AI in healthcare statistics 2025
AI adoption rates have risen from 72 to 85% in just one year. In 2025, the share of healthcare organizations that already report moderate or high ROI reached 82%. What’s driving this rapid acceleration? We analyzed 28 trusted sources to uncover the key factors, emerging trends, and overall industry sentiment.
What’s Vention, and why do we care about artificial intelligence in healthcare?
Vention is a software development company with deep AI and healthtech experience. For over a decade, we've been crafting healthcare AI solutions, including computer vision-based medical imaging, speech recognition, medical chatbots, virtual assistants, and machine learning-powered predictive analytics.
We've teamed up with hundreds of healthcare players, including Thirty Madison and K Health, so we always stay on top of the latest trends in the healthcare industry to offer extra value to our clients and readers.
AI in healthcare market overview
The global AI in healthcare market is demonstrating steady growth. Although the estimates and projections of different market research firms vary slightly, they all agree on the strong double-digit growth.
Healthcare AI market size and CAGR (in billion USD)
2025
2030
Sources: [1], [3], [4]
In terms of geography, North America keeps dominating the AI in healthcare market, with a revenue share of 54%.
Key drivers of AI in healthcare adoption
Chronic diseases on the rise
By 2050, chronic diseases such as cardiovascular conditions, cancer, diabetes, and respiratory illnesses could account for 86% of total deaths. Overall, that represents a staggering 90% increase compared to 2019.
Rapidly aging population
The share of people aged 65 and older is expected to double worldwide between 2024 and 2074, reaching 20.7% of the global population by 2075. The number of people aged 80 and older is projected to increase by more than three times.
Workforce under strain
The global shortage of healthcare workers could reach 10 million by 2030, putting millions of patients at risk of delayed access to care. Even today, more than 75 million Americans lack access to primary care, and 122 million live in areas facing mental health provider shortages.
Globally, 73% of patients have faced delays in care, waiting an average of 70 days for an appointment. Wait times are especially long in Canada (131 days), Spain (128 days), and the UK (109 days). In the US, patients waited an average of 59 days. These delays carry serious consequences: one in three patients said their health worsened, and one in four eventually required hospitalization.
At the same time, the healthcare workforce remains under pressure. In 2025, a majority of physicians experienced burnout, although the proportion declined notably from 60% to 54%. 57% of physicians reported low well-being (up from 52% in 2024), which is a return to levels last seen in 2021, when the impact of COVID-19 was most pronounced.
AI-powered solutions can help ease the burden on health systems by streamlining administrative workloads and supporting clinical decision-making.
AI in healthcare adoption rates
In 2025, generative AI continues to gain momentum across healthcare. What began as cautious experimentation in 2024 has turned into a wave of practical applications, from automating clinical documentation to accelerating drug discovery and enhancing patient communication.
The share of healthcare organizations that have adopted or explored generative AI rose from 72% in Q1 2024 to 85% by the end of the year. The sector shows clear signs of maturity, with more organizations moving from proof-of-concept projects to full-scale deployment and embedding generative AI into everyday operations. As of early 2025, 70% of healthcare payers and providers are actively pursuing generative AI implementation, recognizing both the opportunities and the high expectations surrounding its impact.
of US healthcare organizations say AI is already redefining their operations.
expect it to reduce labor costs through automation.
of healthcare executives believe that organizations that embrace AI will develop a competitive edge over those who do not.
of pharma executives believe AI will drive new therapy discoveries in the next decade.
Vendors or in-house teams? How healthcare organizations approach AI development
In 2024, most healthcare organizations leaned on partnerships to implement generative AI. Reliance on third-party vendors inched up from 59% in Q1 to 61% in Q4. In-house development and off-the-shelf tools held smaller but steady shares (20% and 19%, respectively).
In 2025, the co-development model has become the dominant approach. Internal teams are increasingly collaborating with external partners to integrate AI into clinical and operational workflows. Notably, 64% of healthcare executives report being open to co-developing with early-stage partners, particularly startups that can demonstrate clear and measurable ROI.
Sources: [9], [10], [21]
High-impact use cases
In 2025, the top five AI applications in healthcare are: generative AI (71%), speech recognition (70%), agentic AI (68%), machine learning (66%), and robotics (65%).
