NAPEO
PEOs exist to provide reliability and security for their clients. But once a data breach occurs, that trust erodes quickly. Research shows that 68% of clients switch providers after a security incident.
As both traditional AI and generative AI technologies evolve, the insurance industry will see some tremendous changes, which will impact both insurers and PEOs. By leveraging AI, these organizations can address critical challenges, streamline operations and enhance their service offerings.
Here are six key predictions specific to the opportunities they present for PEOs.
AI WILL DRIVE NEXT BEST ACTION RECOMMENDATIONS IN UNDERWRITING AND CLAIMS MANAGEMENT
Managing workers’ compensation and employee benefits on behalf of their clients can be time intensive and complex for PEOs. This year we will see more PEOs leverage AI to provide next best action recommendations for both underwriting and claims management. When underwriting, ‘next best action’ recommendations provide PEOs with specific suggestions to adjust coverage limits or additional data sources to better assess risk, based on AI-driven insights. Similarly, when overseeing claims, AI can suggest specific next best actions such as seeking additional documentation or identifying the optimal settlement path based on previous claims data. These advanced insights will streamline decision making, reduce resolution times and create a more seamless client experience.
SPECIALIZED GENAI WILL BECOME COMMONPLACE IN INSURANCE
PEOs are continually challenged to keep up with a multitude of evolving state and federal employment laws, joint-employer regulations, paid family leave, and minimum wage requirements. AI tools and their capabilities deliver tremendous benefits, yet they may fall short when it comes to addressing industry-specific needs, like analyzing policy language or understanding regulatory requirements.
As demand grows, purpose-built Generative AI models will evolve to produce increasingly specialized tools that can better interpret nuanced insurance data. These tools will be tailored to analyze intricate policy documents and draft tailored policy language, making them far more effective than general-purpose AI. This shift will enable PEOs to better navigate complex regulatory environments and improve their ability to design personalized insurance products to align with the diverse needs of their clients.
PEOS WILL PHASE IN DIGITAL TRANSFORMATION TO AVOID LEGACY SYSTEM OVERHAUL FAILURES
Many PEOs operating with legacy HR, payroll, and benefits management systems know they need to modernize these systems to stay competitive. However, attempting to replace all core systems simultaneously can become unmanageable, leading to delays and costly setbacks.
In 2025, we will see PEOs take a phased approach to digital transformation, implementing targeted upgrades rather than complete system overhauls. This approach will allow them to focus on specific areas like customer portals or underwriting modules, integrating AI gradually and minimizing disruption to existing operations. This incremental strategy delivers immediate value while ensuring continuity of operations for both PEOs and their clients.
SPECIALIZED DATA SOURCES WILL INCREASE INSURANCE RISK ASSESSMENT ACCURACY
A PEO’s ability to provide competitive employee benefits policies depends significantly on having accurate risk assessment. Insurers typically use established data sets like historical loss data, demographic information, and general weather reports to assess risk. Current AI models handle broad categories of risk—they rarely leverage niche data sources.
In 2025, PEOs will start to integrate specialized data sources, such as climate and health data to enhance risk assessment and underwriting for deeper insights. For example, tapping into health data, like fitness-related information from smartwatches, can help PEOs differentiate between policyholders who may look the same in a policy application but actually represent vastly different risk profiles (e.g., active triathletes vs. sedentary individuals with significant latent health risks). This specialized data integration will provide insurers with a holistic view, enabling more accurate policy pricing and claims assessments.
AUTOMATED INSURANCE DOCUMENT PROCESSING WILL BECOME SMARTER AND MORE SCALABLE
PEOs may face challenges in managing tremendous amounts of paperwork, including employee records, payroll documentation, and benefits contracts. In 2025, advancements in automated document processing will enable PEOs to manage these documents faster and with better accuracy.
They will be able to process thousands of lengthy, multi-format documents efficiently, handling everything from de-duplicating redundant data to categorizing unstructured records. For example, claims involving extensive medical histories will no longer require tedious manual reviews, as automated systems will quickly summarize and catalog pertinent details across hundreds of pages. This means that claims processing will be faster, cheaper, and more accurate, allowing PEOs to manage even higher volumes of claims while reducing error rates and improving customer satisfaction.
AI MODELS WILL ALIGN WITH NEW REGULATORY DEMANDS
Regulatory compliance is a high priority for PEOs, especially when managing client employee benefits and workers’ compensation programs across multiple states. Recently, the National Association of Insurance Commissioners (NAIC) adopted a model bulletin outlining compliance requirements for insurers’ AI systems. This bulletin clarifies expectations for development, deployment, and documentation of AI technologies to ensure adherence to state and federal laws.
