100+ Latest AI in Healthcare Statistics Every Healthcare Leader Should Know

Sean Roy
Jun 28
10 min read

Key AI in Healthcare Statistics

Four in five physicians (81%) reported using AI in their practices in 2026, a significant increase from 38% in 2023.
In 2024, 71% of US hospitals reported using predictive AI integrated into their EHR, up from 66% in 2023.
Widespread AI adoption could unlock up to USD 360 billion annually in US healthcare savings.
The fastest-growing predictive AI uses in hospitals from 2023 to 2024 were automating billing (+25 points), facilitating scheduling (+16 points), and identifying high-risk outpatients (+9 points).
In Germany's PRAIM study of 463,094 women, AI-supported screening achieved a breast cancer detection rate of 6.7 per 1,000 - 17.6% higher than the 5.7 per 1,000 from standard double reading.
A large study of AI scribe use by 1,800 clinicians across five academic medical centers from 2023 to 2025 found those using the technology saved 16 minutes of documentation time per eight hours of patient care.
A 2025 study found 65.8% of US adults report low trust that health systems will use AI responsibly, and 57.7% have low trust that AI tools will not cause harm.

(Article Updated: June 2026)

AI in Healthcare Market Size & Growth

The global AI in healthcare market was valued at USD 14.92 billion in 2024 and is projected to grow to USD 21.66 billion in 2025 and USD 110.61 billion by 2030, a 38.6% CAGR.

The global AI in healthcare market is projected to grow to USD 110.61 billion by 2030, a 38.6% CAGR.

North America held a 42.6% share of the global AI in healthcare market in 2024.

North America accounted for the largest revenue share of over 54% of the global AI in healthcare market in 2025.

The global AI in healthcare market was valued at USD 36.96 billion in 2025 and is projected to reach about USD 613.81 billion by 2034 at a 36.83% CAGR.

The US AI in healthcare market is expected to grow from USD 7.72 billion in 2024 to USD 99.77 billion by 2033 at a 32.88% CAGR.

The generative AI in healthcare market is expected to rise from USD 2.65 billion in 2025 to USD 53.68 billion by 2035 at a 35.10% CAGR.

Medical imaging and diagnostics held about 30.40% of the AI healthcare market in 2025, while drug-discovery platforms are projected to grow fastest at a 42.91% CAGR through 2031.

The global conversational AI in healthcare market was estimated at USD 13.68 billion in 2024 and is projected to reach USD 106.67 billion by 2033 at a 25.71% CAGR.

The patient engagement & support segment accounted for the largest revenue share of over 29.51% of the conversational AI in healthcare market in 2024.

The global healthcare chatbots market was valued at USD 1.31 billion in 2024 and is projected to reach USD 8.5 billion by 2035 at a 16.89% CAGR.

Healthcare AI spending reached USD 1.4 billion in 2025, nearly tripling 2024's investment.

The healthcare industry is deploying AI at more than twice the rate (2.2x) of the broader economy, based on a 2025 survey of more than 700 healthcare executives.

The surge of healthcare AI activity produced eight healthcare AI unicorns by 2025, more than any other vertical AI segment.

AI Adoption Rates in Healthcare

Four in five physicians (81%) reported using AI in their practices in 2026, a significant increase from 38% in 2023.

Physician AI use reached 66% in 2024, up from 38% in 2023 - a 78% jump in one year.

The average number of AI use cases per physician rose to about 2.3 in 2026, up from 1.1 in 2023.

In 2024, 71% of US hospitals reported using predictive AI integrated into their EHR, up from 66% in 2023.

Among hospitals affiliated with multi-hospital systems, 86% reported using predictive AI in 2024, compared with only 37% of independent facilities.

Rural hospitals reported 56% predictive AI adoption versus 81% among urban hospitals in 2024.

The share of hospitals using AI for billing jumped from 36% to 61% between 2023 and 2024, while scheduling AI went from 51% to 67%.

31.5% of US hospitals reported current use of generative AI integrated into the EHR in 2024, with 24.7% planning adoption within a year, in a study of 2,174 hospitals.

22% of healthcare organizations have implemented domain-specific AI tools, a 7x increase over 2024 and 10x over 2023.

Health systems lead AI adoption at 27%, followed by outpatient providers at 18% and payers at 14%.

The share of healthcare respondents reporting gen AI implementation reached 50% for the first time in Q4 2025, up from 47% in Q4 2024 and 25% in Q4 2023.

In Q1 2024, more than 70% of healthcare organizations said they were pursuing or had already implemented gen AI capabilities.

