The artificial intelligence in healthcare market is estimated to reach USD 17,198.9 million in 2025. It is estimated that revenue will increase at a CAGR of 18.2% between 2025 and 2035. The market is anticipated to reach USD 77,456.4 million by 2035.
The integration of artificial intelligence technologies into healthcare systems can enhance medical practices by improving patient outcomes, and streamlining operations. Technologies such as machine learning, context-aware computing, natural language processing, deep learning, querying method etc. are used across various healthcare applications, including diagnostics, treatment planning, drug discovery, and patient management.
The most common application of AI within robot-assisted surgery. The AI tools are used at various end point in the healthcare ecosystem. It assist healthcare provider in better decision making. In The form of virtual health assistant it aid patient with medication compliance and relevant information. Within the pharmaceutical company in accelerates the drug discovery process.
Artificial Intelligence in Healthcare Industry Outlook
| Attributes | Key Insights |
|---|---|
| Historical Size, 2024 | USD 14,550.7 million |
| Estimated Size, 2025 | USD 17,198.9 million |
| Projected Size, 2035 | USD 77,456.4 million |
| Value-based CAGR (2025 to 2035) | 18.2% |
There has been a surge in investment in AI healthcare startups. In the first two quarters of 2024 alone investments in AI startups crossed the USD 35 billion mark. Abridge is a company focused on developing ambient clinical documentation tool and raised USD 150 million for the same. While AKASA secured USD 120 million to improve revenue cycle automation.
Startups like Zephyr AI and Xaira Therapeutics have also attracted significant funding. These investments are enabling rapid innovation for disease prediction and data analysis. These innovations enhance healthcare providers' operational efficiency.
According to Becker's Hospital Review the demand for healthcare workers in the United States, is expected to reach 18.7 million by 2028. But the actual workforce will fall short by 100,000 workers. AI technologies can alleviate this shortage by automating routine administrative tasks. AI is having tremendous impact in healthcare diagnosis through medical image analysis. This enable radiologist to focus on more complex cases.
AI-powered virtual health assistants enabled through NLP and machine learning, support patients in the self-management of chronic diseases. Virtual health assistants can remind patients of their medication, monitor compliance, and send notifications regarding missed doses both to the patient and provider. This integrates with wearable technology for continuous health monitoring of patients and the early identification of signs of complications so interventions can be timely.
Most of the healthcare organizations have old systems that are not designed to work with modern AI tools. The data from EHRs and medical imaging systems is in unstructured non-compatible format which impairs the functionality of AI. Integration of AI with these systems requires huge investments and also poses regulatory and compliance challenges. Despite these, innovation, investment, and the growing needs for efficient and scalable healthcare solutions contribute to growth of the AI market in healthcare.
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The below table presents the expected CAGR for the global artificial intelligence in healthcare market over several semi-annual periods spanning from 2024 to 2034. In the first half (H1) of the decade from 2024 to 2034, the business is predicted to surge at a CAGR of 19.2%, followed by a slightly lower growth rate of 18.8% in the second half (H2) of the same decade.
| Particular | Value CAGR |
|---|---|
| H1 | 19.2% (2024 to 2034) |
| H2 | 18.8% (2024 to 2034) |
| H1 | 18.2% (2025 to 2035) |
| H2 | 17.7% (2025 to 2035) |
Moving into the subsequent period, from H1 2025 to H2 2035, the CAGR is projected to decrease slightly to 18.2% in the first half and remain relatively moderate at 17.7% in the second half. In the first half (H1) the market witnessed a decrease of 100 BPS while in the second half (H2), the market witnessed a decrease of 110 BPS.
Increased Investment in Healthcare AI Startups Drive Growth of Artificial Intelligence in Healthcare Market
The number of AI Startups have gone up and so has the investment. According to the World Economic Forum in the First 2 quarters of 2024 the total investment crossed the 35 billion dollar mark. For example, companies like Abridge have secured USD 150 million to develop ambient clinical documentation tools.
While AKASA raised USD 120 million to enhance revenue cycle automation. These investments are enhancing the operational efficiency of healthcare providers along with addressing critical challenges within healthcare industry.
Recent funding rounds for AI-driven healthcare startups highlight the growing interest wide range of healthcare applications from precision medicine to drug discovery. Zephyr AI is a precision medicine startup that raised USD 111 million in a Series A funding round on March 13, 2024. This round saw investments from major players like Eli Lilly & Co. and MedStar Health.
