AI chatbots in healthcare have seen explosive growth over the past year. According to Rock Health’s 2025 Consumer Adoption Survey, which surveyed 8,000 U.S. adults in December 2025, the share of Americans using AI chatbots for health information has doubled from 16% to 32%, nearly one in three adults. These consumers aren’t turning to their doctors, insurance portals, or even traditional health websites first. They’re going straight to AI-powered tools. And they’re not just asking once out of curiosity. 64% of these AI users engage with chatbots weekly for health questions.
Consumers aren’t waiting for the healthcare system to catch up. They’re already using AI to manage their health on their own terms, asking everything from “What do these symptoms mean?” to “Should I adjust my medication?” The tools they’re reaching for? Primarily general-purpose chatbots from large tech companies, not provider-or payer-offered solutions. Only 5% used provider-offered chatbots, and just 4% turned to payer-offered options.
This shows a growing gap between where consumers get health information and where they get care. As consumers arrive at clinical encounters already “AI-informed,” healthcare organizations need to decide whether they will build bridges to safely meet these empowered consumers or stand by as patients navigate an increasingly fragmented health information landscape alone.
Understanding How Consumers are Using AI in Chatbots in Healthcare
The AI user isn’t a passive information seeker; they’re what Rock Health calls a “healthcare superuser.” These consumers generate more data, track more health metrics, and engage more frequently across the entire care continuum. They’re asking sophisticated questions: 59% search for treatment options based on a diagnosis, 56% seek diagnoses based on symptoms, and 55% look up information about prescription drugs and side effects.
Consumers are using AI for everything from understanding lab results to finding in-network providers to deciding whether a symptom warrants urgent care, making no distinction between clinical questions and administrative ones.
The care journey is no longer linear. It’s not search, appointment, diagnosis, treatment anymore. Instead, it’s continuous, AI-mediated, and increasingly self-directed. Consumers are compressing what used to be fragmented stages, searching, interpreting, deciding whether to seek care or self-manage, into a more fluid, always-on process.
According to the survey:
Source: Rock Health’s 2025 Consumer Adoption of Digital Health Survey
Consumers are arriving at clinical encounters not just informed, but AI-informed and with specific expectations, pre-researched treatment options, and questions that assume a level of personalization the traditional healthcare system often struggles to provide.
Why Consumers Trust AI Chatbots in Healthcare More Than Organizations Realize
A trust shift is underway that healthcare organizations need to understand. While both AI users and non-users largely trust health information from clinicians (85% vs. 88%), AI users cast a significantly wider net. They report higher rates of trust in health information from digital sources: 55% trust health apps (compared to just 25% of non-users), 36% trust social media (vs. 11%), and 56% trust AI chatbots in healthcare themselves (vs. 15% of non-users).
Consumers aren’t abandoning their doctors, they’re expanding their health information ecosystem by getting value from more sources, on their own terms. AI offers personalization, immediate availability, and answers without judgment or wait times.
The data sharing patterns follow a similar trajectory. While healthcare providers remain the entity AI users are most willing to share data with, AI users show less willingness to share with their provider than non-AI users do (56% vs. 71%). The difference is that AI users are notably more open to sharing with non-traditional healthcare stakeholders: 23% would share with health tech companies (vs. 11% of non-users) and 15% with consumer tech companies (vs. just 4%).
This expanded trust comes with tradeoffs. Outside the traditional healthcare system, there’s no duty of care, no duty of confidentiality, and accountability structures vary widely. Consumers are exchanging some of the structured protections of the formal healthcare system for the immediate accessibility and personalization that AI provides. The question for healthcare organizations is how to meet consumers where they are while helping them navigate these tradeoffs more safely.
The Gap That Matters Most From Query to Action
If there’s one insight from the Rock Health data that healthcare organizations need to understand, it’s that the moment between AI query and clinical action is where safety, accuracy, and care quality are won or lost.
Consider what’s happening in that gap. After consulting a AI chatbots in healthcare:
Source: Rock Health’s 2025 Consumer Adoption of Digital Health Survey
That last statistic should make every healthcare leader pause. Nearly one in five AI users is adjusting medications based on chatbot guidance—outside any clinical supervision, without their provider’s knowledge, and potentially without understanding drug interactions, contraindications, or proper dosing.
But even the more benign actions carry risk. When consumers search for “more information,” are they finding clinically accurate sources or falling down rabbit holes of misinformation? When they try “new health behaviors,” are those evidence-based interventions or potentially harmful practices? When they finally do consult a provider, how much time is spent correcting misconceptions versus advancing care?
The path from question to next step is shortening. What used to take days, symptom onset, online research, appointment scheduling, clinical consultation, can now happen in minutes. AI turns information seeking into a continuous flow, and healthcare organizations that don’t build on-ramps into that flow risk becoming an afterthought rather than a trusted guide.
