Connecting consumers with in-network, clinically-appropriate, and high-value care providers via AI-ready architecture
As health plans work to meet rising consumer demands and deliver a more personalized care experience, artificial intelligence (AI) is becoming more embedded in the consumer digital experience from the call center to the authenticated portal. However, in the context of care access the promise of AI can’t be realized without addressing challenges with inaccurate and inconsistent provider data. The future of agentic navigation for member engagement needs to be grounded in a golden record of truth containing accurate provider, cost and clinical data. Misaligned data between payers and providers is contributing to eroding member trust, creating costly inefficiencies, and slowing the adoption of AI tools that could help streamline care guidance. While leaders are eager to implement AI, the foundational issues in data need to be addressed for AI implementations to be successful.
In addition, the cost of these solutions is often unsustainable and comes with concerns of increased risk and hallucinations. Health plans seek the power of AI, but need to ensure the experience provides the most clinically relevant, in-network and high-impact care options, while still being economically efficient.
To compete with retail-forward health plans and meet the tightening 2027 CMS mandates, leaders must break down the silos between provider, program, and cost transparency data and expose this unified data with modern, standardized protocols such that AI tools can access it. By making the golden record data accessible in a format AI understands, plans have an opportunity to deliver proactive, personalized, high-value guidance that drives member loyalty, high-quality outcomes, and higher affordability for members, employers, and plans.
The cost of inaccurate provider data: shifting AI to a sustainable strategic asset
Provider data continues to contribute to friction for health plans and consumers alike. Recent data shows that over 85% of health plan leaders struggle with inaccurate or outdated provider data, and 19% of provider data is considered unreliable and unusable. Data around locations, programs, benefits and cost estimations for providers live in various locations across the organizations, so accessing the data and merging it into a single source of truth can be challenging. Most health plans, about 77%, are still updating their directories manually on a regular basis.
This data highlights a growing problem, and one that has real consequences for members. While consumers have a low tolerance for inaccurate provider data and care costs, the experience of encountering inaccurate data is common. Four in ten consumers reported finding inaccurate provider information on their health plan’s website, with over 77% of consumers saying these kinds of errors impact their trust in their health plan. Even more concerning, many consumers respond by avoiding or delaying care. Thirty percent of all consumers, and 44% of Gen Z members, have postponed care or fully skipped it after finding inaccurate provider information online.
When members can’t easily confirm which doctors are in-network or accepting new patients, their care journeys become fragmented. This doesn’t just create friction for consumers and health plans in the moment but has lasting impacts on patient care journeys. Improving provider data to ensure it’s more easily accessible can improve downstream impact on patient engagement, satisfaction, and care outcomes. Further, the health plan search experience is limited in the available actions for members to take, forced to leave the plan experience to book an appointment or pay a copay. The opportunity to influence their care selection decision is lost in this process. Members shouldn’t have to find a provider and then seek out an action elsewhere; rather it should be a full stop experience where they can take the next step immediately.
Navigating AI’s role in driving care guidance, and the growing implementation gap
Despite these challenges, 100% of the surveyed executives agreed that AI will be critical to network strategy going forward. A majority expect automation to play a key role in provider data management in the future and most believe AI will significantly strengthen member guidance.
Though leaders seem to have strong encouragement on AI’s position in the space, adoption lags. While 91% of leaders believe AI will meaningfully enhance how members are guided to care, only 16% report using AI widely for the process of directing patients to in-network physicians today.
The disconnect is not from lack of belief in AI’s value, but likely from a prioritization of investment in fundamentals to ensure AI’s success in the space. Health plans’ top priorities over the next two to three years include improving provider data accuracy, strengthening collaboration with providers, and advancing personalized member experiences. This prioritization reflects an intentional order that acknowledges how messy, unreliable data can stand in the way of the potential for automation in health care. The quality of AI outcomes is only as strong as the data that feeds them, and leaders have recognized this in their implementation strategy. Additionally, using AI to source data on providers and care programs has the potential to increase risk, cause AI hallucinations and come with a hefty cost. Models need to be grounded in a golden record: a strong source of truth containing validated, trusted data on providers, locations, care programs, and costs. This careful process would allow for increased accuracy, personalization for members, and reduced costs around implementing AI agents.
Building the foundation for AI-driven care guidance
The path forward requires addressing data accuracy, which in turn will help build member trust and drive AI enablement. By unifying these efforts, health plans can convert AI’s promise into measurable member impact.
Implementing an integrated strategy across provider data, AI and the member experience can help plans modernize data infrastructure and address the root cause of challenges. Plans need to be able to aggregate and standardize provider information across sources, verifying that the data is accurate and isn’t missing any information. AI can help to translate data, flag discrepancies and contribute to the infrastructure that builds payer-provider interoperability and creates a more seamless member experience, as well as build upon data by surfacing opportunities for enrichment and augmentation.
Further, powering this actionable member experience requires clean data that moves members to act. Health plans can combine real-time provider data with actionable, dynamic features, including surfacing appointment availability, enabling click-to-schedule capabilities, displaying in-network options clearly, and weaving in benefit details and supplemental programs. The goal is to allow members the ability to easily research and make decisions about their care to help them take the next steps in their care journey, reducing friction while encouraging engagement. All of this data needs to be accessible in industry-standard formats, like Model Context Protocol (MCP), with a demand for new infrastructure to support the next decade of health care commerce.
Agentic AI can help analyze and predict patterns in member behavior, anticipate needs, and recommend the next steps. This helps to move plans from a reactive approach to a proactive, coordinated system that drives the best next action. As plans adopt this approach, AI doesn’t just support navigation but becomes a tool to deliver personalized care.
Quality data driving outcomes
The industry is at a defining moment. Health plan leaders recognize the importance of AI to provide strategic care guidance, but they also understand that its success depends on quality data and deeper collaboration with providers. Prioritizing accurate provider information can help drive more successful AI adoption, in turn, elevating the member experience that helps plans move from crisis to control, reducing costs, improving guidance, and rebuilding trust in member engagement.
About Morgan Beschle
Morgan Beschle is the Vice President of Product at Kyruus Health, a RevSpring Company. She has over 18 years of experience as a digital health leader with a demonstrated track record of building innovative, scalable health care technology to improve quality while reducing costs.