Similarly, Xaira Therapeutics, focused on AI-driven drug discovery, raised an impressive USD 1 billion in its Series A round on April 23, 2024. Led by Foresite Capital and ARCH Venture Partners, this funding positions Xaira to advance its innovative approach to developing new drugs using AI algorithms. These substantial investments reflect the growing momentum in the AI healthcare sector.
Shortage of skilled healthcare workforce is fueling the demand for Artificial Intelligence in Healthcare Industry
The global population is aging because of increased life expectancy. Because of this, chronic conditions also increase and so does the need for health care services. The capacity of the present healthcare worker is unable to accommodate this high demand. Trained healthcare workers are insufficient to meet such growing demands in many region.
According to Becker's Hospital Review, the demand for health workers in United States is expected to reach 18.7 million by 2028. With the current trend the actual workforce is will reach 18.6 million in 2028. This leaves a shortfall of 100,000 workers.
Administrative work is the major burdens for healthcare professionals. AI tools can perform a lot of this work automatically, freeing healthcare professionals to spend more time with the patients. AI systems ease the job of analyzing medical imaging. Medical imaging analysis is getting streamlined with AI systems that support radiologists in detecting conditions like tumors, fractures, and many others. This automates diagnosis and allows clinicians' to concentrate their attention on complex cases requiring human judgment.
AI-driven decision support systems are AI platforms that can analyze vast amounts of patient data and provide real-time recommendations. This allows healthcare providers to make informed decisions without requiring access to a specialist for every case, thus extending the reach of limited specialist expertise. Hence, due to a limited workforce and advantage of AI, the adoption of the same is increasing in the healthcare industry.
AI-powered Virtual health Assistants Offers an Opportunity for Market Growth
AI-powered Virtual health Assistants are designed to support patients for chronic condition management. They use NLP and ML algorithms in order to continuously assist their patients in medication adherence, lifestyle management, and general health education. For instance, AI assistants can send reminders related to medication to the patients, track the compliance rate, and send alerts in case of missed doses to both the patient and healthcare provider.
Remote monitoring extends the role of VHAs through wearable devices and connected health tools. Wearable devices are collecting continuous health data transmitted to health professionals. Continuous monitoring with the help of these devices helps in the early identification of complication signs. For instance, AI algorithms can look at heart rate variability for cardiovascular patients or analyze blood glucose trends for diabetic patients, which could lead to future risks before a crisis point is reached.
The integration of AI-powered virtual assistants with remote monitoring presents a very lucrative opportunity for various market players. In addition, wearable device manufacturers can further expand their product offerings through the integration of AI in these devices to unlock new revenue streams in the growing market for health monitoring solutions.
Integration Challenges with legacy Systems Hinder the Market Growth
Many healthcare providers rely on legacy systems to manage patient data. AI systems, trained on structured data, may struggle with the DICOM format. Many healthcare organizations use a mix of proprietary and outdated systems which are difficult to integrate with AI. AI solutions require access to large datasets stored in EHRs, medical imaging systems, and other clinical data repositories. If these systems are not designed to share data AI tools cannot function optimally.
Healthcare data is unstructured and available in multiple formats that are difficult to process by AI algorithms. Patient records can include handwritten diagnostic results that are not in standardized digital formats. AI tools require structured data such as FHIR (Fast Healthcare Interoperability Resources).
Integrating AI with legacy healthcare systems is a costly process. Even after AI systems are integrated the ongoing maintenance can add to the cost. While integrating the AI solution Regulatory compliance also need to be considered which can further increase the complexity of the process. Hence, this integration challenges are hampering the adoption of AI In healthcare.
The artificial intelligence in healthcare industry recorded a CAGR of 13.2% between 2020 and 2024. According to the industry, artificial intelligence in healthcare generated USD 14,550.7 million in 2024, up from USD 9,113.2 million in 2020.
AI in healthcare was initially being used for few application in diagnostic imaging and robotic surgery. AI was primarily used for automating routine tasks in hospitals. Medical image analysis for accurate diagnosis and management of patients data were some of the application along with other administrative function where Artificial intelligence was used.
AI-powered tools to assist radiologists to identify signs of diseases. At the same time robotic surgery systems were introduced which improved surgical precision. These developments began to show the potential of AI in improving patient outcomes.