This is the gap that matters most, and it’s the gap the industry must urgently address.
What Healthcare Organizations Can Do Now
The market is already starting to organize around this evolution by owning the transition from insight to action. Healthcare organizations and tech platforms are racing to build on-ramps that make transitions from AI queries to clinical actions safer and more connected.
The strategy is to meet consumers where they are, but keep them within a clinically-validated ecosystem. Rather than fighting against consumer behavior or pretending it isn’t happening, forward-thinking organizations are building infrastructure to channel it safely.
This means offering AI experiences that consumers actually want, conversational, personalized, available 24/7, but embedding them within connected care environments where:
Clinical oversight is built in, not bolted on.
AI interactions need safety guardrails, appropriate escalation protocols, and clinical accuracy standards that general-purpose chatbots don’t have. This requires building with clinical experts from the start, not just tech teams.
The journey stays connected.
When a consumer asks a health question, they shouldn’t be sent off into the internet wilderness to piece together answers. They should stay in an environment where their data, care team, and care plan are all accessible. Insights should be contextualized. Recommendations should be personalized to their actual health history, and the path from question to action should be seamless.
Privacy and duty of care are maintained.
Consumers deserve the protections of the formal healthcare system—confidentiality, accountability, and clinical responsibility—even when they’re interacting with AI chatbots in healthcare at 2 AM. Organizations that can offer AI experiences within HIPAA-compliant, clinically-governed frameworks will earn the trust that general-purpose chatbots can’t.
Action is as important as information.
The real value comes from connecting answers to next steps. Scheduling appointments based on symptoms, surfacing longitudinal data to contextualize lab results, routing to pharmacists for medication questions, or triggering care team notifications when responses indicate urgent needs.
As Kristen Valdes, Founder and CEO of b.well Connected Health, states in the Rock Health report: “Patients are not going to stop using these tools because they’re filling a real gap. And even though AI isn’t perfect, medical error isn’t zero either. Humans are imperfect. The real question is whether this represents an incremental step forward. We have an obligation to make the technology better, and to do so in a responsible, thoughtful way.”
That obligation extends across the industry. Companies like Amazon are rolling out embedded AI experiences with tight connections to care linkages and escalation protocols. Quest Diagnostics launched a Google-powered AI companion that surfaces longitudinal test insights and prompts follow-up conversations with providers. b.well introduced bailey, a white-labeled conversational AI that routes users from AI-generated questions directly into care navigation. The common thread is that these aren’t standalone chatbots, they’re integrated experiences designed to keep consumers connected to their care ecosystem.
Redefining the Provider-Patient Relationship
The provider-patient relationship is evolving. Providers are increasingly encountering patients who arrive AI-informed, with specific expectations and pre-researched information. This requires a shift in the clinician’s role from primary bearer of health information to interpreter, validator, and contextualizer of information patients have already explored. Less gatekeeper, more guide.
This isn’t a diminishment of the provider’s role, it’s an elevation. When patients arrive having already done preliminary research, providers can spend less time on basic information delivery and more time on nuanced clinical judgment, shared decision-making, and the human elements of care that AI can’t replicate. This only works if the information patients bring to the encounter is accurate, contextualized, and connected to their actual care plan.
That’s where healthcare organizations have both an opportunity and an obligation. By offering AI experiences embedded within the care ecosystem, organizations can ensure that when patients arrive “AI-informed,” they’re informed with accurate, personalized, clinically validated information, not whatever AI chatbots in healthcare happened to generate in isolation.
The Rock Health report frames this moment as a race between the tortoise (institutional AI adoption, measured and risk-managed) and the hare (consumer AI adoption, fast and largely self-directed). Success means keeping these forces in balance, ensuring always-on availability doesn’t outrun standards of care, and clinical rigor, privacy, and safety keep pace with consumer momentum.
The Choice Ahead
Consumer AI adoption is here, and it’s accelerating. The 32% of Americans who have used AI chatbots in healthcare will reach 40%, then 50%, and eventually become the majority. The generational gradient shows that 45% of Gen Z adults and 48% of Millennials are already using AI for health questions. As these digital-native generations age and represent larger shares of the patient population, AI-mediated healthcare will become the norm, not the exception.
Healthcare organizations have a choice. They can treat this shift as a threat, something to warn patients against, something to compete with, something to ignore until it becomes unavoidable. Or they can treat it as an opportunity to meet empowered consumers where they are, with tools that channel their curiosity into safer, more connected care experiences.
The organizations that will thrive in this new landscape are those that understand that the future isn’t about choosing between consumer empowerment and clinical excellence. It’s about building bridges that make both possible.
The AI-empowered consumer has already left the starting line. The question is whether healthcare will build the infrastructure to meet them where they’re going, or watch them navigate the journey alone.
