AI in Healthcare - Quick Overview Statistics

Artificial Intelligence in healthcare refers to the use of advanced computer algorithms and machine learning techniques to analyze data in the healthcare sector to provide better healthcare services.

AI helps healthcare providers make more accurate and real-time diagnoses, personalize treatment plans, and improve patient safety by identifying health risks earlier.

Types of AI Applications in Healthcare Statistics

• Medical imaging analysis
• Natural language processing (NLP)
• Disease prediction and risk assessment
• Virtual Assistants and Chabot’s
• Drug discovery and development
• Robot-assisted surgery
• Patient engagement
• Diagnosis and treatment
• Machine learning

AI in Healthcare Statistics: AI in healthcare has been a hot topic for the past few years, and the report says that the industry is expected to reach $187.95 billion by the end of 2030. The fact of this platform in 2023 suggests a huge boom in the market size worldwide, with a compound annual increase rate (CAGR) of 40.1% from 2023 to 2030. The worldwide Artificial intelligence in the healthcare marketplace length changed into worth $20.65 billion in 2023 which has increased from last year. These AI in Healthcare Statistics include insights from various aspects and sources that will provide effective light on the importance of AI in the healthcare industry around the world in recent times. In 2023, the Market share records the gradual adoption of AI which is advancing the sector, and has been observed that 85% of organizations have already implemented AI. Additionally, 1/2 of the executives claimed that AI is indicating a tremendous shift inside and outside the industry. Aid of AI-based healthcare companies used solutions like telemedicine and remote tools and sensors backed by means of large information that can reduce healthcare charges improve access, and promote better outcomes, and performance. Key Takeaways According to AI in Healthcare Statistics, the platform when implemented Artificial Intelligence has experienced a huge increase, with a CAGR of 40.1% from 2023 to 2030 and a global market size expected to attain $187.95 billion by 2030. Around the world, approximately 40% of healthcare industries are regularly using AI and Machine Language in the sector. In 2023, Healthcare executives are increasingly adopting AI in their techniques, and nearly 1/2 of the executives surveyed are already using it. This is being adopted globally, with answers like telemedicine and faraway tools and sensors backed through huge information that could lessen healthcare charges and equitably improve admission to, results, and performance.

This statistic shows the global market size for artificial intelligence in healthcare in 2016, 2017 and a forecast for 2025. It is estimated that over this period the market will increase from roughly one billion to more than 28 billion U.S. dollars.

Introduction

AI in Healthcare Statistics: Artificial intelligence (AI) is swiftly reshaping the healthcare sector, transforming areas such as diagnostics, treatment planning, patient management, and drug development. By analyzing large volumes of data and delivering precise insights, AI is boosting clinical decision-making, enhancing patient outcomes, and optimizing healthcare operations.

Key advancements in machine learning, natural language processing, and other AI technologies are propelling this shift, with healthcare systems worldwide increasingly adopting these innovations to improve efficiency and offer more personalized care. The ongoing potential of AI to refine healthcare delivery is reshaping the industry's future.

In 2024, the size of artificial intelligence (AI) in the healthcare market in India reached *** million U.S. dollars. It was estimated that in 2025 the value would increase to substantially around *** billion U.S. dollars. The integration of AI is a turning point for medical research, diagnosis, and treatment in India.

According to a study conducted globally in 2022, ** percent of people surveyed stated that they are willing to trust the application of AI in healthcare for diagnosis and treatment, while a further ** percent were ambivalent. This high level of willingness to trust AI in healthcare could reflect the significant immediate benefits that improved medical diagnosis and treatment precision provide for patients, along with the high levels of trust in doctors in most nations. Adoption and market growth While public trust in healthcare AI is increasing, adoption within medical organizations varies. A 2022 survey found that 16 percent of healthcare organizations had implemented AI models for less than 2 years, while ** percent were still evaluating use cases. Notably, ** percent were not actively considering AI solutions. Despite this mixed adoption, the AI healthcare market is poised for significant growth, with robot-assisted surgery alone forecast to reach ** billion U.S. dollars by 2026. Generational and regional differences Attitudes toward AI in healthcare differ across age groups and regions. Younger generations are more optimistic about AI's potential to improve their personal health in the near future compared to baby boomers. Geographically, trust in AI for medical use varies significantly, with Chinese clinicians showing the highest confidence at ** percent, compared to less than ** percent of the clinicians surveyed in the United States.

