Regardless of regulatory model, workers’ compensation insurers generate economic value through their specialist knowledge in risk management, loss control, claims management and economic scale.
Historically a challenging market, workers’ compensation has posted positive combined ratios since the early 2010s through improved risk management, lower loss frequency, and technology that better connects claims management with clinical care and sustained support for injured workers.
However, challenges remain with current trends in medical cost inflation, increased mental health claims, litigation exposure and changes to the nature of work increasing the modernization challenge for insurers.
In this joint paper from Guidewire and PwC, we examine these macro trends alongside advances in generative, agentic and other forms of artificial intelligence, collectively referred to here as AI.
Workers’ compensation insurers are uniquely positioned at the intersection of the healthcare and insurance industries. This gives them a unique opportunity to leverage advances across multiple industries to improve injured worker outcomes, boost insurer performance, and deliver on the promise of a safer work environment.
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LOSS CONTROLGuidewire Customer in the US: A West-Coast regional carrier is combining on-site video monitoring with AI vision to identify hazards or unsafe activities, leading to targeted training and improved factory layouts. Initial results show lower claims frequency from participating insureds.
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MEDICAL BILL REVIEWGuidewire Customer in the US: A workers’ compensation customer used a Guidewire predictive analytics and AI partner to analyze medical bills and treatment details and identify providers who overprescribed opioids. By removing these providers, the carrier significantly reduced costs and improved claims outcomes, demonstrating AI’s power to detect patterns of abuse in medical practices.
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CASE MANAGEMENTGuidewire Customer in Canada: A workers’ compensation board implemented an AI-driven predictive model directly into ClaimCenter that automatically identifies high-risk No Lost Time claims for early intervention, leading to significant cost savings within the first year and preventing hundreds of claims from becoming Lost Time claims.
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RETURN-TO-WORK PLANGuidewire Customer in the US: A single-state workers’ compensation carrier improved their return-to-work (RTW) performance with a solution that directly integrates to Guidewire ClaimCenter and provides both recommended activities as well as comparison against similar RTW outcomes to identify variances.
of respondents believe medical cost inflation will have the greatest impact to their performance
of respondents believe an aging workforce will shift the risk profile and loss experience of the industry
of respondents are building or planning to build out their AI platforms
of insurers have a defined AI strategy at the enterprise or business unit level
of insurers with a defined AI strategy have one or more AI models in pilot or production
of respondents expect improvement in operational efficiency through AI
of insurers expect improved return-to-work outcomes
of insurers have realized some anticipated benefit from AI, while ~30% have yet to achieve their benefit goals
In discussions with Guidewire’s workers’ compensation user groups, business advisory councils, and carrier role observations, insurers expressed overall optimism toward the benefits of AI, with improvements in handling large and complex volumes of documentation a key benefit. Insurer fears relate to their competitive position, the concern of being left behind due to lack of technological capabilities, and internal barriers to innovation.
While much of the current discussion around AI in the insurance industry focuses on process automation and cost savings, these conversations often overlook more transformative, long-term implications. Case in point: 100% of the respondents in our survey expect AI to improve their operational efficiency, suggesting that it has become table stakes. For workers’ compensation carriers, AI presents opportunities far beyond that.
We believe 5 AI Forces will have an impact on workers’ compensation consumers and insurers through 2030:
As a key component of workers’ compensation, claims management has largely operated in a process-centric model since the early 1900s—reflecting the institutional capabilities and technologies insurers possessed at the advent of the modern workers’ compensation market.
Toward a New Worker-Centric Model
AI supports the transition from an institutional, process-driven claims model to one of personalization, individualized insight, and worker-centric case management. Four enabling capabilities unique to AI will catalyze this shift:
- Integration of AI & Insurer Data Platforms As AI models become integrated with complementary external and internal data, traditionally manual or semi-automated processes can be streamlined and enhanced to improve injured worker outcomes.
- AI-Powered Expertise AI tools can embed expert knowledge directly into the claims workflow, improving decision-making of front-line claims representatives while reducing dependence on a few key specialists.
- Intelligent Data Extraction AI can automatically pull pertinent information from documents throughout the claims process, from First Report of Injury (FROI) to medical receipts. This allows insurers to monitor claims in real time and make adjustments that improve both claim outcomes and performance.
- Personalized Support Injured workers can get 24/7 support from AI-powered agents that provide instant, personalized answers about claim status, explain complex medical plans, and offer tailored guidance.
AI & Workflow Automation
Workers’ compensation insurers are embracing AI-enabled workflows to meet rising expectations for caseload, speed, precision, and personalization. At the heart of this shift, AI empowers insurers to streamline complex processes like submission processing and treatment planning through intelligent agents that reason across data in real time. These systems reduce administrative overhead and guide decision making, all while keeping humans in the loop.
AI Centers of Excellence
As this transformation moves beyond experimentation, forward-looking carriers are standing up AI centers of excellence to enable sustained, enterprise-wide adoption and even more significant impact in core processes:
- Underwriting AI enables faster, more nuanced risk profiling and enhanced consistency in risk assessments by analyzing application data combined with external sources such as social media, IoT, and news.
- Proactive Intervention AI can flag potential high-risk cases by analyzing historical data and real-time inputs to suggest timely interventions that improve both loss prevention and case management outcomes.
