Using AI To Improve Employer-Sponsored Insurance

Artificial intelligence (AI) offers many opportunities to reshape health care delivery and access. In recent years, leaders across the health care industry have welcomed the AI boom and its promise to streamline administrative tasks and create efficiencies in provider workflows – ultimately empowering frontline clinicians to spend more time interacting with patients and delivering timely care.

This represents a tremendous advantage in employer-sponsored health care. Half of the U.S. population (160 million people) receives coverage from their workplace – and employers collectively invest $1 trillion in health care offerings to ensure that their employees have reliable access to high-quality care.

But these investments haven’t translated to better care outcomes or an improved patient experience. Individual factors can lead to significant variations in both health care access and outcomes. At the same time, the average employer is experiencing double-digit cost increases for their health benefits.

As American businesses grapple with rising costs and the need for more personalized, effective care, AI-driven clinical solutions are emerging as essential tools in the benefits arsenal. The deployment of AI can drive towards better clinical outcomes and ultimately improve the quality, affordability and equity of employer-sponsored health care.

Here are five key opportunities:

1. Clinical Decision Support for Evidence-Backed Care: One of the most promising applications of AI is in clinical decision support. By analyzing patient histories, the latest medical literature and outcomes from similar cases, AI can recommend treatment protocols that are both evidence-based and tailored to individual needs. This not only helps clinicians make more informed decisions but also may ensure employees receive care that is proven to work – reducing unnecessary procedures and improving recovery rates. Tools like Embold’s Virtual Assistant use AI to review clinical data and directly connect patients to high performing providers to access the best possible care. Equally important, it meets patients where they are – and interfaces with them on their preferred channel.
2. Patient Triage for Optimized Care Delivery: AI-powered patient triage systems can transform how health systems prioritize care. By assessing the criticality of patient presentations in real time, these tools can help direct resources where they are needed most and ensure that urgent cases receive immediate attention while routine issues are managed efficiently. For employers, this means their workforce can get timely care, minimizing downtime and supporting productivity. Cortica, a leader in autism and neurodivergent care, leverages this approach to speed up the initial diagnosis process and reduce delays in treatment (which remains a key hurdle for patients and their families today).
3. Precision Diagnosis and Monitoring: Computer vision technologies are now being applied to medical imaging, enabling faster and more accurate diagnoses. AI can detect subtle variations in X-rays, MRIs and other scans to support even the most experienced radiologists. This capability not only speeds up diagnosis but also aids in treatment planning and disease monitoring, ensuring employees are on the right path to recovery and reducing the risk of missed or delayed diagnoses. Merative’s Merge Imaging Suite combines AI with data expertise to help clinicians improve their workflow and diagnose with confidence.
4. Risk Prediction and Proactive Intervention: AI can efficiently identify individuals at high risk for adverse health outcomes. By analyzing vast datasets, these solutions can flag employees who may benefit from early interventions – whether it’s chronic disease management, preventive screenings or targeted wellness programs. In the long term, this can help employers manage population health more effectively – reducing costly hospitalizations and improving overall well-being. As one example, apree health uses machine learning and advanced algorithms to analyze over 220 million medical and pharmaceutical claims to identify future cost and utilization trends.
5. Tailoring Care to the Employee: Perhaps the most exciting frontier is personalized treatment. AI can synthesize nuanced health histories and real-time data to develop patient-specific protocols, moving beyond one-size-fits-all medicine. Employees can receive care that reflects their unique needs, preferences and risks. In turn, this can lead to better engagement, improved outcomes and higher satisfaction. This is an increasingly important feat for serious health issues, like cancer, where patients have historically struggled with fragmented care and a patchwork of solutions. Thyme Care, a leader in value-based oncology care, is deploying AI to seamlessly guide patients throughout their cancer journey – from personalized treatment plans to clinical trial matching.

As AI continues to evolve, its integration into employer-sponsored health care will only deepen. The challenge for benefits leaders is how to harness these technologies responsibly – ensuring data privacy, transparency, and equity – while embracing the potential for smarter, more personalized care. The potential payoff is clear: healthier employees, lower costs, and a more resilient provider workforce.