Today, AI in healthcare is about advanced applications that drive precision medicine. Machine learning algorithms are integrated into various aspects of healthcare from drug discovery to treatment personalization. AI models are used to analyze vast amounts of healthcare data to tailor treatments to individual patients.
In the upcoming year AI in healthcare will be defined by hyper-personalization. AI can predict genetic predispositions for treating complex conditions like rare diseases. AI will allow healthcare providers to analyze patient data from hospitals, primary care providers, and wearable devices. This will lead to 360-degree view of a patient’s health. AI will also be key to developing smart hospitals and remote monitoring systems. AI-powered virtual assistants and telemedicine platforms will become essential in providing healthcare remotely.
Companies in the Tier 1 sector account for 55.1% of the global market, ranking them as the dominant players in the industry. Tier 1 players’ offer a wide range of product and have established industry presence. Having financial resources enables them to enhance their research and development efforts and expand into new markets.
A strong brand recognition and a loyal customer base provide them with a competitive advantage. Prominent companies within Tier 1 include DeepMind, Microsoft Corporation, Amazon Web Services Inc., Intel Corporation, Nvidia Corporation, Siemens Healthcare, and others
Tier 2 players dominate the industry with a 34.5% market share. Tier 2 firms have a strong focus on a specific Product and a substantial presence in the industry, but they have less influence than Tier 1 firms. The players are more competitive when it comes to pricing and target niche markets. New Product and services will also be introduced into the industry by Tier 2 companies. Tier 2 companies include Medtronic, Cloudmedx Inc., Enlitic Inc., Micron Technology Inc., Nuance Communications Inc., and others.
Compared to Tiers 1 and 2, Tier 3 companies have smaller revenue spouts and less influence. Those in Tier 3 have smaller work force and limited presence across the globe. Prominent players in the tier 3 category are General Vision Inc., iCarbon, Welltok Inc., and others.
The section below covers the industry analysis for the artificial intelligence in healthcare market for different countries. Industry analysis of consumer demand on key countries in several regions of the globe, including North America, Latin America, East Asia, South Asia and Pacific, Western Europe, Eastern Europe, and Middle East and Africa (MEA), is provided. The United States is anticipated to remain at the forefront in North America through 2035. India is projected to witness a CAGR of 17.6% from 2025 to 2035.
| Countries | Value CAGR (2025 to 2035) |
|---|---|
| USA | 6.6% |
| Canada | 8.8% |
| Germany | 13.2% |
| France | 11.0% |
| Italy | 12.1% |
| UK | 9.9% |
| Spain | 9.3% |
| China | 17.1% |
The United States’ healthcare system is highly advanced. As the chronic disease prevalence is increasing the pressure created on the healthcare system in immense. There is need for accurate and faster diagnostic solution. AI technologies are addressing these challenges by significantly enhancing diagnostic imaging solutions.
AI algorithms based on deep learning and neural networks can analyze medical images. Arterys, Zebra Medical Vision, and Aidoc are developing AI solutions that can automatically detect medical conditions. These solution can classify among the various disease conditions such as cancers, cardiovascular diseases etc. AI tools can process vast amounts of imaging data in a fraction of the time.
The United States has become a global hub for AI research. Major tech companies are heavily investing in AI solutions. Additionally, regulatory agencies such as the FDA are increasingly approving AI-based medical devices. Hence due to the joint effect of private sector and support environment by the government bodies the artificial intelligence in healthcare industry is growing within the United States.
Germany has strong focus on precision medicine. Precision medicine refers to tailoring medical treatment to individual characteristics. Precision medicine rely on analyzing vast among of patient data. AI is crucial to analyze large datasets from diverse sources such as genomic data, electronic health records (EHRs), and clinical trials.
New pattern are uncovered while analyzing the patient data which allows to predict most effective treatment option. AI algorithms are used to interpret genetic data offering personalize treatments for complex diseases. Companies like BioNTech are leveraging AI to analyze genetic information to create targeted therapies. The main advantage of targeted therapy is that it results in lower side effects.
The government has been proactive in creating a framework to digitize healthcare processes. This initiative promote the use of AI across the healthcare system. AI can be integrated into electronic health records (EHR) to enhance decision support systems which ultimately ensure better interoperability between healthcare platforms. The focus on utilizing AI for precision medicine is fueling the industry growth in Germany.
Japan is a global leader in robotics. The continuous robotic innovations is transforming healthcare delivery, making it more efficient and patient-centric. Using AI enhance surgical precision by minimize human error. AI algorithms in robotic surgery platforms like Fujifilm’s Endoscope Robotics assist in real-time decision-making to guide surgeons on complex procedures.
