Americans will accept healthcare AI help—but want people making the final call
A Pew survey of 3,488 US adults found broad openness to AI for translation and scheduling, but much less appetite for autonomous diagnosis or insurance decisions. The findings measure public preferences, not clinical performance.
The short version
- What happened
- Pew surveyed 3,488 US adults in June 2026 using its probability-based American Trends Panel; the full-sample margin of error is plus or minus 1.8 percentage points.
- Who it affects
- Patients may accept AI assistance while still expecting a named person to remain accountable. Health providers need task-specific consent, review and challenge routes rather than a single blanket statement that AI is used.
- What remains unproven
- US adults only
Keep in mind
US adults only
Attitudes rather than observed behaviour
No AI system tested
No clinical outcome measured
June fieldwork released in October
3% cumulative panel response rate
English- and Spanish-language interviews
Asian adult estimates primarily represent English speakers
Question wording can affect responses
Source analysis · 2 linked sources. Primary analysed source date: 29 October 2026.
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Acceptance depends on the task—and who keeps responsibility
Americans were most receptive where AI could assist a bounded task. Seventy-eight per cent were open to it translating for a patient: 26% would accept AI acting alone and 52% wanted a person to review the result. Scheduling drew 73% combined openness. Higher-stakes decisions changed the balance. For diagnosis, only 3% accepted AI acting alone, 47% accepted it with final human review and 41% wanted no AI role. For insurance claims, the corresponding shares were 5%, 38% and 46%.[1]
Trust is the deployment problem clinicians cannot treat as a footnote
Sixty per cent said they would be uncomfortable if their doctor used AI for diagnosis or treatment, compared with 30% who would be comfortable. Views of health outcomes were almost evenly divided: 37% expected improvement and 36% expected harm. Half said AI would worsen the security of patient information, while 47% expected a worse patient-doctor relationship. For clinicians and health services, that makes disclosure, meaningful review and a clear route to challenge an output part of implementation—not an optional communications layer.[1]
The distinction that matters
How willingness changed with the healthcare task
The survey separated AI acting alone from AI whose output receives final human review.
Translation
26% AI alone; 52% with review
78% open
Scan analysis
6% AI alone; 60% with review
66% open
Diagnosis
3% AI alone; 47% with review
50% open
Insurance claim
5% AI alone; 38% with review
43% open
The sample is strong, but attitudes are not clinical outcomes
SSRS surveyed 3,488 members of Pew's probability-based American Trends Panel from 22 to 28 June 2026, online or by live telephone in English and Spanish. Of 4,069 sampled panelists, 86% responded; the cumulative response rate after recruitment nonresponse and attrition was 3%. Results were weighted to US population benchmarks, and the full-sample sampling error is plus or minus 1.8 points. Question wording, panel attrition and social expectations can still shape answers. Confidence about deployment would require separate evidence on diagnostic accuracy, patient outcomes, access, privacy incidents, workload and appeals.[1][2]
Watch the background, then check the evidence
Illustrative photo · not a video frame
The Royal Society · 44 min 28 sec · Background explainer
Is this the AI future we want? | The Royal Society
YouTube loads only when you choose; playback starts when you press play.
A Royal Society discussion with Madhumita Murgia and biomedical engineer Alison Noble on AI’s potential in healthcare, science and culture, recorded at the 30 June 2026 event.
Evidence check: A discussion of opportunities and risks, including future possibilities. It is not evidence that every application described is available or clinically proven.
Published 2026-07-01. Source checked 14 October 2026. Check captions on the publisher’s video page.
Check the healthcare evidencePhoto: Daniel Sone / National Cancer Institute / Unsplash · Licence
Continue the story
Read next
Continue exploring healthcare ai: compare the finding and its evidence limits.
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Read the next reportExplore the full source and evidence record
What this means for people
- Patients may accept AI assistance while still expecting a named person to remain accountable. Health providers need task-specific consent, review and challenge routes rather than a single blanket statement that AI is used.
Global context
The percentages describe US adults in a healthcare and insurance system with its own institutions, costs and trust patterns. They should not be transferred to other countries without locally representative research.
What the evidence does not yet show
- US adults only
- Attitudes rather than observed behaviour
- No AI system tested
- No clinical outcome measured
- June fieldwork released in October
- 3% cumulative panel response rate
- English- and Spanish-language interviews
- Asian adult estimates primarily represent English speakers
- Question wording can affect responses
What to watch next
- Patient outcomes from real deployments
- Task-specific consent and disclosure
- Human-review quality
- Privacy and security incidents
- Appeal and correction rates
- Comparable surveys outside the United States
- Changes in views after direct experience
Living evidence record
Impact record IAI-18YRL7W
Evidence stage
Announced
Confidence
Supported
Reporting basis
Source analysis
Independent or research support
Not yet
Record status
Monitoring
Last checked
31 October 2026
Source trail
2 direct sources across 1 source type.
People impact
Documented in this record.
Uncertainty
Limits and next checks are explicit.
Stages describe the evidence available—not whether a technology is good or bad. See the public method.
Related-source reporting disclosure
This record analyses 2 linked source records around the same underlying development. The extra records add method, date or context, but they do not by themselves constitute independent replication of every performance claim or predicted outcome.
Evidence trail
Sources used for this report
Links checked 31 October 2026
Research question, topics and regions
US adults' preferences and expectations for AI use in healthcare
Topics: Healthcare AI · Human oversight · Patient trust · Health privacy · Insurance decisions · Public opinion
Regions: United States · North America
This report is labelled source analysis. We summarise and analyse source material in our own words; company statements remain attributed claims until independently supported. Translated summaries preserve the meaning of the original source and link back to it. Read our editorial standards.
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