Kaiser Permanente deployed Abridge's ambient documentation solution across 40 hospitals and over 600 medical offices, the largest generative AI rollout in healthcare history.

Mayo Clinic is investing more than USD 1 billion in AI across more than 200 projects.

A poll fielded April 8, 2025 found only about one in five (19%) medical group practices use some version of chatbot or virtual assistant for patient communication, while 81% do not and an additional 21% are considering adoption.

AI in Diagnostics & Clinical Outcomes

In Germany's PRAIM study of 463,094 women, AI-supported screening achieved a breast cancer detection rate of 6.7 per 1,000 - 17.6% higher than the 5.7 per 1,000 from standard double reading.

AI detects an estimated 20–40% of interval cancers that can be seen or suspected in retrospect on prior screening mammograms but were missed by radiologists.

In a retrospective study of 2,052 screening mammograms, a standalone AI system at 96% specificity identified 23.5% of interval cancers, with 76.9% correctly localized.

The UC San Diego COMPOSER AI sepsis model was associated with a 17% reduction in sepsis mortality in emergency departments, in a January 2024 study.

Duke Health's Sepsis Watch deep learning system was associated with a 27% reduction in sepsis deaths.

One prospective evaluation across 9 hospitals found that following implementation of an AI sepsis algorithm, in-hospital mortality fell 39.50%, length of stay fell 32.27%, and 30-day readmission fell 22.74%.

Viz.ai LVO implementation reduced stroke treatment time by an average of 31 minutes in a multicenter analysis of 474 patients.

A 2026 study showed a 44% reduction in door-in-door-out time for large vessel occlusion stroke patients with Viz.ai.

The Viz.ai platform is deployed in 2,000 hospitals across the United States.

In AI-assisted dermatology, AI assistance increased overall diagnostic accuracy but disproportionately improved accuracy for lighter skin tones, widening performance gaps.

AI-powered chatbots now handle initial patient inquiries in 42% of major healthcare networks.

Robot-assisted surgery currently has an overall success rate of 94% to 100%, with individual rates depending on procedure type and patient health.

In value-based settings, AI-enabled risk stratification can reduce hospital admissions nearly 30% by identifying high-risk patients earlier.

Generative AI & Clinical Documentation

In a UCLA Health randomized trial of 238 physicians across 14 specialties and 72,000 patient encounters, Nabla AI scribe users reduced documentation time by nearly 10% compared to usual care.

A large study of AI scribe use by 1,800 clinicians across five academic medical centers from 2023 to 2025 found those using the technology saved 16 minutes of documentation time per eight hours of patient care.

A 2025 multicenter study found ambient AI scribe use was associated with significant reductions in burnout, cognitive task load, and documentation time across six US health systems.

At Mass General Brigham, ambient AI scribe use was associated with a 21.2% absolute reduction in burnout prevalence (from 52.6% to 30.7%).

At Emory Healthcare, ambient AI scribe use was associated with a 30.7% absolute increase in documentation-related well-being in a 2025 study.

A Stanford pilot of an LLM-powered ambient AI scribe with 45 physicians found total EHR time decreased by 19.95 minutes per day in 2025.

AI-powered ambient scribes have reduced in-visit documentation time by approximately 20% and after-hours charting by 30%.

68% of physicians who use AI said their use of AI to help generate clinical documentation increased in the past year.

Fewer than 10% of patients declined AI scribe use in the UCLA Health randomized trial.

54% of care organizations report they have already implemented gen AI for clinical productivity, the most widely adopted domain, as of Q4 2025.

ROI, Cost Savings & Administrative Efficiency

Widespread AI adoption could unlock up to USD 360 billion annually in US healthcare savings.

AI could generate annual savings of USD 60 billion–120 billion for hospitals (4–11% cost reductions), USD 20 billion–60 billion for physician groups, and USD 80 billion–110 billion for private payers.

Among healthcare organizations implementing AI use cases, 64% report anticipated or realized positive ROI.

Administrative activities account for roughly 25% of total US healthcare spending of more than USD 4 trillion.

Excess administrative costs add an estimated USD 268 billion annually to the US healthcare system.

AI-leading payers could achieve 20% lower administrative costs or 10% lower medical costs than competitors.

Direct revenue tied to AI technology in healthcare was nearly USD 26.6 billion in 2024, still under 1% of total healthcare spend.

Annual cost savings from chatbots in healthcare were projected to reach USD 3.6 billion globally by 2022, up from an estimated USD 2.8 million in 2017.