In 2025, PEOs will begin to adopt transparent, AI-driven models that align with both NAIC guidelines and specific state regulations. These models will also include explainable AI components to ensure clear, auditable insights into predictive processes to meet compliance demands. For PEOs operating across state lines, these advancements will streamline regulatory adherence and enhance consumer trust by offering transparent, ethical risk assessments. This shift will establish responsible AI use as a foundational standard in the industry, reshaping the role of predictive analytics and data usage in insurance.
PEOs that adopt both traditional and generative AI technologies are positioning themselves to drive meaningful change, unlock new growth opportunities, and deliver greater value to their small and midsized business customers.
If operational engagement is the goal, “micro-frictions” are its subtle enemies. These small, persistent irritations—tedious passwords, delayed responses, unclear steps—quietly say, “We didn’t consider your experience.”
PEOs that embrace HCM technology to enhance EX can move beyond transactional payroll and employer-related compliance to offer services that build deeper, more meaningful partnerships with their clients.
Technology-driven solutions like applicant tracking systems, workforce management platforms, and real-time reporting software offer a clear path to overcoming recruitment hurdles, optimizing operational efficiencies, and making data-driven decisions.
Many firms adopt a use-case approach to demonstrate the value of AI, select tools, and build momentum within the enterprise. While this approach remains relevant, the competitive landscape now demands a strategic approach to enterprise AI deployment.
Comprehensive consumer privacy laws are rapidly expanding across the United States, significantly impacting PEOs. Currently, 19 states have enacted privacy laws, with 8 already in effect and 11 set to take effect between January 2025 and January 2026.
Today, the infusion of technology in workers’ compensation is revolutionizing how PEOs serve their clients. In an industry where speed, accuracy, and a human-centered approach are important, technology keeps PEOs ahead of the competition.
As AI transforms the business landscape, PEOs are uniquely positioned to assist small businesses in navigating this technological revolution. They can provide guidance on AI-related HR practices, help with training and development programs focused on AI skills, and offer insights into how AI can enhance various aspects of workforce management.
Nothing seems untouched from AI these days. Even PEO risk management. Earlier this year, I had the privilege to join a panel at NAPEO’s Risk Management Workshop on the growing influence of AI and how it impacts the world of PEO risk management.
Insurance, healthcare and employee benefits have common business drivers that mandate the need for test automation. Each of these industries are data intensive and often include personally identifiable information (PII), payment card industry (PCI) or protected health information (PHI) compliance. There is no room for manual errors. While that alone may be sufficient to justify test automation, the customer experience lifecycles for onboarding, servicing, and renewals drive successful customer satisfaction and retention results. This is where PEOs can differentiate themselves with automation.
In today’s digital environment, test automation is necessary for meeting the service levels required by a sophisticated customer base. Given the wider adoption of agile methodologies, automation, and continuous deployments, testing cannot be executed using traditional manual processes. In this article, we will examine key opportunities for introducing test automation and identify approaches and technologies to drive successful project delivery and ensure accelerated onboarding of customers.
DOES ONBOARDING TEST YOUR CUSTOMER’S PATIENCE?
For employee benefits, onboarding involves various insurance and healthcare products and payroll options. A tremendous amount of active and historical data is transferred between customer, broker, and administrator. To add to the challenge, the quality of the data is often problematic and may come from various sources. Organizations can achieve automation by building testing accelerators, data extraction engines, automated forms and file comparisons, and automated reconciliation into your process. The onboarding process sets the bar for service expectations or can build a backlog of issues that may take weeks or months to resolve and start the relationship on a challenging path.
UNDERWRITING: ENSURING THE PRICE IS RIGHT
For property and casualty and specialty business insurance, submission and underwriting process automation is a key component of winning business and issuing policies. Testing must align with a straight-through-processing model. Processing ingests product-specific forms, claim loss run reports and supplemental data. Accelerators can be built for identifying specific forms for data extraction, testing automating risk triage and ensuring the correct pricing is applied based on accessing a rating engine or applying an underwriter decision. Testing the correct data ingestion, risk triage and raters are key to getting the proper pricing for the risk class, notifying the broker, and issuing the policy. How you price the risk will drive the profitability of the business.
TO RENEW OR NOT RENEW THAT IS THE QUESTION
Open enrollment is the time where test automation is often appreciated most. This is a time where organizations are onboarding new customers while also renewing existing customers that may have selected various new products and services along with revised pricing that aligns with prior claims and service experience. For renewals, automation can include the analysis of data collected during the contract year and testing the implementation of the changes in product or benefit selection, third-party interfaces, reporting, and premium billing for the new effective date. The windows are tight to sunset prior year rules and implement new contract year selections. Automation is a key enabler to avoid a backlog and provide a positive customer experience.
