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Table Of Content
August 2024
The global artificial intelligence (AI) in healthcare market size is calculated at USD 36.96 billion in 2025 and is forecasted to reach around USD 613.81 billion by 2034, accelerating at a CAGR of 36.83% from 2025 to 2034. The North America artificial intelligence (AI) in healthcaremarket size surpassed USD 12.01 billion in 2024 and is expanding at a CAGR of 36.86% during the forecast period. The market sizing and forecasts are revenue-based (USD Million/Billion), with 2024 as the base year.
The global artificial intelligence (AI) in healthcare market size was estimated at USD 26.69 billion in 2024 and is predicted to increase from USD 36.96 billion in 2025 to approximately USD 613.81 billion by 2034, expanding at a CAGR of 36.83% from 2025 to 2034.
The U.S. artificial intelligence (AI) in healthcare market size was valued at USD 8.41 billion in 2024 and is expected to be worth around USD 195.01 billion by 2034, growing at a CAGR of 36.94% from 2025 to 2034.
North America region was the highest market share holder in 2024. North America is characterized by the increased inclination towards the advanced and latest digital technologies. The strong and developed healthcare, IT, and telecommunications infrastructure in North America has supported the growth of the artificial intelligence in healthcare market. Furthermore, the favorable government policies that encourage the adoption of the digital and novel technologies like artificial intelligence in the healthcare sector. North America has the presence of huge pool of patients. It is estimated that over half of the US population is suffering from one or more chronic diseases. This is resulting in increased volume of patients in hospitals. The health data of these patients needs to be stored and managed in digital form as per the government regulations. This is a major factor that propels the demand for the artificial intelligence in healthcare sector.
Asia Pacific is estimated to be the fastest-growing market during the forecast period. This is attributed to the rising government investments towards the development of smart hospitals, growing investments in the development of healthcare and IT infrastructure, and growing volume of patients in the region. Asia Pacific is witnessing a rising adoption of smartphones and growing penetration of internet. The technological advancements in the digital technologies to cater to the needs of data security and data privacy in the healthcare sector is expected to propel the adoption of the artificial intelligence in healthcare in this region. The presence of huge population in the region, growing geriatric population, and rising prevalence of lifestyle diseases are fostering the adoption of the digital technologies in the healthcare sector.
Artificial intelligence (AI) is specified as the study of “intelligent agents” i.e., any representative or tool that can comprehend and grasp its environment and therefore draw relevant action to enhance its chances of reaching its purpose. AI likewise relates to conditions where machines can imitate the human mind in learning and analyzing, thereby working to solve problems. Such a kind of intelligence is also known as machine learning. Usually, AI covers a method that sustains both software and hardware. From a software outlook, AI is notably involved with algorithms. The artificial neural network is a theoretical frame for performing AI algorithms which simulate a human brain.
Medicine has been determined from the beginning as one of AI’s most promising fields of application. Since the mid- 20th century, researchers have proposed and developed multiple systems to aid clinical decision-making. In addition, it is tough to code higher-order interactions amongst distinct fragments of knowledge penned by various experts, and the wholeness of previous healthcare awareness confines the execution of the network. Furthermore, it has been challenging to implement a system that integrates deterministic and probabilistic reasoning to reduce the relevant clinical context, prioritize diagnostic assumptions, and recommend therapy.
The Covid-19 outbreak certainly influenced the need for AI technologies and uncovered the ability held by these leading technologies. Healthcare methods widely approved these technologies in the speedy detection and diagnosis of different virus strains and used personalized data to improve the operation of the outburst.
Hence, AI algorithms can be skilled to examine patient health details, which further holds care suppliers in quickly detecting the condition and making a correct therapy scheme. Government initiatives, the rising number of fusions and purchases and technical cooperation, and the sustained Covid-19 pandemic had a notable role in scaling up the market's growth and speeding up the approval value of artificial intelligence in medical care. The rising entry of artificial intelligence methods in medical treatment applications resulted in key market participants concentrating on product newness and technical connections to escalate their commodity portfolio and meet and greet the increasing needs during the outbreak.
