Unlocking Member Value with AI-Empowered Experiences

By Sri Lakshminarayanan

The stakes are rising: According to the 2025 JD Power U.S. Commercial Member Health Plan Study, the national average satisfaction score for commercial health plans has dropped to 563 (on a 1,000-point scale), with only 56% of members reporting satisfaction with their coverage. This marks a continued decline from previous years and highlights widening gaps between the highest- and lowest-performing plans. Regional scores vary significantly, and member experience is now a key differentiator for both retention and employer decision-making. Notably, 20% of employers cite low employee satisfaction as a top reason for switching health plans. The study also found that members who do not fully understand their benefits are much more likely to have claims denied and to face provider access issues.

To succeed, AI-empowered member engagement must focus on the needs of the connected generation; “Generation “C” represents of the customer who values brand reputation and personalized experiences. A comprehensive digital toolkit includes interaction analytics with AI-powered data capture, Gen AI, or Agentic AI, and intelligent automation. Such a toolkit can enhance engagement and build loyalty, enabling health plans to meet the evolving expectations of today’s digitally connected members.

Analytics & AI-Powered Data Capture

Interaction analytics, combined with AI-powered data capture, offer unprecedented advantages across all consumer journey touchpoints. These technologies extract actionable insights from both structured and unstructured data — voice, text, and documents — delivering essential ROI by enabling health plans to understand member sentiment, intent, and preferences at scale.

For example, end-to-end analytics that can transform every touchpoint in the member and provider journey. By leveraging process mining, predictive analytics, and intelligent content processing, organizations can extract actionable insights from both structured and unstructured data — including voice, text, and documents — at scale and in real time.

This approach enables health plans to:

• Understand not just the “what” and “where,” but also the “why” behind complex claim and service journeys
• Uncover root causes of provider disputes, CMS complaints, and Star Rating challenges
• Streamline documents, correspondence, and claim processing, reducing manual effort, and minimizing errors

Tangible Results:

A leading U.S. health plan, facing below-par Star Ratings and increasing provider disputes, implemented an end-to-end analytics and AI-powered data capture solution. By applying process mining and code-level analytics, the organization achieved:

• A 30% reduction in provider dispute overturns by identifying and addressing adjudication rules and process gaps
• A 50% reduction in duplicate disputes, particularly same-day, same-channel true duplicates, through intelligent detection and workflow automation
• Reduced provider abrasion, directly contributing to improved Star Ratings and measurable operational improvements

With this solution, the health plan improved dispute resolution, compliance, and overall provider and member experience through data-driven, real-time decision making.

Generative and Agentic AI

AI technologies are transforming member and provider experiences by automating high-volume, low complexity workflows and by delivering hyper-personalized interactions. These AI applications can generate tailored responses, automate routine communications, and even guide members and providers through plan inquiries or claims processes in real time.

By integrating Gen AI into digital engagement platforms, health plans can offer instant, context-aware support — answering questions, clarifying benefits, and resolving issues without human intervention. Agentic AI goes a step further, acting autonomously to complete tasks such as scheduling appointments, submitting forms, or escalating cases when necessary.

Tangible Results:

A national health plan provider partnered with Sagility to enhance contact center operations through a Virtual Agent solution. Approximately 55% of incoming calls were low in complexity and suitable for self-service, but existing options were inadequate.

Sagility conducted a thorough analysis of call and Interactive Voice Response (IVR) data, identified key use cases, and deployed a Virtual Agent within the client’s IVR system. By 2024, two of the ten identified use cases were implemented, resulting in a 34% to 58% increase in call deflection within three months — equating to around 120,000 calls. Containment and resolution rates also improved from 16% to 54%.

The initiative will be expanded with additional use cases that represent 27% of the overall call volume, with an estimated 12% more calls expected to be deflected by 2026 through expanded self-service. Intelligent automation thus can reduce call volumes and enhance satisfaction significantly for both providers and members.

Automation:

Automation is revolutionizing open enrollment and document management, delivering significant efficiency gains and cost reductions for health plans. Today’s cutting-edge machine learning, optical character recognition (OCR), and intelligent character recognition (ICR) technologies — collectively known as intelligent content processing — have transformed what was once a highly burdensome, paper-intensive process for payers.

By automating the intake and processing of both structured and unstructured data, these solutions minimize manual effort, reduce errors, and accelerate turnaround times. Open enrollment, in particular, benefits from intelligent data capture, and AI-powered automation streamlines workflows, enhances accuracy, and drives substantial cost savings.

Tangible Results:

Sagility developed an intelligent machine learning solution to help a client improve its Medicare Advantage (MA) plan’s Star Rating — a key metric directly linked to member experience. The team implemented a cognitive content processing workflow that leveraged an image analytics engine to handle source documents and a natural language processing (s) engine to analyze keywords and context, achieving the following results:

• Enabled an 8% weighted average improvement in Star Ratings for the MA plan, via the as-a-service solution
• Achieved quick and accurate decision-making with AI-powered data capture, addressing member resolutions and closing the loop on service issues
• Improved the plan’s selection experience for members, supporting better outcomes and higher satisfaction and enhancing Star Ratings

This case demonstrates how advanced automation and AI can deliver measurable improvements in both regulatory performance and member experience.

The healthcare landscape is at an inflection point. Declining member satisfaction scores and increasing employer scrutiny underscore the urgency for health plans to deliver more personalized, seamless experiences. AI-powered engagement, combined with intelligent automation and advanced analytics, offers a clear path forward — one that transforms every interaction into an opportunity to build trust, loyalty, and measurable value. By embracing these technologies, health plans can close gaps in understanding and service and create a future-ready model that meets the expectations of Generation C and beyond. Investing in AI-driven strategies today will define the member experience of tomorrow.