SELECTING YOUR AUTOMATION FRAMEWORK
At Quess GTS, we use a variety of tools for automation. Three commonly used tools for test automation are Selenium as an Automated Testing Framework, Jenkins for Continuous Deployment and Excel for building Test Case Accelerators. These tools work very well together and are ideal for organizations of all sizes. The frameworks integrate with existing tools and technologies without constraints on scale. They also provide comprehensive reporting and analytics to track test results, defect trends, and enable prioritization.
With Excel, you can generate hundreds or thousands of test cases or easily modify your test case repository for similar conditions. For insurance, healthcare and employee benefits you may want to consider starting with:
BUILDING YOUR TEST CASE REPOSITORY
Automation will not happen overnight. It is an incremental process that leverages reusable cases and assets for onboarding new customers, testing new features, performing automated compares, or running regression. The following are considerations in building your repository:
TESTING YOUR AGILITY
Test scripting in an agile environment requires writing automated, repeatable, and reusable test cases. Test scripts must be well documented and easily adaptable for frequent or continuous deployments. Some considerations include:
Maintainability and scalability: Automated tests in Agile should be easily updated to accommodate frequent changes.
Collaboration and communication: Agile processes require collaboration among testers, developers, and product owners. There must be clear targets, alignment on goals and defined acceptance criteria.
Continuous Deployments (CD): Automated test scripts should run as part of automated process that may evolve to a CD pipeline, providing immediate feedback on the quality of code changes in a release.
User Experience: Test scripts are not for back-office functions only. The user experience should consider multi-platform/browser inputs (mobile, desktop, other), workflow rules and straight-through-processing while ensuring security requirements are met.
While each organization is at a different level of technology and test automation sophistication, test automation is achievable for all. Using some of the tips and recommendations in this article within a PEO industry context enables a verticalized approach to automation. Organizations should start small, scale the automation, and consider evolving to continuous deployments where test scripts are bundled with software changes into a shared environment. With each update, automated builds and tests are triggered for early detection of errors. Integrating automated testing seamlessly into the delivery pipeline provides actionable insights to each release, enabling quick defect resolution and limiting technical debt. The result is improved quality, time to market and customer satisfaction.
Test automation is a mandate in today’s digital-first environment and provides a PEO a foundation to grow its business while increasing the competitive capabilities to win and service business. Our recommendation is to start with test case automation and frameworks and transition to CD over time based on business needs, technology tools and application stack. We suggest partnering with a firm with expertise in this area to assess your environment, collaborate with your team to build test cases, provide advisory tools and establish the environment, and ensure scalability to increased automation and potentially continuous deployment. The right approaches will give you a time-tested digital foundation to grow your business with significant improvements in customer experience.
AI-assisted hiring represents not just a trend but a significant shift in how organizations approach talent acquisition, promising a more efficient, unbiased, and inclusive future.
The bottom line – if you have not updated your CCPA notices since 2022 or earlier – or if you have never provided such notices – you should act quickly to implement new notices and stay compliant with the ever-changing law.
As the rate of digital transformation continues to accelerate across all industries, insufficient cybersecurity guardrails and policies remain a pressing threat to the insurance and benefits ecosystem. Here are 6 questions to ask to assess your PEO’s cyber risk.
Deepfake media is only going to become more prevalent. Its use in social engineering is going to grow. Education is the best way to help your organization thwart this alarming reality.
From my vantage point, the infusion of AI into the unemployment sector holds the key to unlocking a multitude of advantages that could revolutionize the efficiency, accuracy, and cost-effectiveness of unemployment insurance operations.
Efficiencies are and always will be an investment, and updating your daily processes may take time; however, the payoff is guaranteed. By innovating with technology, you will achieve your goals of improving efficiencies and delighting your customers.
PEOs should seek to cultivate a culture of risk management surrounding AI use – both in your organizations and at your clients’ places of business – in order to be best positioned in this new area. These are the 10 most critical steps to minimize.
Today, any business that doesn’t capitalize on data advancements risks being swept away with the tide. PEOs in particular should think of data as a direct pipeline to the resources you and your clients need to navigate the complex world of HR and compliance, and make better business decisions in the process.
AI holds the potential to revolutionize the insurance and benefits industry, contributing to risk reduction, enhanced customer service, and augmented efficiency. The potential of automation and generative AI is boundless, and adoption continues to surge.
Automation tools can provide some much-needed relief during open enrollment, empowering small business leaders to get it all done. However, many small business leaders seem unsure about the return on the investment of technology in this space.
We’ve now reached a critical juncture where companies need to make a few important decisions about how to use AI. Many topics will include both HR and HCM, meaning countless companies will be looking to their PEO partners to provide guidance in navigating the increasingly complicated AI waters.
The pressing question for organizational leaders centers around how to leverage data strategically and productively toward meaningful results. Here is a simple framework to drive value and impact through the use of quality data.
PEOs should be aware of what AI tools can do to assist their clients but should also recognize that this is an emerging technology still subject to flaws.
