Introduction

AI in Healthcare Statistics: Artificial Intelligence (AI) in healthcare is growing rapidly, helping doctors and healthcare providers improve patient care. AI uses machines and algorithms to analyse data, such as medical records or images, to help diagnose diseases and suggest treatments faster and more accurately. AI technologies like machine learning, natural language processing, and robotic surgery are driving this growth.

AI helps in areas like medical imaging, drug discovery, and personalised treatment, making healthcare more efficient. This technology is transforming healthcare by reducing costs, speeding up diagnoses, and improving the accuracy of treatments, all while supporting healthcare professionals in delivering better care.

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.

According to a survey of healthcare organizations in the United States in 2024, a lack of accuracy was ranked as the biggest potential limitation of generative AI. The second-highest rated potential limitation was the fact that GenAI poses major legal or reputation risks, with a score of 3.62.

In the first quarter of 2024, 29 percent of the respondents representing healthcare organizations in the United States reported already having implemented generative AI technologies in their organizations. This was an increase compared to the last quarter of 2023, when 25 percent of the healthcare organizations had implemented generative AI.

According to a survey of European healthcare professionals in 2024, there were higher levels of trust in AI tools among those that had experienced using the technology. Almost half of surveyed HCPs who have used AI said they would trust it to in supporting decision-making and diagnosis, compared to fewer than 20 percent who hadn't used AI.

According to a survey carried out in 2022, around 40 percent of adults surveyed in the United States believed that the implementation of artificial intelligence in health and medicine would reduce the number of mistakes made by health care providers. Meanwhile, more than half of the respondents expected the worsening of patients' personal relationships with their health care providers to be an effect of the implementation of AI.

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, approximately eight percent of healthcare organizations reported their budget allocated to AI projects in their organization had increased by more than 300 percent compared to the previous year. A further 13 percent stated the budget allocated to AI projects in their organization increased between 100 and 300 percent in this period.

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Artificial Intelligence (AI) Market In Healthcare Size 2025-2029

The artificial intelligence (AI) market in healthcare size is valued to increase USD 30.23 billion, at a CAGR of 33.1% from 2024 to 2029. Push for digitization in healthcare will drive the artificial intelligence (AI) market in healthcare.

Major Market Trends & Insights

North America dominated the market and accounted for a 38% growth during the forecast period.
By Application - Medical imaging and diagnostics segment was valued at USD 1.52 billion in 2023
By Component - Software segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 961.16 million
Market Future Opportunities: USD 30230.60 million
CAGR : 33.1%
North America: Largest market in 2023

Market Summary

The market is a dynamic and rapidly evolving sector, driven by advancements in core technologies such as machine learning and natural language processing. These technologies are revolutionizing healthcare delivery through applications like predictive analytics, medical imaging, and virtual nursing assistants. According to recent reports, the global AI in healthcare market is expected to reach a significant market share by 2027, growing at a steady pace due to increasing adoption rates and the need for digitization in healthcare. For instance, AI-based tools are increasingly being used to improve elderly care, with applications ranging from fall detection to medication management.
However, challenges such as physician and provider skepticism, data privacy concerns, and regulatory issues persist. Despite these challenges, the opportunities for AI in healthcare are vast, with potential applications in disease diagnosis, treatment planning, and population health management.

What will be the Size of the Artificial Intelligence (AI) Market In Healthcare during the forecast period?

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How is the Artificial Intelligence (AI) In Healthcare Market Segmented and what are the key trends of market segmentation?

The artificial intelligence (AI) in healthcare industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Medical imaging and diagnostics
  Drug discovery
  Virtual assistants
  Operations management
  Others


Component

  Software
  Hardware
  Services


End-user

  Hospitals and clinics
  Research institutes and academies


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Application Insights

The medical imaging and diagnostics segment is estimated to witness significant growth during the forecast period.

