AI Is Moving Into the Front Door of Care
Forrester’s 2027 outlook describes a healthcare system drifting away from the familiar sequence of primary care visit, referral, testing and treatment. In its view, more than half of U.S. consumers will begin with public AI tools when they need medical guidance, turning chatbots and generative search into the first checkpoint for symptoms, medication questions and treatment decisions.
The shift is already visible. Pew Research Center data cited in the forecast showed that 34% of U.S. adults use AI chatbots for health-related reasons, and 25% use them to figure out what might be causing their symptoms. Those behaviors matter because they move early decision-making outside the clinic walls, long before a clinician has the chance to frame risk, confirm a diagnosis or steer a patient away from unsafe self-treatment.
Hospitals and physician groups are no longer competing only with neighboring systems. They are competing with the answer itself.
For health systems, the implication is blunt: visibility will increasingly depend on whether their content can be surfaced by generative engines and answer engines, not just by traditional search. If patients ask an AI model about chest pain, urinary symptoms or weight loss drugs, the organization that built the care relationship may never enter the conversation unless its information is easy to find, credible and machine-readable.
Insurers Are Pushing Toward Fixed-Cost Designs
Forrester expects five of the 10 largest health insurers to unveil alternative health plans by 2027, a response to another year of rising premiums. KFF has projected double-digit increases for marketplace and small-group customers, creating a market where price predictability is becoming as important as raw coverage breadth.
The model is straightforward. Plans such as UnitedHealthcare’s Surest and Health Care Service Corp.’s Easify Edge replace traditional deductibles with upfront, fixed costs. For patients, the appeal is easy to understand: fewer billing surprises and a simpler sense of what care will cost before the visit ever happens. For employers, the promise is administrative clarity. For insurers, these designs are a way to stay competitive as consumers grow more sensitive to complexity and out-of-pocket risk.
This is not just a benefit-design story. It is also a signal that patients want healthcare packaged more like a consumer service, with price transparency, predictable access and less reliance on post-service explanation.
AI Agents May Take Over Routine Check-Ins
Forrester also predicts that AI agents will handle 20% of routine care check-ins by 2027, including medication renewals, chronic disease monitoring, care navigation and wellness support. The forecast assumes that workforce strain will continue to limit the amount of low-complexity work clinicians can absorb manually, especially in systems already stretched by staffing shortages and rising demand.
A pilot in Utah involving Doctronic, where AI is being tested to renew and write new prescriptions, serves as an early example of how that shift could unfold. The interest from consumers is real enough to matter operationally: 41% of U.S. online adults are at least somewhat interested in receiving care from medically trained AI models, according to Forrester.
The practical challenge is not whether automation will expand. It is how safely it can expand without blurring the line between routine follow-up and nuanced clinical judgment. Medication refills, adherence reminders and symptom check-ins can be standardized. Escalation of red-flag symptoms, diagnostic uncertainty and multimorbidity cannot. Health systems will need governance rules, escalation pathways and reimbursement structures that keep complex patients attached to clinicians rather than letting them disappear into a machine-only loop.
GLP-1 Demand Is Rewriting Direct-to-Consumer Treatment
One of the most consequential predictions in the report centers on GLP-1 drugs. Forrester expects one in five Americans to take a GLP-1 by 2027, and it sees the direct-to-consumer model around these drugs spreading to other treatments.
The reason is behavioral as much as pharmacologic. Consumers are already learning that they can research medications on their own, obtain treatment through digital channels and receive drugs at home with less friction than traditional pathways require. More than half of adults surveyed by Forrester said they research medications before speaking with a physician, and one-fifth get medications delivered to their homes. Once patients experience that kind of access, their expectations for other therapies change as well.
The model is especially attractive for conditions where stigma, long wait times or scarce specialty access delay care. Forrester expects women’s health, dermatology and longevity care to be among the areas where digital-first options accelerate. Drugmakers are likely to follow the demand, increasing direct-to-consumer engagement and virtual care partnerships that reduce dependence on hospitals and clinics as the main gateway to treatment.
One health system already moving in that direction is Novant Health, which opened a virtual men’s health clinic to address erectile dysfunction and related sexual health concerns. Privacy and flexibility are not side features in this market; they are often the reason patients seek care at all.
At-Home Testing Could Deepen Health Inequity
The final prediction turns on a paradox. The same tools that expand access can also widen gaps.
Forrester expects 25% of consumers to regularly use at-home diagnostics by 2027 to verify health information from wearables, wellness programs and AI coaches. In a best-case scenario, those tools help patients catch disease earlier, confirm uncertainty and bring better data into the exam room. In a worse one, access concentrates among people with more money, more digital literacy and more ability to buy convenience.
That divide has direct clinical consequences. If higher-income patients are more likely to test early, monitor more often and act on results faster, prevention and early detection will tilt in their favor. Lower-income patients may remain dependent on delayed, episodic encounters and miss the moment when intervention would have been simplest.
Health systems can narrow that gap only if they treat home diagnostics as part of care delivery rather than a consumer novelty. Patients need pathways that explain what results mean, when to seek help and how to move from a home reading to a clinical decision without losing time or confidence.
The larger message running through Forrester’s forecast is unmistakable. Care is becoming more consumer-led, more algorithm-mediated and more fragmented from the traditional encounter model. Organizations that rely on patients finding them through old channels may discover too late that the first stop in healthcare has already changed.