How Gen AI Will Revolutionize Claims

In workers’ comp, generative AI can transform claims management by improving accuracy, enhancing documentation and, freeing adjusters to focus more on the injured workers.

An artist’s illustration of artificial intelligence (AI).

According to a recent report, 38% of insurance CEOs are embarking on generative AI initiatives, and 34% of surveyed companies have already incorporated this technology into existing workflows. While the rapid development of large language models leaves room for discoveries, this survey and others present a clear picture of generative AI’s potential value for the insurance industry.

In workers’ compensation, generative AI has the power to transform claims management by improving decision-making accuracy, enhancing documentation and, most importantly, freeing time for adjusters to focus on helping injured workers get the care they need quickly. This will ultimately accelerate return to work and protect an employer’s brand. Generative AI can equip staff with more robust data, leading to enhanced predictive models to optimize and reduce emerging risks. 

Let’s explore where generative AI makes the greatest impact in claims management and how AI-friendly workplaces can augment human insights and empower claims professionals to work at their highest professional standard. 

See also: The Dawn of Gen AI In Insurance

Revolutionizing Efficiency

A chief insight of the report is the belief held by nearly 80% of respondents that generative AI will significantly increase operational and process efficiencies. This capability stems from the power of large language models (LLMs) to digest vast amounts of information, detect patterns often hidden to the human eye and generate insights and reports. As adjuster workloads have historically been composed of manual processes, the power of generative AI to streamline claims processing represents the transformation of an entire industry. 

When adjusters receive a claim, the information found in the accompanying medical records tells a story that will determine the direction of the claim and the resulting next steps. In current cases, generative AI tools can read and digest this complex medical information, produce concise summaries of key highlights and propose actions. This utility is taken one step further by the power of LLMs to extract unstructured data from medical documents for quick updates on claims management platforms. This helps ensure that all stakeholders are apprised of the status of the current claim. In addition, adjusters can leverage generative AI’s rapid processing capabilities to answer queries in context, sidestepping searching what could be copious amounts of documents for answers. 

The efficiencies realized from incorporating generative AI tools into claims workflows translate into time savings, increased productivity and more accurate decision-making. By automating repetitive tasks, professionals can focus on more complex cases, enhance customer service and satisfaction and ultimately improve injured worker outcomes. 

Improving Outcomes 

When adjusters automate and streamline high-volume, manual claims processing tasks with generative AI, they can devote additional time to strategic work, such as directly engaging with injured workers, conducting comprehensive investigations and delivering personalized assistance throughout the claims journey. These personalized interactions and faster claims processing times enable injured workers to be quickly connected with care resources and embark on their recovery journey. In addition, by leveraging generative AI’s power to derive insights from medical documentation, adjusters can equip clinicians and insurers with pertinent information about workers’ injuries and health history, further removing communication silos between key stakeholders on workers’ care teams. 

Experiencing delays in getting an appointment and navigating insurance processes are common challenges many encounter within the U.S. healthcare system. For injured workers who may be unfamiliar with the workers’ compensation process, these poor experiences can easily be compounded, leading to fragmented care and delayed recovery. By accelerating claims processing and streamlining communications, generative AI places injured workers at the center of the claims journey and influences better experiences, enhanced care outcomes and faster return to work.

See also: How Gen AI Changes Everything in 2024

Transforming the Role of Claims Adjuster   

Generative AI not only has the power to transform injured worker outcomes but can also revamp and expand the role of the adjuster. As adjusters leverage advanced technology to equip injured workers with care, these professionals are empowered to understand their role as more than just processing documents; they can effect real change in the lives of injured workers. Over the next five years, as adjusters increasingly rely on generative AI to handle routine tasks and streamline processes, we will see the role of the adjuster focus on highe-value tasks such as strategic decision-making and customer relationship management. 

To support adjusters’ evolving role, third-party administrators (TPAs) and insurers will be called to prioritize generative AI training and education to ensure the effective use of these tools. Learning models such as hands-on workshops, online courses and continuous skill development programs will enhance understanding and proficiency in using AI for claims management. The key to promoting AI best practices is highlighting the importance of using AI as a supportive function rather than a worker replacement. This perspective, known as “augmented AI," refers to using AI technologies to enhance human capabilities rather than replace them entirely. While AI has the benefit of streamlining processes and providing actionable insights, human oversight and empathy remain critical to claiming success. 

Considerations and Looking Ahead

As with any new process or implementation, TPAs and insurance leaders can expect to encounter challenges with integrating generative AI into claims processing workflows. These challenges include data privacy concerns, ensuring the accuracy and reliability of AI-generated insights, employee resistance to change and regulatory compliance considerations. Leaders can navigate these obstacles by investing in robust data security measures, providing comprehensive training and support, collaborating with regulators to ensure compliance and, most importantly, proactively addressing concerns. 

The future is bright for generative AI in claims management, and we can expect long-term uses to include automation of the entire claims processing cycle. While industry-leading TPAs are already revolutionizing efficiency in medical document review, future iterations may further automate claims processing tasks, learn from past claims to generate new information, enhance fraud detection and improve customer service through AI-powered chatbots. 

Jeff Gurtcheff

Profile picture for user JeffGurtcheff

Jeff Gurtcheff

Jeff Gurtcheff is CorVel's chief claims officer. 

He has more than 30 years of experience in the industry, spanning the third-party administrator space, independent insurance and the carrier market.

Gurtcheff received his bachelor's in business administration/finance from the University of Iowa.


Read More