nearly everything I need to review a case. It doesn’t just summarize information. It connects the data, applies P&C-specific logic, and delivers insights that matter to claims professionals, such as identifying the progression or improvement of a condition. When paired with their in-depth analysis chat feature, I can complete a full case review using just those two tools.
3. It dramatically increases efficiency: Using DigitalOwl’s platform, I can save over two-thirds of the time it takes to review medical records, especially when handling larger, more complex files. Instead of reading through an entire medical record, I get key insights surfaced up front. I can verify them quickly, rather than gathering and interpreting everything myself. If I have questions, I can ask the chat feature and get immediate answers. These tools help me work faster without compromising the quality of my decisions.

Using DigitalOwl’s platform, I can save over two-thirds of the time it takes to review medical records.

After initially questioning the value of AI in claims, I saw firsthand what the right solution can do. I believed in it enough to join the team at DigitalOwl, helping tailor solutions for the real-world needs of claims professionals. I’ve been in your seat, I know what the day-to-day challenges look like, and I understand what adjusters need from a platform in order to actually use and benefit from it.

My goal is to make sure DigitalOwl continues to build AI products that don’t just sound good in theory, but deliver meaningful, practical value where it counts—in the workflow. Because when claims professionals have tools they can trust, that’s when the real impact of AI becomes clear.

Have questions or just want to talk shop? Feel free to follow me on LinkedIn and send a message. I’m always happy to connect.