Customer Experience Platforms For Healthcare

Forrester's research into consumer attitudes toward AI in health insurance produced one figure that should concern every organisation in this market.

Comfort with public AI tools sits at twenty nine percent. Comfort with health insurer AI tools sits at thirty one percent.

Two percentage points. For questions about their own coverage, their own benefits, and their own bills, consumers regard a general-purpose chatbot as roughly as trustworthy as the company that holds their policy.

That indifference is the strategic problem this category exists to address, and Forrester states the consequence plainly: consumers will not wait for healthcare to catch up, and organisations that fail to act risk ceding influence and engagement to external tools that may give incomplete or inaccurate answers.

What these platforms do

A customer experience platform for healthcare sits between an organisation and the people it serves, handling the non-clinical experience that surrounds care.

For providers, that means appointment scheduling and reminders, digital front door navigation, intake and registration, billing and payment, care instructions, and follow-up.

For payers, it means benefits explanation, claims status, provider search, cost estimation, plan selection during enrolment, care navigation, and the engagement programmes intended to move members toward better outcomes and lower costs.

Zelis's Strong Performer citation in the current evaluation describes the payer version precisely: an integrated ecosystem helping health plans guide members toward lower-cost, high-quality care while improving satisfaction, cost transparency, and activation.

Note that the payer and provider use cases are related but not the same, and vendors specialise. A platform built around member cost transparency and plan navigation is solving a different problem from one built around appointment access and clinical follow-up. The category label covers both.

Inside The Forrester Wave: Customer Experience Platforms For Healthcare, Q1 2026

Published on 5 March 2026 and authored by principal analyst Arielle Trzcinski, the evaluation covers twelve providers across current offering, strategy, and customer feedback. The predecessor, published in late 2024, assessed vendors against thirty three criteria using market presence as its third dimension rather than customer feedback.

League placed as a Leader across strategy, current offering, and customer feedback.

Zelis placed as a Strong Performer, with Forrester evaluating its member engagement and transparency products and positioning it for health plans wanting a broad integrated ecosystem for guiding members on cost and quality.

The title Forrester gave its own commentary describes the market's condition: the AI race is on, but the pace is uneven. Some organisations are testing and learning, others remain stalled, and Forrester's assessment is that both delayed experimentation and reckless acceleration carry risk.

That framing is more careful than most analyst commentary on AI adoption, and it is appropriate to the sector. In most industries a bad chatbot answer is an annoyance. Here it can concern a treatment, a coverage denial, or a bill someone cannot pay.

Conversational AI stopped differentiating

Forrester's clearest finding for buyers is that conversational AI is now table stakes. Most vendors offer it in some form, so its presence tells you nothing.

What Forrester identifies as differentiating instead is narrower and more demanding. Solutions need to be reputable, trained, and explainable, capable of handling benefits, billing, and navigation questions safely when staff are unavailable. Its specific guidance is to choose a vendor with explainable models that cite sources.

Citation is the operative requirement and it is worth understanding why it matters more here than in most sectors.

An answer about a deductible, a prior authorisation requirement, or whether a specific provider is in network is not a matter of opinion. It is determined by a document: a plan design, a benefits schedule, a coverage policy. A system that produces the right answer without being able to show which document it came from has produced something the organisation cannot defend when challenged, and challenges in this domain arrive through appeals, complaints, and occasionally regulators.

Explainability here is not an ethical nicety. It is the difference between an answer a member services representative can stand behind and one they have to unpick.

The after-hours argument

Forrester's observation that patients increasingly seek help outside business hours points at the most legitimate use case in this category.

Healthcare administration operates on office hours. The questions do not. A parent working out at ten at night whether a paediatric visit is covered, a patient trying to understand a bill that arrived on Saturday, someone deciding whether a symptom warrants urgent care before Monday.

Historically the options were a call queue the next morning, a portal that answers only what its designers anticipated, or a search engine. Increasingly it is a general-purpose AI assistant, which is where the twenty nine percent comfort figure becomes strategically significant.

The organisation holds the authoritative information. The external tool holds the attention. If the member's plan documents, claims history, and provider network are not reachable by the interface they actually use, they will get an answer that is plausible, general, and frequently wrong about their specific situation.

That is the competitive case for this category, and it is stronger than the efficiency case that usually funds it.

Why this is harder than CX elsewhere

Several structural features make healthcare experience genuinely different from retail or banking experience, and they explain why a dedicated category exists rather than general CX platforms serving the sector.

The identity problem is layered. A person is simultaneously a patient of a health system, a member of a plan, a payer of a bill, and sometimes a caregiver acting for someone else. Those roles carry different data, different permissions, and different regulatory treatment, and a platform that models the individual as a single customer record will get access wrong in at least one direction.

The data is fragmented by design and by history. Electronic health records, claims systems, benefits administration, pharmacy, and billing sit in different systems with different identifiers, often across organisations that are commercially independent. Reported estimates put administrative costs at a substantial share of total healthcare spending, much of it attributable to reconciling exactly this fragmentation.

The regulatory constraints are strict and specific. Protected health information carries handling requirements that shape what can be processed where, by whom, and with what retention. In Europe, health data receives special category treatment under GDPR, which raises the bar again for any processing including automated decision support.

And the consequences are asymmetric. A wrong product recommendation costs a sale. A wrong answer about coverage or care access can delay treatment or produce financial harm, which is why Forrester's caution about reckless acceleration reads differently in this category than it would in another.

The uneven pace, and what it produces

Forrester's characterisation of an uneven race describes something worth naming for buyers.

The organisations moving fast are frequently the ones with the least regulatory exposure and the most commercial pressure, which is not the same as the ones where the technology would do the most good. The organisations stalled are frequently the largest and most complex, where the integration burden is heaviest and the risk tolerance lowest.

That produces a widening gap in experience quality that has nothing to do with quality of care, and it creates an odd dynamic where a member's experience of their insurer may be substantially better or worse than their experience of the health system treating them, for reasons neither controls.

It also means reference customers in this category need reading carefully. A vendor's successful deployment at a regional plan with clean data and a single system of record tells you limited amounts about what happens in an integrated delivery network with four legacy EHR instances from acquisitions.

What the platform cannot fix

The honest limitation of this category is that experience platforms sit on top of the operational reality rather than changing it.

If prior authorisation takes eleven days, a well-designed interface communicates an eleven-day wait clearly and pleasantly. If a bill is incomprehensible because the underlying pricing is incomprehensible, an explanation layer explains something the organisation itself struggles to justify. If the provider directory is inaccurate, a better search surfaces wrong information faster.

Forrester's framing of the market's direction, from transactional to trustworthy engagement, implicitly acknowledges this. Trust is not produced by interface quality. It is produced by the experience matching what was promised, which is an operational property.

The platforms that deliver value are the ones treated as instrumentation for the operation rather than as a wrapper around it. If the engagement data shows that a particular benefit generates disproportionate confusion, the useful response is to change the benefit design or the communication that precedes it, not to improve the chatbot's answer about it.

That requires the experience function to have influence over operations, which in most healthcare organisations it does not. Which is the same constraint that limits every category in this series, appearing here with higher stakes attached.

Forrester does not endorse any vendor named here, and tier placement should not be read as a recommendation to buy. This article discusses enterprise software for healthcare organisations and is not medical advice.