The fastest-growing predictive AI uses in hospitals from 2023 to 2024 were automating billing (+25 points), facilitating scheduling (+16 points), and identifying high-risk outpatients (+9 points).

AI led all investment trends in 2024 with USD 124.3 billion in equity funding.

AI-discovered drugs achieve an 80–90% success rate in Phase I trials in a 2024 analysis, more than double the industry average of ~40–65%.

AI can reduce the traditional 10–15 year drug discovery process to as little as 1–2 years at a fraction of the cost.

The number of AI-discovered molecules entering clinical trials grew from 3 in 2016 to 17 in 2020 and 67 in 2023.

Clinician & Healthcare Workforce Sentiment

The belief that AI-enabled tools give physicians an advantage in their ability to care for patients grew from 65% in 2023 to 76% in 2026.

35% of physicians reported their enthusiasm for health AI exceeded their concerns in 2024, up from 30% in 2023, while those whose concerns exceeded enthusiasm fell to 25% from 29%.

57% of physicians surveyed in 2024 cited addressing administrative burden through automation as the top opportunity for AI.

The top attributes physicians said would advance AI adoption were a designated feedback channel (88%), data privacy assurances (87%), and EHR integration (84%), in a 2024 survey.

Nearly half of physicians said they would never or rarely want patients using AI to interpret radiology (46%) or pathology (49%) results, in a 2026 survey.

US physician burnout fell to 41.9% in 2025, down from 43.2% in 2024 and 48.2% in 2023, in a survey of nearly 19,000 physicians.

Physicians spend more than half their workday documenting in the EHR, with only about a quarter of time spent face-to-face with patients.

Clinicians spend nearly 28 hours per week on administrative duties.

Physicians complete an average of 39 prior authorizations weekly, spending 13 hours on the process, and 89% report it contributes to burnout, in a 2024 survey.

Physician burnout dropped nearly 10% in 2025, with AI use to address administrative burdens cited as a main driver.

As of Q4 2025, healthcare leaders most frequently cite administrative efficiency as the domain with the greatest potential for gen AI.

Patient Perceptions, Trust & Engagement

About one-third (32%) of US adults said they used AI chatbots for health information and advice in the past year, in a poll conducted February–March 2026.

29% of adults use AI tools for health information at least monthly, up from 17% in June 2024.

77% of adults are concerned about the privacy of personal medical information provided to AI tools, in a 2026 poll.

A 2025 study found 65.8% of US adults report low trust that health systems will use AI responsibly, and 57.7% have low trust that AI tools will not cause harm.

In 2025, 79% of healthcare professionals were optimistic AI could improve patient outcomes, but only 59% of patients shared that optimism.

Only 37% of consumers used generative AI for health purposes in 2024, down from 40% in 2023, with 30% citing a lack of trust in the information, in a survey of 2,000+ US adults.

Most consumers are comfortable with their doctors using gen AI to convey information about new treatments (71%), interpret diagnostic results (65%), and diagnose conditions (53%).

77% of US adults expressed willingness to use AI-assisted healthcare services, in a November 2024 poll.

59% of US adults believe AI-assisted diagnosis and treatment will significantly improve health outcomes within the next decade, in a November 2024 poll.

55% of adults age 50 and older had ever used AI technologies, but nearly half (46%) had very little or no trust in AI-generated health information, in a February 2025 poll.

80% of American consumers said they would be concerned knowing their healthcare provider was using generative AI, but that concern drops to 63% when the AI is from an established healthcare source.

Older adults (average age 71) are generally open to AI chatbots for appointment reminders (89%), emergency assistance (79%), and health monitoring (75%), in a 2025 study.

AI-powered hybrid chatbots can reduce hospital readmissions by up to 25% and improve patient engagement by 30%, in a 2025 systematic review.

FDA & Regulatory Approvals

The FDA's list of AI-enabled medical devices surpassed 1,300 devices as of early December 2025.

Radiology-specific tools account for nearly 80% of the FDA's entire list of approved AI devices, with 1,039 such tools as of December 2025.

The FDA cleared a record 295 AI/ML-enabled medical devices in 2025.

In 2025, the median FDA clearance time for AI/ML devices was 142 days, with 24% of submissions cleared in under 90 days.

Aidoc received the first FDA clearance of a foundation model-powered clinical AI device in February 2025 for rib fracture triage.

In late 2025, the FDA granted Breakthrough Device Designation to RecovryAI, an LLM-powered chatbot for joint replacement recovery - a first for generative AI in the device space.

Among hospitals using predictive AI in 2024, 82% evaluated it for accuracy, 74% for bias, and 79% conducted post-deployment monitoring.

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