Artificial Intelligence (AI) is revolutionizing the healthcare sector by enhancing various applications, from treatment optimization and diagnostics to patient engagement and fraud detection. Natural language processing and machine learning algorithms enable AI-powered virtual assistants to assist in clinical decision support, while computer vision systems analyze medical images for disease prediction and radiation therapy planning. Genomic data analysis and drug discovery platforms leverage AI to uncover new insights and accelerate research. Data mining techniques and predictive modeling are crucial for risk stratification and clinical trial optimization, while deep learning models improve healthcare chatbots and robotic surgery systems' precision.

The market for AI in healthcare is expanding rapidly, with remote patient monitoring and AI-powered diagnostics witnessing significant growth. According to recent studies, the market for AI in healthcare is projected to reach 61.2 billion USD by 2026, representing a 41.5% increase from its current size. Additionally, the adoption of AI in healthcare is expected to grow by 38.2% in the next five years. AI's impact on healthcare is multifaceted, from improving patient outcomes and reducing costs to enhancing operational efficiency and enabling personalized medicine. Wearable sensor data and electronic health records are essential data sources for AI applications in healthcare, while healthcare data interoperability and big data analytics are crucial for driving innovation and improving patient care.

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The Medical imaging and diagnostics segment was valued at USD 1.52 billion in 2019 and showed a gradual increase during the forecast period.

AI's role in healthcare is continuously evolving, with ongoing developments in precision oncology, disease prediction models, and drug repurposing. AI-powered fraud detection systems and biometric authentica

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,...

In 2024, 68 percent of respondents to a survey in the United States were concerned about the use of AI in healthcare due to potential weakening of relationships between patients and providers. Furthermore, new security risks and inaccurate information were causes of concern for over 60 percent of the respondents.

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.

BackgroundResearch related to Artificial Intelligence (AI) in healthcare applications is evolving. It is essential to incorporate collaborative learning from published research to comprehend the challenges and accessibility of opportunities when integrating AI in healthcare systems. To investigate the role of AI, a qualitative and quantitative year in review study was conducted, encompassing the evaluation of literature published in 2024 to gain insight into the recent advancements of the field.MethodsTo find research articles about integrating new AI technologies into healthcare systems, a PubMed search using the terms “2024”, “artificial intelligence”, and “large language models” was conducted. The search was restricted to human subject research and used a deep-learning-based approach to assess the reliability of publications as of December 31, 2024 on January 1, 2025. In addition, for each publication, each mature article was manually annotated for the AI model type (e.g., LLM, DL, ML), healthcare specialty, and the data type used (image, text, tabular, or audio).Additionally,qualitative and quantitative analyses were performed to illuminate statistics and trends of combined published articles.ResultsOur PubMed search yielded 28,180 total articles; 1,693 were initially labeled mature, after which 1,551 articles were analyzed after exclusions. Similar to the prior years, we excluded systematic reviews in the final analysis and were excluded in this year's dataset.The most prevalent specialties within our PubMed search originated from imaging (407), head and neck (127), and General (122). Analysis of AI model types showed that the Large Language Model (LLM) was the most popular utilized in 479 publications, followed by AI General (448), and DL (372). Qualitative data was obtained on the data types, and it was revealed that the image data was predominant and used in 57.0% of the mature sources, followed by text (33.1%), followed by tabular (7.59%). The utilization of Large Language Models (LLMs) is the highest in publications associated with education at 18.6%, followed by General at 13.6%. These results indicate that LLMs are frequently applied in educational contexts and administrative tasks amongst the healthcare specialties for research.ConclusionHealthcare specialties, including imaging, head and neck, and general medicine, have taken over the realm of AI in healthcare. Other specialties that distinctive types of AI and LLMs could likely drive in the future include education, pathology, as well as surgery. It is essential to use a collaborative approach to investigate the multimodal models of AI in healthcare applications to provide a thorough encapsulation of AI in healthcare.Data Files DescriptionOne data file is provided, which illustrates the annotations of the mature sources used in our review. The first file is named Annotated_OnlyMature_Unique_2024_YIR_All_Publications - Annotated_OnlyMature_Unique_2024_YIR_All_Publications and includes ‘Title’, ‘DOI’, ‘Abstract’, ‘Author Address’, ‘Specialty’, ‘Model’, and 'Data Type’. The ‘Specialty’, ‘Model’, and ‘Data Type’ were predominantly analyzed by the BrainXAI research team to produce our meta-analysis of the mature sources of AI. This year we have excluded systematic reviews from the dataset compared to the 2023 year in review dataset, but can be provided on request.