The Medical Knowledge Graph market is experiencing robust growth, driven by the increasing need for efficient data management and analysis within the healthcare sector. The rising volume of patient data, coupled with advancements in artificial intelligence (AI) and machine learning (ML), is fueling the adoption of knowledge graphs to improve clinical decision-making, research, and drug discovery. We estimate the market size in 2025 to be approximately $250 million, with a Compound Annual Growth Rate (CAGR) of 15% projected from 2025 to 2033. This growth is attributed to several key drivers, including the rising prevalence of chronic diseases demanding personalized medicine approaches, the increasing emphasis on interoperability between healthcare systems, and the growing demand for improved patient outcomes through data-driven insights. The market is segmented by application (e.g., clinical decision support, drug discovery, public health surveillance) and type (e.g., cloud-based, on-premise). Major players are actively investing in research and development to enhance the capabilities of their Medical Knowledge Graph solutions, further driving market expansion. The restraints to market growth include concerns around data privacy and security, the complexity of integrating knowledge graphs with existing healthcare IT infrastructure, and the need for skilled professionals to manage and interpret the vast amounts of data generated. However, ongoing advancements in data security technologies and the development of user-friendly interfaces are mitigating these challenges. Geographically, North America currently holds a significant market share, driven by early adoption and robust technological advancements. However, the Asia-Pacific region is poised for significant growth in the coming years due to increasing investments in healthcare infrastructure and rising healthcare expenditure. The forecast period of 2025-2033 presents significant opportunities for market players to capitalize on the growing demand for efficient and intelligent data management solutions in healthcare. The market's future is bright, with continuous innovation and expanding applications set to propel its trajectory.

In a sunlit hospital room in San Diego, a pediatrician glances at a screen not to read a chart but to receive a real-time, AI-generated diagnosis that considers thousands of similar cases. This is not fiction, it’s today’s reality. AI has become a silent partner in healthcare, revolutionizing diagnosis, treatment,...

Introduction

Global Generative AI in Healthcare Market size is expected to be worth around US$ 17.2 Billion by 2032 from US$ 1.1 Billion in 2023, growing at a CAGR of 37% during the forecast period from 2024 to 2032. In 2022, North America led the market, achieving over 36.0% share with a revenue of US$ 0.2 Billion.

Generative AI is enhancing medical imaging, aiding clinical decisions, and streamlining operations. Its application in virtual nursing assistants could save healthcare providers up to USD 20 billion annually. Additionally, its integration into clinical settings, including diagnostics, telemedicine, patient care management, and telehealth applications, has secured its top market share.

However, challenges such as data privacy concerns, the need for high-quality data sets, and sophisticated infrastructure may hinder its growth. Balancing AI’s potential benefits with these challenges is crucial for sustainable market expansion.

Recent developments illustrate the dynamic nature of this market, with major investments and collaborations focused on harnessing GPT-4 and other advanced AI technologies for healthcare applications. Microsoft Corp. and Epic Systems Corp. recently collaborated to integrate generative AI into electronic health records to increase patient outcomes and effectiveness of healthcare delivery.

North America has led in terms of healthcare infrastructure and adoption rate of new technologies; while Asia Pacific appears poised for explosive growth as technological innovations meet rising healthcare demands and supportive government initiatives.

At present, the market for generative AI in healthcare is at an important juncture, only just beginning to realize its full potential. Projected growth highlights a shift toward more AI-integrated healthcare solutions which promise increased efficiency, better patient outcomes and significant economic advantages.

Sixty percent of respondents from the pharma and healthcare industry state that deployment of artificial intelligence helps improve quality control. According to 42 percent of respondents, monitoring and diagnosis is another important use case for AI. AI technology helps diagnosing diseases and its algorithms can select treatments accordingly. In addition, it may soon be possible to use AI in this industry to offer patients personalized preventive risk screenings. This opens possibilities to find the most suitable options for patients based on AI-enabled technology.

The global AI in healthcare market is projected to grow significantly, registering a CAGR of 33.7% from 2024 to 2031, with market value increasing from $19.27 Billion in 2023 to $189.55 Billion by 2031.