- Claims Triage AI categorizes incoming claims based on severity, complexity, and urgency, quickly routing claims to the right adjuster to improve overall claim cycle time.
- Injury Analysis AI analyzes injury narratives, medical codes, and past claims to predict recovery times and cost implications. It enhances transparency and supports evidence-based claim adjudication.
- Decision Support AI augments human judgment with intelligent summaries, recommendations, and predictive insights across the insurance value chain for better decisions in underwriting, claims, and operations.
Effective workers’ compensation risk management relies on several interconnected components that work together to create a comprehensive safety ecosystem. Beyond traditional data analytics, AI can analyze vast amounts of unstructured data—such as safety reports, maintenance logs, and incident descriptions—to identify hidden risks. It goes beyond spotting historical trends to generating predictive scenarios, allowing organizations to address vulnerabilities before they lead to injuries.
Prevention
Organizations that invest in regular training sessions, industry-specific safety protocols, and employee wellness initiatives see significant reductions in workplace incidents. These programs help create a culture of safety awareness that extends throughout the organization.
Early Intervention
When injuries do occur, AI enables early intervention by accelerating the claims process and recommending individualized return-to-work plans, which prove essential in minimizing the impact of workplace injuries. Quick response systems, coupled with coordinated medical care and modified duty programs, help injured workers recover faster and return to productivity sooner, reducing overall claim costs.
Continuous Risk Assessment
Finally, continuous assessment and improvement ensure that risk management strategies remain effective over time. AI turns periodic safety reviews into a continuous, real-time process by scanning regulatory databases and industry reports to alert managers to new compliance requirements or emerging risks. These regular safety audits, industry benchmarking, and ongoing protocol updates keep safety programs current and relevant.
Ecosystem Partners Drive Innovation
The workers’ compensation market is evolving rapidly, with a large share of innovation driven by ecosystem partners.
Examples:
- To address both rising medical costs and increasing mental health claims, AI-driven bill review and digital care management partners can ensure treatments are both cost-effective and clinically appropriate.
- As the labor force shifts, AI-powered claims guidance tools embed expertise into core systems to bridge the knowledge gap left by retiring veterans.
- For increased litigation exposure, robust predictive analytics enables early identification of potential attorney involvement.
- To navigate complex regulations, claims reporting partners automate regulatory reporting, reducing risk and operational friction across multiple jurisdictions.
Key Considerations for Ecosystem Enablement
A modern, API-first core platform is the essential foundation that enables insurers to innovate quickly with new capabilities and services to better meet the needs of the evolving workers’ compensation market. Key considerations when enabling an ecosystem include:
Align business goals
The objective is not simply to use the latest new AI technology, but rather to solve a business problem. Specific challenges may require different designs based on complexity, point in the value chain, and customer expectations.
Select the appropriate partners for each critical function in the value chain
Guidewire’s ecosystem, for example, features pre-vetted solutions that integrate easily into the core system.
Embed the ecosystem’s insights and automation into end-to-end workflows
This avoids creating piecemeal solutions and ensures the entire organization benefits from a unified, technologically-empowered approach to managing risk and serving customers.
Guidewire Marketplace Partners
Are Embracing AI in Workers’ Compensation
Cloud-Native, Modernized Core Systems
A modern, cloud-native core platform is essential to achieve and maintain breakthrough potential, particularly with AI. This core provides the scalability, flexibility, and integration points needed for AI-driven transformation across the insurance value chain.
Flexible Architectural Framework
An “agentic AI architectural framework” is required to support modular, task-specific AI agents (e.g., for underwriters, claims adjusters, developers). This framework should enable the creation and orchestration of AI-assisted applications, leverage multiple large language models (LLMs), and support prompt management, evaluation, and observability.
AI Governance, Security, and Observability
Operationalizing AI at scale requires robust governance, including prompt testing, security, and observability. This requires tools and processes to manage, evaluate, and monitor AI models and agents, ensuring responsible and compliant AI usage.
Data Ecosystem and Connectivity
A networked data ecosystem is critical for AI success. Upstream and downstream connectivity to cloud data platforms, as well as analytics to enable predictive insights, automated processing, and intelligent workflows are especially important.
Business Process Transformation and Automation
The transformation is not just technical. It is critical to reimagine and automate business processes (e.g., underwriting, claims, billing) to make use of AI-powered agents and low-code workflow tools. This enables insurers to increase agility, reduce manual work, and unlock new business value.
Identify Highest Value Business Use Cases
Partner with leaders across your business and IT organizations—and extend collaboration beyond your own organization by engaging with industry peers, partners, and technology experts—to identify and prioritize the highest-value use cases for AI.
Move to a Modern Cloud Technology Stack
A modern cloud technology stack is a crucial enabler for AI. Evaluate your current-state technology capabilities across policy administration, claims, billing and data platforms.
Leverage Partner Ecosystem
Maximize your modern cloud insurance platform by tapping into its ecosystem of data providers, services, partners, and edge technologies to boost capabilities, speed innovation, and deliver real-time insights.
Commit to Scale
Most companies are experimenting with AI but fail to scale. It is crucial to prioritize and commit to scaling a small selection of use cases.