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...

As of 2024, at least one fifth of respondents working in healthcare organizations reported that they used large language models for answering patient questions and medical chatbots. Furthermore, 18 percent of healthcare organizations used LLMs for biomedical research.

Explore North America Artificial Intelligence in Healthcare Market, including size, share, growth, trends, and industry analysis, with forecasts extending to 2033.

Artificial Intelligence (AI) in Healthcare Market Outlook

According to our latest research, the global Artificial Intelligence (AI) in Healthcare market size reached USD 24.6 billion in 2024, with a robust compound annual growth rate (CAGR) of 36.4% expected through the forecast period. By 2033, the market is projected to achieve a value of USD 349.5 billion, driven by increasing adoption of AI-powered solutions across healthcare ecosystems worldwide. The primary growth factor is the accelerating integration of AI technologies for enhancing diagnostics, streamlining patient management, and expediting drug discovery processes. As per our latest research, the sector is witnessing unprecedented investment and innovation, particularly in the realms of medical imaging, virtual assistants, and precision medicine, which are transforming the quality and efficiency of healthcare delivery.

One of the most significant growth drivers for the AI in Healthcare market is the surging demand for advanced data analytics and predictive modeling in medical decision-making. Healthcare providers are increasingly leveraging AI-powered tools to extract actionable insights from vast repositories of patient data, electronic health records (EHRs), and real-time monitoring devices. These technologies enable clinicians to identify disease patterns, predict patient outcomes, and personalize treatment regimens with remarkable accuracy. The proliferation of high-throughput medical imaging and wearable sensors has further amplified the need for scalable AI solutions, as traditional methods struggle to keep pace with the exponential growth in healthcare data. The ability of AI to process and interpret complex datasets in a fraction of the time required by human experts is revolutionizing diagnostics, leading to earlier interventions and improved patient prognoses.

Another crucial factor fueling the expansion of the AI in Healthcare market is the ongoing digital transformation initiatives across hospitals, clinics, and pharmaceutical companies. The COVID-19 pandemic has accelerated the adoption of telehealth, remote patient monitoring, and virtual care platforms, all of which rely heavily on AI algorithms for triage, symptom assessment, and risk stratification. Pharmaceutical and biotechnology firms are also harnessing AI to expedite drug discovery, optimize clinical trial design, and identify novel therapeutic targets, thereby reducing development timelines and costs. Additionally, AI-driven automation is streamlining administrative workflows, claims processing, and patient scheduling, resulting in significant operational efficiencies and cost savings for healthcare organizations. These advancements are fostering a data-driven culture that prioritizes evidence-based care and continuous improvement.

The growing acceptance of personalized medicine and precision healthcare is also a major catalyst for AI adoption in the sector. AI algorithms are instrumental in analyzing genetic, phenotypic, and lifestyle data to tailor treatment plans that maximize efficacy and minimize adverse effects. This paradigm shift towards individualized care is supported by advances in genomics, proteomics, and bioinformatics, all of which generate massive datasets that are ideally suited for AI-driven analysis. Furthermore, regulatory bodies are increasingly recognizing the value of AI in improving patient safety and outcomes, leading to a more favorable environment for the development and deployment of innovative AI solutions in healthcare. The convergence of these trends is expected to sustain the high growth trajectory of the AI in Healthcare market over the coming decade.