The medical knowledge graph market is experiencing robust growth, driven by the increasing need for efficient data management and analysis within the healthcare sector. The convergence of big data, artificial intelligence (AI), and the rising adoption of electronic health records (EHRs) is fueling this expansion. A projected Compound Annual Growth Rate (CAGR) of 20% (a reasonable estimate given the rapid technological advancements in this space) suggests a market valued at approximately $2 billion in 2025, with a forecast to reach $6 billion by 2033. Key drivers include the need for improved clinical decision support, accelerated drug discovery, personalized medicine initiatives, and enhanced patient care through more effective data analysis. The market is segmented by deployment (cloud, on-premise), application (drug discovery, clinical research, diagnostics), and end-user (hospitals, pharmaceutical companies, research institutions). Leading companies such as Raapid, Datavid, Wisecube AI, Cambridge Semantics, Ontotext, and Elsevier are actively shaping the market landscape through innovative solutions and strategic partnerships. However, challenges like data interoperability issues, data privacy concerns, and the high cost of implementation pose restraints to widespread adoption. The market's trajectory indicates significant opportunities for growth across various segments. The cloud-based deployment model is expected to dominate due to its scalability and cost-effectiveness. The pharmaceutical industry's increasing reliance on data-driven insights for drug discovery and development is a significant growth catalyst. Similarly, the integration of medical knowledge graphs into diagnostic tools promises improved accuracy and efficiency. The North American market currently holds the largest share, followed by Europe, driven by strong technological adoption and regulatory support. However, emerging markets in Asia-Pacific are poised for significant growth as healthcare infrastructure improves and digitalization efforts accelerate. The forecast period (2025-2033) will witness a continuous rise in market penetration, driven by innovation and increasing awareness of the benefits of knowledge graphs in optimizing healthcare operations and outcomes.

Background:The infodemic we are experiencing with AI related publications in healthcare is unparalleled. The excitement and fear surrounding the adoption of rapidly evolving AI in healthcare applications pose a real challenge. Collaborative learning from published research is one of the best ways to understand the associated opportunities and challenges in the field. To gain a deep understanding of recent developments in this field, we have conducted a quantitative and qualitative review of AI in healthcare research articles published in 2023.Methods:We performed a PubMed search using the terms, “machine learning” or “artificial intelligence” and “2023”, restricted to English language and human subject research as of December 31, 2023 on January 1, 2024. Utilizing a Deep Learning-based approach, we assessed the maturity of publications. Following this, we manually annotated the healthcare specialty, data utilized, and models employed for the identified mature articles. Subsequently, empirical data analysis was performed to elucidate trends and statistics. Similarly, we performed a search for Large Language Model(LLM) based publications for the year 2023.Results:Our PubMed search yielded 23,306 articles, of which 1,612 were classified as mature. Following exclusions, 1,226 articles were selected for final analysis. Among these, the highest number of articles originated from the Imaging specialty (483), followed by Gastroenterology (86), and Ophthalmology (78). Analysis of data types revealed that image data was predominant, utilized in 75.2% of publications, followed by tabular data (12.9%) and text data (11.6%). Deep Learning models were extensively employed, constituting 59.8% of the models used. For the LLM related publications,after exclusions, 584 publications were finally classified into the 26 different healthcare specialties and used for further analysis. The utilization of Large Language Models (LLMs), is highest in general healthcare specialties, at 20.1%, followed by surgery at 8.5%.Conclusion:Image based healthcare specialities such as Radiology, Gastroenterology and Cardiology have dominated the landscape of AI in healthcare research for years. In the future, we are likely to see other healthcare specialties including the education and administrative areas of healthcare be driven by the LLMs and possibly multimodal models in the next era of AI in healthcare research and publications.Data Files Description:Here, we are providing two data files. The first file, named FinalData_2023_YIR, contains 1267 rows with columns including 'DOI', 'Title', 'Abstract', 'Author Name', 'Author Address', 'Specialty', 'Data type', 'Model type', and 'Systematic Reviews'. The columns 'Specialty', 'Data type', 'Model type', and 'Systematic Reviews' were manually annotated by the BrainX AI research team. The second file, named Final_LLM_2023_YIR, consists of 584 rows and columns including 'DOI', 'Title', 'Abstract', 'Author Name', 'Author Address', 'Journal', and 'Specialty'. Here, the 'Specialty' column was also manually annotated by the BrainX AI Research Team.

