Gartner’s Hype Cycle for U.S. Healthcare Payers, 2026 maps the technologies shaping payer operations, member experiences, and long-term investment. For payer leaders, five categories stand out: AI service assistants, digital brokers, no-code agent builders, intelligent enrollment onboarding, and large language models. Ushur is named a Sample Vendor in all five.
Together, these categories span the full member journey, from choosing a plan to enrolling to getting ongoing help. Our view is that payers should judge them by real outcomes, not activity: requests resolved, enrollments completed, and manual follow-up eliminated. This article explains what each category does, how Gartner rates it, and how payers can connect them to deliver completed journeys rather than faster individual interactions.
Key Takeaways
- Five categories, one member journey. Ushur is named a Sample Vendor in AI service assistants, digital brokers, no-code agent builders, intelligent enrollment onboarding, and large language models, which together cover plan selection, enrollment, and ongoing service.
- Start where value is near-term. Gartner points to AI service assistants and intelligent enrollment onboarding as candidates for pilots now, and to no-code agent builders as a foundation for scaling AI. Gartner rates no-code agent builders and large language models as transformational.
- Measure completed journeys, not faster interactions. Track requests resolved, enrollments completed, and manual follow-up eliminated, not just speed or call deflection.
- Governance makes scale possible. Clear controls over data access, system actions, and human review are what let payers expand AI beyond a single pilot.
Why Are Healthcare Payers Reassessing Their AI Investments?
Healthcare payers are under sustained pressure to manage costs, improve service, and respond to regulatory requirements. At the same time, advances in AI are expanding what organizations can automate and how quickly they can introduce new capabilities. The challenge is deciding where those capabilities will make a meaningful difference.
A faster answer can improve an interaction. But if a member still needs to call another department, repeat information, or complete the same request elsewhere, the underlying service burden remains.
Gartner’s 2026 research gives payer leaders a framework for considering both immediate opportunities and the foundational investments needed for broader AI adoption. For business and technology teams, that means connecting each investment to a specific operational problem and a measurable outcome.
What Is the Gartner Hype Cycle for U.S. Healthcare Payers?
The Gartner Hype Cycle evaluates technologies relevant to healthcare payers, including their maturity, adoption, potential benefits, and obstacles to implementation.
Its accompanying Priority Matrix considers two related questions: how much value a technology could deliver and how long it may take to reach mainstream adoption.
These perspectives help organizations distinguish between technologies suited to focused experimentation and those requiring longer-term preparation.
A technology’s position does not establish whether it is the right investment for an individual health plan. That decision also depends on the organization’s workflows, data readiness, integration requirements, and ability to manage change.
Why Disconnected Automation Falls Short in Healthcare Payer Operations
Many payer processes span multiple teams, systems, and customer interactions. Improving one step can leave the rest of the journey unchanged.
An enrollment experience may explain benefits clearly but still require manual follow-up for missing information. A service assistant may retrieve a policy detail while leaving an employee to update another system or coordinate the next action.
Common sources of friction include:
- Repeated information collection across channels
- Manual searches across disconnected systems
- Incomplete submissions that require additional outreach
- Transfers that lose the context of the original request
- Limited visibility into whether the member’s need was resolved
Our view is that healthcare payer AI should be evaluated against these gaps. The practical question is how much of the underlying work the solution can complete, within the controls that the organization requires.
Five Healthcare Payer AI Categories to Understand
The five categories in which Ushur is named as a Sample Vendor address different parts of payer operations. Together, they offer a useful way to examine adoption opportunities across acquisition, enrollment, service, and AI development. Here is how Gartner rates each one.
1. AI Service Assistants for Payers
AI service assistants support interactions with members, providers, and purchasers. Gartner describes capabilities such as guidance during an interaction, recommended next actions, summaries, and automation of simpler service requests.
For payer contact centers, the opportunity includes reducing manual searches and administrative work while helping employees deliver more consistent service.
The report also emphasizes the importance of balancing AI and human support. Members should have access to the right assistance for their situation, particularly when a request is complex or requires judgment.
Payers evaluating this category should establish the service outcomes they want to improve, such as wait times, first-call resolution, or cost per interaction, before selecting a solution.
2. Digital Broker
Digital broker solutions support plan selection and enrollment by collecting information, answering questions, and helping purchasers understand their options.
Gartner positions this category around more scalable digital distribution. The report also identifies challenges involving trust, explainability, security, and the relationship between digital and human sales channels.
For payer leaders, the practical consideration is where digital assistance can reduce friction without removing the support that purchasers need.
A straightforward plan question and a complex benefits decision may require different experiences. The technology should help organizations serve both appropriately.
3. No-Code Agent Builders for Payers
No-code agent builders provide an environment for creating and managing AI agents without exposing code to the builder. Gartner identifies their potential to help business and IT teams develop solutions across payer administrative and service workflows.