Source: [24]
Administrative AI
35% of healthcare professionals claim they spend less time with patients than on administrative tasks, and 45% of healthcare professionals say this proportion is on par. It’s no surprise, then, that administrative AI is on the rise. In 2024, it attracted 60% of all healthcare AI investment, a trend carrying into 2025.
Among physicians, 68% report an increased use of AI for clinical documentation, striving for accurate recording and efficient management of patient information, while 36% note growth in administrative applications, such as scheduling, claims processing, and revenue cycle management.
57% of healthcare organizations identify reducing administrative burdens through automation as the most significant opportunity for AI adoption. AI-powered ambient scribes illustrate this shift in action, tackling one of the most time-consuming administrative tasks: clinical documentation. Their adoption is advancing rapidly: 30% of providers report system-wide deployments, 22% are in the implementation phase, and 40% are actively piloting solutions.
Sources: [6], [21], [25], [26]
Clinical AI
In our AI in healthcare report 2024, we’ve seen enthusiasm and high expectations that AI can:
- Reduce errors by up to 86%
- Potentially save 250,000 lives by 2030
- Boost physician time spent with patients.
In 2025, the expectations of the healthcare industry about gen AI’s potential are high, a sentiment that has carried over from 2024:
expect AI to improve patient outcomes
believe AI and predictive analytics can save lives through early intervention
of the surveyed healthcare executives are optimistic about gen AI improving access to clinical research
say it can expand capacity to treat more patients.
Clinical use cases are no longer theoretical. Radiologists detect lesions 26% faster and identify nearly 30% more cases with AI. Trials show faster heart scans and zero recalls, which helps screen 9% more patients.
The risks of delay in AI implementation are also clear. Healthcare AI professionals believe that slow AI implementation could mean missed opportunities for early intervention (46%), more clinician burnout due to administrative tasks overload (46%), and a growing backlog of patients (42%).
Sources: [6], [12], [13], [16], [24]
AI in drug discovery
AI has become one of the most transformative areas of healthcare innovation. In 2023, drug discovery represented the leading AI use case, accounting for 28% of the market and valued at $0.9 billion. By 2024, the market nearly doubled to $1.86 billion, with a CAGR of 29.9%, indicating growing investment and confidence in AI-driven research.
In 2025, 66% of life sciences executives report investing in generative AI to accelerate research and drug discovery, particularly in areas such as analyzing chemical interactions and identifying new protein structures.
AI has the potential to generate between $100 billion and $600 billion in healthcare savings by 2050. These savings would largely result from an increase in the number of approved medicines, which could reduce spending on hospital care and physician services. Estimates also point to a 10–40% faster approval rate for new drugs.
Sources: [2], [15], [27]
AI-enabled medical devices
By the end of May 2025, the FDA had approved 1,247 medical devices powered by AI and machine learning. Most of them are used in radiology (956 devices), followed by cardiovascular care (116), neurology (56), anesthesiology (22), and hematology (19).
Annual count of FDA-cleared AI/ML medical devices
1995–2017
2018
2019
2020
2021
2022
2023
2024
2025 (Jan-May)
Financial impact
Among healthcare organizations that actively track outcomes, 52% report moderate ROI, 30% report high or very high ROI, and 18% report low, break-even, or negative ROI. Notably, 45% of organizations using generative AI achieved a measurable return within 12 months.
69% of healthcare executives report pressure from shareholders to demonstrate clear returns on their AI investments. There's a clear understanding that ROI is not always immediate, as efficiency gains often come before direct financial results. 85% are pursuing AI initiatives even when returns remain uncertain.
Sources: [24], [28]
Concerns around AI adoption in healthcare
AI-related challenges remain, and in many cases, they’ve grown sharper. The top issues in healthcare include data quality (62%), workforce acceptance and AI skill development (47%), and compliance with strict regulatory requirements (42%).
Significant concerns exist regarding the potential loss of human interaction (61%) and overreliance on AI for diagnosis (58%).
Security, ethics, and risk remain major points of discussion. 72% of healthcare leaders are concerned about data privacy, not only in relation to cyberattacks but also about the profit motives of companies controlling AI systems.