Artificial intelligence (AI) in healthcare market is expected to grow from USD 22.61 bn in 2024 to USD 35.71 bn in 2025 and USD 765.12 bn by 2035, at CAGR of 35.9%.

AI in healthcare is accelerating transformation, from diagnosing illnesses faster to streamlining hospital workflows. Impact spans advanced diagnostics to drug development and patient documentation. For example, AI is cutting drug development timelines by over 50% in some cases, and ambient‑AI scribes are already easing burnout for clinicians. Explore the stats...

In 2021, 42 percent of healthcare organizations in the European Union were currently using AI technologies for disease diagnosis, while a further 19 percent had plans to employ this technology within the next 3 years. Furthermore, 33 percent of healthcare organizations surveyed planned to use patient monitoring AI tools in the next 3 years How much impact does AI have on saving time in healthcare? An online survey from several European countries concluded that the implementation of AI could free up significant portions of time in healthcare – with nearly half of the hours worked by medical equipment preparers and one-third of the hours of medical assistants. While, according to another survey, physicians in Europe could spend almost ** percent more time with patients instead of administrative tasks with the help of AI. The same held true for nurses, whose time with patients would increase by *** percent thanks to AI, according to estimates. Attitudes and opinions regarding AI in healthcare In 2021, a quarter of respondents surveyed in the European Union reported trusting AI-enabled decisions in patient monitoring, higher than any other AI applications. Meanwhile, only * percent trusted AI-enabled decisions in disease diagnostics, with the majority preferring to combine it with expert judgment from healthcare professionals. Overall, the opinions of EU respondents on the impact of AI in healthcare were positive, with the majority agreeing that the use of AI could result in improvement in the quality of diagnosis decisions and treatment

Generative AI in healthcare market is estimated to be USD 3.3 billion in 2025 and is projected to reach USD 39.8 billion by 2035, representing a CAGR of 28%.

The Clinical Knowledge Graph (CKG) technology market is experiencing robust growth, driven by the increasing need for efficient and insightful data management within the healthcare sector. The market's expansion is fueled by several key factors: the exponential growth of healthcare data, the demand for improved patient care through personalized medicine, the rise of precision medicine initiatives, and the growing adoption of AI and machine learning in clinical decision support. The integration of CKGs allows healthcare organizations to connect disparate data sources – electronic health records (EHRs), clinical trials data, research publications, and genomic information – creating a holistic view of patient health. This facilitates improved diagnostics, treatment planning, drug discovery, and ultimately, better patient outcomes. While the precise market size in 2025 is unavailable, a reasonable estimate, considering similar technology markets and reported CAGRs for related sectors, would place it at approximately $500 million. A conservative CAGR of 20% over the forecast period (2025-2033) would project significant growth, exceeding $3 billion by 2033. This growth is tempered by challenges such as data integration complexities, concerns around data privacy and security, and the need for skilled professionals capable of building and maintaining these complex systems. Key players in the CKG market, such as Raapid, Datavid, Wisecube AI, Cambridge Semantics, Ontotext, and Elsevier, are actively contributing to market growth through continuous innovation and the development of sophisticated CKG solutions. The market is segmented by deployment model (cloud-based vs. on-premise), application (drug discovery, clinical decision support, personalized medicine), and end-user (hospitals, pharmaceutical companies, research institutions). Geographic expansion is also driving growth, with North America and Europe currently holding the largest market shares, though the Asia-Pacific region is expected to witness significant growth in the coming years. The restraints on market growth primarily involve the considerable investment required for infrastructure development and skilled workforce training, as well as regulatory hurdles surrounding data privacy and interoperability.

Integrating Artificial Intelligence (AI) in healthcare is considered an unavoidable trend across countries globally. The perceptions and attitudes of healthcare students play a crucial role in advancing reforms within training programs. This study aimed to explore healthcare students' perceptions and attitudes toward the application of AI in the healthcare process and to assess the correlation between these two factors.A cross-sectional study was conducted on 967 healthcare students from December 2024 to January 2025. The research utilized a three-part self-report questionnaire designed to assess the perceptions and attitudes of healthcare students regarding the application of AI in healthcare. Descriptive statistics and correlation tests were employed for data analysis.This dataset was used for the study.

The India AI in healthcare market size was worth around USD 0.83 billion in 2023 and is predicted to grow to around USD 17.75 billion by 2032