Artificial intelligence is quickly becoming part of the clinical toolkit, but the conversation often centers on hype rather than how healthcare professionals themselves are actually using it. To ground the discussion, we fielded an AI in Healthcare Pulse Survey—asking front-line clinicians and leaders how familiar they are with AI, which tools they’re already using, where they see the most value, and what would build their trust going forward.
We heard from 113 healthcare professionals across 35 U.S. states, the vast majority (95%) working in direct patient care. Titles ranged from physician assistants and attending physicians to highly specialized experts such as pediatric surgeons, vascular surgeons, orthopaedic surgeons, fellowship-trained Mohs surgeons, and hematology/oncology physicians. This mix gives us a clear view into how AI is landing in real clinical environments today.
AI in Healthcare Pulse
How familiar are you with AI in healthcare?
Slightly familiar
53%
n=59
Very familiar
34%
n=38
Somewhat familiar
12%
n=13
Not familiar at all
1%
n=1
n=111 healthcare professionals • U.S. sample
Our take: Familiarity is now baseline—87% report at least some familiarity, and over a third are very familiar (34%). The task ahead isn't education; it's conversion: pair clear evidence of impact with EHR-native workflows so this awareness turns into habitual use. Messaging that connects everyday pain points (notes, in-basket, prior auth) to measured time savings will move the "slightly familiar" majority into regular users.
AI in Healthcare Pulse
Which AI-powered tools (if any) are you aware of or using?
Documentation assistants / automated note‑taking
73%
n=83
Clinical decision support (diagnostics; treatment recommendations)
52%
n=59
Predictive analytics (e.g.; risk stratification; readmission)
20%
n=23
Imaging interpretation (radiology; pathology)
20%
n=23
Patient chatbots / triage tools
19%
n=22
Other
5%
n=6
n=113 respondents to this question • Multi‑select (totals > 100%)
Our take: Awareness clusters around day‑to‑day workflow helpers—ambient documentation (73%) leads by a wide margin, with clinical decision support second (52%). A second tier—predictive analytics and imaging interpretation—sits near 20%, while patient chatbots trail at 19%. Respondents recognize about 1.9 categories on average, signaling breadth but with concentration where time savings are immediate. Messaging should anchor on documentation and CDS wins, then ladder into imaging/predictive use cases as trust and integration deepen.
AI in Healthcare Pulse
How valuable do you think AI is today in improving patient care?
Somewhat valuable
55%
n=61
Very valuable
35%
n=39
Neutral / unsure
7%
n=8
Not valuable yet
3%
n=3
n=111 respondents to this question
Our take: The value signal is decisive—90% see AI as at least somewhat valuable today, with over a third rating it very valuable. That's a green light for deployment focused on tangible wins (documentation, in‑basket, scheduling) where benefits show up quickly. To move the "somewhat valuable" majority into the "very valuable" camp, anchor rollouts in measurable outcomes (time saved, faster throughput, fewer clicks) and ship inside existing EHR workflows to minimize friction.
AI in Healthcare Pulse
Which area of healthcare do you believe AI will have the biggest positive impact in the next 3–5 years?
Reducing administrative burden
50.5%
n=56
Improving diagnostic accuracy
21.6%
n=24
Enhancing patient communication and engagement
16.2%
n=18
Predicting health risks and outcomes
10.8%
n=12
Other: don't know
0.9%
n=1
n=111 respondents to this question
Our take: The near‑term win is administrative—paperwork and clicks dominate expected impact (~51%). Diagnostics is a strong #2 (~22%), with patient communication and risk prediction forming a meaningful second tier. Roll out where ROI is immediate (admin burden), then extend into decision support and proactive risk tools as trust and integration deepen.
AI in Healthcare Pulse
If you could "hire" an AI assistant for one task tomorrow, which would you choose?
Drafting and organizing patient notes
48.6%
n=54
Managing patient communications and scheduling
18.0%
n=20
Assisting in diagnostic decisions
12.6%
n=14
Identifying high-risk patients early
9.0%
n=10
Summarizing the latest medical research
6.3%
n=7
Other
5.4%
n=6
n=111 respondents to this question
Our take: The single most sought‑after assistant is a note drafter (49%), followed by in‑basket & scheduling (18%) and assistive diagnostics (13%). "Other" write‑ins cluster around insurance admin (paperwork and eligibility/verification), summarizing/correcting past medical history with refill & preventive reminders, and automating follow‑up tasks from chart notes or patient answers; there's also one mention of screening/matching physician candidates and a single "don't know." The throughline: automate documentation first, then tame the inbox and routine admin to free up clinical time.
AI in Healthcare Pulse
What would make you most likely to trust AI in clinical practice?
Proven accuracy in studies
49.5%
n=55
Integration into existing workflows
21.6%
n=24
Transparency in how AI makes decisions
13.5%
n=15
Regulatory approval / FDA clearance
8.1%
n=9
Peer adoption and recommendations
7.2%
n=8
n=111 respondents to this question
Our take: Evidence rules—half of clinicians point to proven accuracy in studies as the #1 trust driver, with workflow‑tight integration next and transparency close behind. Notably, among regular AI users, transparency rises in salience, while occasional users over‑index on integration. The trust recipe is clear: publish validation with real‑world outcomes, ship EHR‑native experiences, and expose rationale/uncertainty so seasoned users can vet outputs quickly.
AI in Healthcare Pulse
Overall, do you believe AI will make patient care better or worse in the next decade?
Somewhat better
62.2%
n=69
Much better
31.5%
n=35
No real change
5.4%
n=6
Somewhat worse
0.9%
n=1
n=111 respondents to this question
Our take: Outlook is overwhelmingly positive—93.7% expect AI to make care better (31.5% "much better," 62.2% "somewhat better"). Only 0.9% anticipate deterioration, and 5.4% foresee no material change. That mandate favors near‑term, low‑risk deployments that deliver visible gains while building the evidence base for larger clinical lifts over the decade.
AI in Healthcare Pulse
Overall, what excites you most (or worries you most) about AI in healthcare?
What excites clinicians
“Reduction of busywork and improvement in diagnostic accuracy in radiology and other medical technology.”
Attending Physician • Illinois
“I am excited about potentially less provider documentation required to do my job.”
Physician Assistant • Washington
“Creating a workflow that allows providers to spend more time with patients while also creating improved accuracy.”
Oncology Physician Assistant • Pennsylvania
“The ability to improve patient outcomes and reduce administrative burden.”
Resident Physician • New York
What worries clinicians
“Concern that it will miss something critical or life‑threatening.”
Physician Assistant • Florida
“Errors worry me—or 'missing' something because I relied on AI.”
Physician Assistant • New Jersey
“Wrong diagnosis; duplication of record; errors; miscommunication.”
Attending Physician • New York
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