Bridging the Divide: Addressing AI Concerns in P&C Implementation

In a recent blog, we explored how P&C insurers are shifting from understanding AI to putting it into action. This shift raises important questions about the ethical, safe, and effective use of AI, whether AI can accelerate career paths in claims adjusting, and how AI can consistently meet the accuracy and quality standards that claims professionals are held to.

In my conversations with industry leaders, one thing is clear—plaintiff attorneys are already using AI for evaluation, demands, and exploiting insurance company behaviors, and it’s time for insurers to engage similarly. As AI governance continues to evolve, organizations are actively exploring how to adopt these technologies while ensuring compliance. 

Ethical, Safe, and Effective Use of AI in Claims

P&C carriers have historically been slow to adopt change, but the rapid rise of AI among plaintiff attorneys makes it clear—it’s time to recognize the benefits of AI for claims handling. However, AI in insurance is not one-size-fits-all. Different applications come with varying levels of ethical considerations, safety risks, and effectiveness. For carriers and AI governance committees, this makes it critical to carefully evaluate AI solutions and their impact on accuracy, compliance, and decision-making.

When assessing AI-powered claims solutions, insurers must consider:

• Ethical Implications – Is the AI designed to support fair, unbiased decision-making?
• Safety & Compliance – Does the AI meet regulatory requirements and data security standards?
• Effectiveness in Claims Workflows – Does the AI enhance efficiency without sacrificing accuracy?

To properly assess these options, many insurers have established AI governance teams tasked with ensuring responsible AI adoption and implementation. However, with nearly every major platform now embedding AI into their solutions, these teams are often overwhelmed, making it difficult to efficiently move AI projects forward.

If this sounds familiar, I encourage you to download our AI Governance Toolkit—a resource designed to help committees streamline their review process and easily evaluate our commitment to secure, responsible AI practices.

Accuracy and Quality in AI-Powered Medical Record Reviews

Claims professionals are held to an exceptionally high standard of accuracy and quality. When discussions around AI’s efficiency arise, I can see the wheels turning in claims professionals’ heads—can AI truly meet the accuracy and quality standards of human reviewers? Not all AI solutions are created equal, but I can confidently say that DigitalOwl’s AI can.

DigitalOwl’s AI is trained by an in-house team of medical, data, and insurance experts to ensure it pulls the right information from medical records with precision. It’s backed by a continuously expanding medical knowledge base, providing critical context to understand the nuances of medical terminology, conditions, and treatment patterns. Unlike a human reviewer, AI never gets tired and excels at identifying minute discrepancies across hundreds or even thousands of pages of similar information.

By reducing variance between claims professionals—which can be influenced by training, experience, or personal interpretation—DigitalOwl’s AI elevates every medical record review to an expert level. This doesn’t replace the role of claims professionals but instead enhances efficiency by surfacing the most relevant information quickly. 

Ensuring Accuracy with AI

Accuracy is a top concern among claims professionals, and this is why selecting an AI provider that prioritizes transparency is critical. With DigitalOwl, every piece of extracted data is easily verifiable with click-to-evidence, allowing for immediate fact-checking and verification of results of the AI to ensure confidence in the outcome.

At DigitalOwl, we recognize the risks of missing crucial information, which is why our AI is trained to err on the side of caution. Instead of omitting uncertain data, our AI surfaces all potentially relevant information. This ensures claims professionals see everything that could be important, but only need to verify the details that actually impact decision-making.

This approach eliminates the need to hunt down missing details and helps claim professionals build trust in AI over time. Getting comfortable with AI is like test-driving a new car—you need time to try it out, kick the tires a bit, test the features and see how it performs. And when AI is built to be transparent, reliable, and designed with the user in mind, it’s easy to see how it can enhance—not replace—the work they do.

Adapting to Change: Embracing AI in Claims Handling

It’s time to embrace AI and the competitive advantages it brings to the marketplace. Casualty and Workers’ Compensation claims handling still rely heavily on manual processing, yet the use of AI in insurance claims offers a powerful solution to enhance efficiency, accuracy, consistency, and overall claims performance.

By integrating AI, insurers can streamline claims handling and create greater accessibility for adjusters without medical backgrounds. AI enables quick search, retrieval, and analysis of medical records, ensuring consistency and reducing the manual effort required to find key information. It also clearly outlines gaps in records, highlighting additional details needed to evaluate an injury claim —speeding response time and improving claim outcomes.

In the short term, reducing the time spent on medical record analysis allows claims professionals to focus more on evaluations, negotiations, and claim strategy, rather than getting bogged down in reading hundreds or thousands of pages of medical records. AI also enables less experienced staff to confidently review medical records without sacrificing quality or accuracy.

Over the long term, these efficiency gains enable adjusters to touch each claim fewer times to arrive at their evaluation,  reducing cycle times. Improved injury claim management creates a positive ripple effect that can be measured in file quality, cycle time, attorney penetration, and reduction in claims progressing to litigation.

The Future of AI in Claims

DigitalOwl is more than just a medical record summarization service. In addition to delivering accurate, high-quality medical record summaries and chronologies, our platform also features conversational AI capabilities, allowing claims professionals to Chat directly with the medical record for instant answers—eliminating the need to manually sift through thousands of pages. 

With the recent addition of Case Notes, a revolutionary new product, our platform now goes beyond summarization, offering actionable insights tailored to each claims professional’s specific use case, such as:

• Time-sensitive information about demands or conditions
• Critical decision-making information
• Incomplete or future treatments
• Patient compliance with medical advice
• The severity and impact of injuries

Want to see it in action? Book a 30-minute demo with me to learn more!