The value extends beyond faster configuration. Teams closest to the operational problem can participate more directly in designing, testing, and improving the experience.
That participation still requires enterprise controls. The report recommends assessing AI readiness, establishing governance, and providing controlled environments where teams can experiment before moving agents into production.
For healthcare payers, no-code development should make it easier to improve workflows while keeping data access, system actions, and accountability clearly defined.
4. Intelligent Enrollment Onboarding
Intelligent enrollment onboarding supports members before and after enrollment, helping them understand benefit options and use their coverage.
Gartner identifies opportunities to reduce duplicate outreach, improve data handling, and create more consistent onboarding experiences.
This is a particularly important point in the member relationship. Confusing instructions, missing information, and disconnected communications can create avoidable service demand before members have used their benefits.
An effective onboarding experience should help members complete the necessary steps and understand what comes next. Payers should also account for differences in insurance literacy, contact information quality, and preferences for human assistance.
5. Large Language Models for Healthcare Payers
Large language models support applications that generate content, summarize information, and organize data across payer workflows. Gartner identifies uses such as member and provider communications, medical record summaries, and benefits information management.
For payer teams, the opportunity includes reducing manual review and making information easier to access and use. These capabilities can support both employee decisions and member-facing interactions.
Their value depends on the quality of the underlying data and the controls surrounding deployment. Payers should assess accuracy, privacy, and human review requirements before expanding use across workflows.
The report recommends aligning data strategies with AI readiness, understanding member perceptions, and establishing governance that supports safe LLM use.
How Do These Five AI Categories Work Together?
Members don’t experience these categories separately. They experience one relationship with their health plan, from choosing coverage to enrolling to getting help, and each category supports a different part of that journey:
- Digital Broker helps purchasers compare plans and select coverage.
- Intelligent Enrollment Onboarding helps new members complete enrollment and understand how to use their benefits.
- AI Service Assistants for Payers resolve ongoing questions and requests from members, providers, and purchasers.
- Large Language Models for Healthcare Payers provide the language understanding and summarization these experiences rely on.
- No-Code Agent Builders for Payers let business and IT teams build, govern, and improve the agents behind all of them.
The value comes from connecting them. When information a member provides during plan selection carries into enrollment, and enrollment data informs later service, members stop repeating themselves and fewer requests stall between teams. That is why Ushur’s view is that payers should measure AI by the journeys it completes, not by the speed of any single interaction.
Compliance, Security, and Governance in Healthcare Payer AI
Across the report, governance is closely connected to the ability to realize value from AI.
Healthcare payer workflows involve sensitive information and actions that can affect members, providers, and purchasers. As AI takes on more responsibility, organizations need clear boundaries around what it can access, decide, and execute.
Key considerations include:
- Protection of member and provider information
- Access controls appropriate to each role and workflow
- Traceable actions and decisions
- Defined conditions for human review
- Monitoring of accuracy and operational performance
- Ownership of changes to agents, data, and integrations
Gartner also highlights the need for collaboration between business and technology teams. Operations, customer experience, security, legal, and compliance stakeholders should help define the requirements for deployment.
Governance is most useful when it becomes part of how teams build and operate AI, with clear guardrails that support controlled progress.
How AI Can Improve Member Engagement From Enrollment to Service
The categories in the report address different functions, but members experience them as parts of one relationship with their health plan.
Information collected during enrollment can influence later communications. A benefits question may reveal that a member needs help finding a provider. An incomplete submission may require targeted outreach before a request can move forward.
For payers, this creates an opportunity to connect proactive engagement with responsive service.
Relevant journeys include:
- Helping new members complete onboarding requirements
- Explaining benefits and answering follow-up questions
- Collecting and validating information needed for a request
- Sending reminders when an action remains incomplete
- Connecting members to human assistance with the relevant context
Our view is that journey continuity should be an evaluation criterion in its own right. Faster individual interactions are useful, but the larger benefit comes when members can move toward resolution without restarting the process.
Medicaid redetermination illustrates this need for connected engagement. Outdated contact information and fragmented communications can make it harder for members to complete renewal requirements. Ushur’s Voice-Guided Experience for Medicaid Redetermination keeps Medicaid members on a live AI-guided call while they review and update contact details and confirm communication preferences through a synchronized, secure mobile interface. This helps plans maintain accurate information for renewal outreach, reduce manual follow-up, and guide members through critical redetermination steps.
Integration Into Healthcare Systems and Workflows
AI needs access to the information and systems required to perform its assigned work.
For healthcare payers, relevant connections may include enrollment platforms, claims systems, customer relationship management tools, provider directories, and document repositories.
Integration requirements should be assessed at the workflow level. Retrieving a benefit detail, updating contact information, and submitting a service request involve different permissions and system actions.