Japan has higher percentage of elderly population that requires more frequent surgeries. AI-driven robots led to reduced trauma and improved patient outcomes. Additionally, Japan’s aging population has spurred the development of care robots like Robear and Pepper. This robots assist with tasks such as lifting, moving, and monitoring elderly patients.
A description of the leading segments in the industry is provided in this section. The hardware segment held 60.2% of the value share in 2025. Based on the application, robot-assisted surgery held 26.1% of the market in 2025.
| Offering | Hardware |
|---|---|
| Value Share (2025) | 60.2% |
The healthcare sector relies heavily on specialized medical equipment. Equipment’s are the main backbone for AI Applications. MRI, CT scanners, fitness trackers, robotic surgery tools etc. require hardware to process the data. AI Technologies are consistently improving. The rapid Technological advancement placed high computational demand for which robust hardware are required.
Hardware innovations in edge computing and cloud integration have enabled AI models to operate faster. For instance, edge devices can process data locally with minimal latency. This superiority in operation aid in real time decision making. This has been a crucial factor in the adoption of AI-powered medical devices in healthcare setting.
Increasing investment in AI-based medical technologies has led to demand for hardware infrastructure to support these advanced systems. AI algorithms are becoming more complex. High-performance GPUs, FPGAs, and ASICs are required to optimize their processing power. The combination of these factors positions hardware as a dominant segment.
| Application | Robot-Assisted Surgery |
|---|---|
| Value Share (2025) | 26.1% |
The integration of AI-powered robotic systems in surgery allows for precise minimally invasive procedures. These systems enable surgeons to perform complex procedures with greater control than traditional methods. This Technological superiority allows surgeons to make accurate incisions. Recovery time is reduced due to led trauma to surrounding tissues.
Robotic surgery systems are becoming increasingly sophisticated. AI algorithms assist in preoperative planning by analyzing the patient data and images. This analysis help surgeon created personalized surgery plan. During Surgery AI assist in identifying the tissue, guide surgeon’s action etc. Post-surgery AI is used for monitoring patient recovery, identifying potential complications.
Companies such as Intuitive surgical within market of robotic assisted surgery are constantly innovating new technologies. Their objective is to bring more number of surgery within the umbrella of robotic assisted surgery. Hence the culmination of the above factor is driving the dominance of the robot-assisted surgery in the market.
Market players are developing new artificial intelligence (AI) Model to address various gaps within the healthcare industry. It can analyzing molecular structure of compound, accelerating the drug discovery, increasing accuracy in diagnosis, improving the operational efficiency etc.
Firms are collaboration to leverage each other technical capability and achieve greater milestone. Industry leader are also acting as catalyst in implementation of AI within various healthcare domains by provide grants, funding for Institutions providing value within the industry using AI. This market dynamic act as a breeding ground for future innovations.
Recent Industry Developments in the Artificial Intelligence in Healthcare Market
Artificial intelligence in healthcare industry is expected to increase at a CAGR of 18.2% between 2025 and 2035.
The hardware segment is expected to occupy 60.2% market share in 2025.
The market for artificial intelligence in healthcare is expected to reach USD 77,456.4 million by 2035.
The United States is forecast to see a CAGR of 6.6% during the assessment period.
The key players in the artificial intelligence in healthcare industry include Amazon Web Services Inc., Cloudmedx Inc., DeepMind, Enlitic Inc., General Vision Inc., International Business Machines, iCarbon, Intel Corporation, Medtronic, Micron Technology Inc., Microsoft Corporation, Nuance Communications Inc., Nvidia Corporation, Siemens Healthcare, Welltok Inc., and others.
In terms of offering, the industry is segmented into hardware, software, and services.
In terms of technology, the industry is machine learning, context-aware computing, natural language processing, deep learning, querying method, and others.
In terms of application, the industry is segmented into robot-assisted surgery, virtual nursing assistant, administrative workflow assistance, fraud detection, dosage error reduction, clinical trial participant identifier, preliminary diagnosis, and others.
In terms of end user, the industry is segmented into healthcare providers, pharmaceutical and biotechnology companies, patients, and others.
Key countries of North America, Latin America, Western Europe, Eastern Europe, South Asia and Pacific, East Asia, the Middle East, and Africa have been covered in the report.
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Artificial Intelligence in Healthcare Market
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