Regionally, North America currently dominates the global AI in Healthcare market, accounting for the largest share due to its advanced healthcare infrastructure, substantial investment in research and development, and early adoption of cutting-edge technologies. The United States, in particular, is a hub for AI innovation, with numerous startups and established players collaborating with academic institutions and healthcare providers. Europe follows closely, propelled by supportive regulatory frameworks and significant government funding for digital health initiatives. The Asia Pacific region is emerging as a high-growth market, driven by the rapid expansion of healthcare systems, rising prevalence of chronic diseases, and increasing focus on digitalization in countries such as China, Japan, and India. Latin America and the Middle East & Africa are also witnessing growing interest in AI-power

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.

Artificial Intelligence (AI) in Medical Market Outlook

The global market size for Artificial Intelligence (AI) in the medical sector was valued at approximately $5.2 billion in 2023 and is expected to reach around $45.2 billion by 2032, growing at a CAGR of 26.8% during the forecast period. This remarkable growth can be attributed to several factors, including advancements in AI technology, increasing healthcare data, and the rising demand for personalized medicine.

One of the primary growth factors for AI in the medical market is the rapid advancement in AI technologies such as machine learning, natural language processing, and computer vision. These technologies enable healthcare providers to analyze vast amounts of data more effectively, leading to improved diagnostic accuracy and better patient outcomes. The integration of AI in medical imaging, for example, aids radiologists in detecting anomalies much earlier, thus facilitating timely intervention and treatment.

Another significant driver is the growing volume of healthcare data generated from electronic health records (EHRs), wearable devices, and genomics. AI systems are highly efficient at processing and analyzing this data to extract meaningful insights, which can be used for predictive analytics and early disease detection. This capability not only enhances patient care but also contributes to the operational efficiency of healthcare providers by streamlining administrative tasks and reducing the risk of human error.

The rising demand for personalized medicine is also a crucial factor driving the market. AI algorithms can analyze individual patient data to provide customized treatment plans, improving the efficacy of medical interventions. This approach is particularly beneficial in oncology, where personalized treatment plans based on genetic profiling can significantly improve patient outcomes. Furthermore, AI's role in drug discovery and development is accelerating the process of bringing new drugs to market, thus addressing unmet medical needs more rapidly.

Regionally, North America holds the largest share of the AI in medical market, primarily due to the high adoption rate of advanced technologies and substantial investments in healthcare infrastructure. The presence of key market players and extensive research activities further bolster the market in this region. Europe follows closely, with significant contributions from countries like Germany, the UK, and France, which have well-established healthcare systems and a strong focus on innovation. The Asia Pacific region is anticipated to witness the highest growth rate, driven by increasing healthcare expenditure, growing awareness of AI applications in healthcare, and supportive government policies.

Component Analysis

The AI in medical market can be segmented by component into software, hardware, and services. The software segment holds the largest market share and is expected to continue its dominance during the forecast period. This segment includes AI algorithms, platforms, and analytical tools that are crucial for data analysis and decision-making processes in medical applications. The growing adoption of AI-based software solutions for diagnostic and predictive analytics is a key driver for this segment.

The hardware segment, although smaller than software, is also experiencing significant growth. This segment comprises AI-enabled medical devices, sensors, and computing infrastructure necessary to support AI applications. The increasing demand for advanced imaging systems, robotic surgical instruments, and AI-integrated diagnostic tools is propelling the growth of this segment. Furthermore, advancements in hardware technologies, such as the development of high-performance GPUs and specialized AI chips, are enhancing the capabilities of AI systems in healthcare.

The services segment encompasses various support services required for the implementation and maintenance of AI systems in medical settings. This includes consulting, integration, and training services provided by vendors to ensure the smooth deployment and operation of AI technologies. The growing need for specialized skills and expertise to manage AI systems, along with the rising trend of outsourcing these services, is driving the expansion of this segment. Additionally, ongoing support and maintenance services are essential to keep AI systems updated and functioning optimally.

Within the services segment, managed services are gaining traction as healthcare providers seek to minimize the complexi

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