Payers should establish:
- Which systems hold the information the agent needs
- Whether the agent can only retrieve data or also update it
- How information is validated before an action occurs
- What happens when a system is unavailable
- How employees review exceptions and incomplete requests
These details determine whether AI becomes part of the operational process and whether the experience can reliably progress toward completion.
What the Next Chapter of AI Adoption Requires
Gartner’s 2026 Hype Cycle includes technologies that support service interactions alongside platforms for building and coordinating AI agents. This creates two connected priorities for healthcare payers: identifying useful applications today and establishing the capabilities needed to expand them.
AI service assistants and intelligent enrollment onboarding offer opportunities for focused deployments. No-code agent builders and other foundational technologies can support broader adoption, with different maturity levels and implementation requirements.
A focused deployment should also establish practices the organization can reuse, including system integration, performance monitoring, employee training, and human oversight. The experience gained from one workflow can then inform where and how to expand.
How to Evaluate AI Solutions for Healthcare Payers
Technology maturity is one part of the evaluation. Payers also need to determine whether a solution fits their operational environment and the experience they want to deliver.
Organizations should prioritize:
- A clearly defined business or service outcome
- Integration with the systems required to complete the work
- Appropriate data protection and governance controls
- Reliable handling of incomplete information and exceptions
- Human escalation that preserves relevant context
- Participation from the employees who will use or oversee the solution
- Measurement that connects performance to business value
A pilot should have a clear starting point, completion condition, and baseline.
For example, an enrollment initiative might measure completed submissions, manual follow-up effort, and time to completion. A service initiative might track resolution, repeat contacts, and employee effort alongside interaction speed.
These measures help establish whether the investment improves the overall process.
How Ushur Helps Healthcare Payers Put AI Into Practice
Ushur is an agentic CX automation platform purpose-built for regulated industries. Its AI agents bring together customer conversations, information collection, document handling, and actions across connected systems to help complete customer journeys.
For healthcare payers, that means evaluating AI around the work a member needs to finish, from completing onboarding requirements to moving a service request toward resolution.
Ushur’s approach combines:
- Goal-based AI agents that carry out multi-step journeys
- No-code capabilities for building and managing experiences
- Proactive outbound and reactive inbound engagement
- Enterprise integrations that connect interactions to operational systems
- Governance, auditability, and human oversight built into the platform
The five categories featured in the report provide useful perspectives on that opportunity. They connect the way payers build AI experiences with the ways purchasers select coverage, members complete enrollment, and service teams respond to ongoing needs.
For organizations evaluating their next investment, the objective is to identify where these capabilities can remove friction and produce a measurable improvement in service.
Conclusion
Gartner’s research highlights practical opportunities for healthcare payers to use AI to reduce administrative work, improve service, and support member journeys. AI service assistants, digital brokers, no-code agent builders, intelligent enrollment onboarding, and large language models offer different paths toward these goals.
Successful adoption depends on reliable integrations, clear ownership, and governance that keeps data access and system actions accountable. These foundations help payers expand AI use while maintaining the controls their workflows require.
The next chapter of AI adoption will be measured in completed requests, reduced manual effort, and better member and provider experiences. For healthcare payers, the path forward is to start with a defined operational need, demonstrate value, and use that evidence to guide expansion.
Explore the Gartner Hype Cycle for U.S. Healthcare Payers, 2026.
Frequently Asked Questions About AI for Healthcare Payers
How can AI improve healthcare payer operations?
AI can automate routine service requests, collect and validate information, and coordinate enrollment workflows, reducing manual work while helping members and providers complete their requests.
Why are healthcare payers investing in agentic AI?
Rising administrative costs and service demands are driving payers to adopt AI that can execute multistep workflows, support employees, and deliver more consistent member experiences.
How do AI service assistants differ from no-code agent builders?
AI service assistants provide guidance and automate service interactions, while no-code agent builders enable teams to design, deploy, and manage the agents that perform this work.
Where should healthcare payers begin with AI adoption?
Member service and enrollment support offer practical starting points, with defined workflows and measurable opportunities to reduce follow-up, improve completion, and ease administrative workloads.
What should healthcare payers evaluate before deploying AI agents?
Payers should evaluate integration, data quality, security, and governance, alongside the agent’s ability to complete tasks reliably and involve human teams when needed.
What five categories is Ushur recognized in?
Ushur is named a Sample Vendor in five categories in the Gartner Hype Cycle for U.S. Healthcare Payers, 2026: AI Service Assistants for Payers, Digital Broker, No-Code Agent Builders for Payers, Intelligent Enrollment Onboarding, and Large Language Models for Healthcare Payers.
Source: Gartner, Hype Cycle for U.S. Healthcare Payers, 2026, Connie Salgy, Austynn Eubank, Robert Potts, Faith Adams, 4 June 2026. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and HYPE CYCLE is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.