Physicians share these concerns. Seven in ten express unease about ethical implications. 84% say they are as worried, or more worried than a year ago, about AI replacing medical judgment. 90% remain equally or more concerned about malpractice risks linked to AI-assisted diagnosis and treatment.
Both healthcare executives and frontline staff are calling for stronger oversight and inclusion. 80% of C-suite leaders support tighter regulation, and 73% of nurses believe they should be directly involved in building trustworthy AI tools.
Sources: [6], [9], [11], [14], [19], [21], [24]
The voices of patients
Surveys in 2024 revealed mixed feelings: eight in ten Americans recognized AI’s potential to improve care and lower costs, yet 60% felt uneasy about the idea of AI diagnosing or treating them.
By 2025, optimism has grown. 59% of patients believe AI can improve healthcare, and 73% say they welcome more technology if it enhances their care. However, 52% remain concerned that it could reduce the time they spend with doctors.
Sources: [6], [20]
The voices of healthcare professionals
Healthcare professionals feel more optimistic about AI than patients, showing an average confidence gap of 20%. The biggest differences appear in the following use cases:
- Documenting medical notes (87% confidence among healthcare workers vs. 64% among patients)
- Triaging patients to prioritize urgent cases (81% vs. 63%)
- Processing test results and scans (86% vs. 68%)
Nurses are especially eager to see greater AI adoption in their daily work. 64% support wider use of the technology, with enthusiasm spanning generations: 71% among nurses in their 30s and 60% among those aged 70 and older. When asked how working with AI makes them feel, 57% said they are hopeful it will enhance care quality and improve job satisfaction.
Sources: [6], [18]
Budgets for AI initiatives
For 60% of healthcare organizations, AI budgets are growing faster than overall IT budgets, and most leaders agree that funding is no longer the main barrier to scaling. The C-suite remains in control, making 70% of use case decisions.
The challenge now is to translate strong investment and executive momentum into sustainable, production-level results.
Sources: [21]
Investments
Digital health funding has remained resilient, with AI startups leading the momentum. In the first half of 2025, venture funding reached $6.4 billion, slightly above the $6 billion raised during the same period in 2024 despite fewer overall deals.
The decline in deal count was offset by larger deal sizes, with the average reaching $26.1 million as later-stage rounds gained strength.
AI continues to drive most of the activity. In 2025, AI-enabled healthcare startups captured 62% of all venture dollars ($3.95 billion), raised rounds 83% larger on average than their peers, and secured nine of the 11 mega-deals exceeding $100 million. Notable examples include Abridge ($550 million across two rounds in four months), Innovaccer ($275 million), Truveta ($320 million), and Hippocratic AI ($141 million).
Sources: [22], [23]
A note from Vention
Our focus is to give organizations engineering peace of mind. It begins with understanding where the industry is headed and what’s truly valuable, and it comes to life in real-world solutions built responsibly, working efficiently, and improving outcomes for patients and professionals alike.”
Check back often: We’ll be updating this page regularly. In the meantime, if you’re craving more AI adoption trends across other industries, check them out here.
Mikhail Dashuk
Engineering manager
List of sources
Sources
- AI in the healthcare market by MarketsandMarkets
- AI in drug discovery by MarketsandMarkets
- Grand View Research
- Fortune Business Insights
- United Nations Population Fund
- Future Health Index 2025 by Philips
- State of the US Health Care Workforce by the National Center for Health Workforce Analysis
- Healthcare workers: A critical shortfall by McKinsey
- Generative AI in healthcare: Adoption trends and what’s next by McKinsey
- Generative AI in healthcare: Current trends and future outlook by McKinsey
- Medscape & HIMSS AI Adoption by Medical Business Report 2024
- Journal of mHealth
- Clare Medical
- 2025 Global Health Care Outlook by Deloitte
- Accelerating Drug Discovery and Development by Deloitte
- The Guardian
- US Food and Drug Administration
- American Nurses Foundation survey
- University of Minnesota
- Pew Research Center
- Heathcare AI adoption index by Bessemer Venture partners, AWS, Bain & Company
- Fierce healthcare
- Rock health
- Intelligent healthcare: A blueprint for creating value through AI-driven transformation, KPMG International, 2025
- AI in healthcare: Patient and Physician Perspectives by United States of Care
- AMA survey
- Morgan Stanley
- 2025 State of AI Report by NVIDIA