The growing adoption of the digital technologies in the healthcare sector owing to the growing need for reducing the healthcare costs and offer enhanced quality patient care services to the patients are the prominent factors that are boosting the growth of the global artificial intelligence in healthcare market. The surging prevalence of various chronic diseases and growing elderly population is resulting in the increased pool of patients at hospitals. The large volume of patient health data is generated every day, which is required to be stored and managed effectively. The growing demand for the personalized medicines and the necessity of maintaining digital health records are significantly driving the artificial intelligence in healthcare market. The novel technologies like artificial intelligence and machine learning are now being integrated to the healthcare systems that will allow the health professionals in early identification of the diseases and offer enhanced care services to the patients. Moreover, the data analytics, deep learning technology, natural language processing (NPL), predictive analytics, and content analytics are supporting the healthcare professionals in early diagnosis and care services.
| Report Coverage | Details |
| Market Size by 2034 | USD 613.81 Billion |
| Market Size in 2025 | USD 36.96 Billion |
| Market Size in 2024 | USD 26.69 Billion |
| Market Growth Rate from 2025 to 2034 | CAGR of 36.83% |
| Largest Market | North America |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
| Segments Covered | Component, Application, Technology, End User, and Regions |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
AI-based remedies and hardware assist healthcare organizations in easing extended processes while improving patient care. These solutions also help lower costs while increasing overall effectiveness.
Some essential increasing drivers of the global industry comprise the booming aged population, the alarming rise in chronic disruptions, and technical advancement in the healthcare sphere. The surging need for operational efficacy amongst healthcare organizations, the escalating grip of hybrid care, and the advent of vast amounts of information also furnish to the market expansion.
The rising centre from volume to value-based healthcare combined with the rise in the customer in the healthcare field will present profitable opportunities to healthcare AI producers. The flying number of security companies will also help market growth in the outlook. Consumers emerging attempt to spark the benefit of biotechnological and pharmaceutical firms through tight marketing approaches owe more upgrade the marketplace over the upcoming years.
Rising requirement for remote patient monitoring systems
Remote patient monitoring coupled with artificial intelligence enables continuous monitoring of patients, providing real-time insights into their health status. This personalized approach ensures that healthcare interventions are tailored to each patient’s unique needs, optimizing the effectiveness of treatments. Artificial intelligence algorithms can analyze medical images, such as X-rays, CT scans and MRIs, remotely and accurately. This capability is particularly valuable in areas with limited or lack of access to advanced healthcare facilities. The Covid-19 pandemic has boosted the requirement for remote patient monitoring, especially for elderly people. Remote patient monitoring is especially beneficial for managing chronic conditions such as heart problems. Artificial intelligence systems can track a patient’s overall health. As healthcare providers focus on offering remote patient monitoring for remote accessibility of patients, the deployment of artificial intelligence is observed to grow.
In March 2023, Zephyr, a company building transparent AI solutions and KangarooHealth announced a multi-layered partnership to integrate artificial intelligence and machine learning-based solutions in order to offer personalized healthcare services for remote patients with the remote patient monitoring system.
Improved diagnosis process
AI algorithms have demonstrated the capability to analyze vast amounts of medical data, including patient records and genetic information. This efficiency allows healthcare professionals to diagnose conditions more quickly and accurately, leading to better patient outcomes. AI-powered diagnostic tools can detect subtle patterns and indicators of diseases, this offers early detection and further works on early prevention of diseases. AI systems also help in assisting healthcare professionals with valuable tools, all these factors that offer improved diagnosis process act as a driver for the market’s growth.
The considerable complexity and cost of implementing AI-based processes and tools are growing concerns related to patient data security and can hinder market growth in the following years.
Complexities in adopting AI systems
Creating or deploying an artificial intelligence system for a healthcare firm can be costly. With this issue, many healthcare providers may limit themselves from adopting such services. Resistance to change is another major hindering factor for the market, healthcare professionals may resist changing their existing system to an AI-operated system that requires less human intervention. Moreover, lack of standardization of AI models is another major restraint for the market. Healthcare data is often unstructured and varies across different institutions, making it difficult to create robust and generalizable AI solutions. All these factors limit the adoption of Ai solutions in the healthcare industry by creating a major restraint for the market.
Regulatory hurdles
Developing and deploying AI applications for healthcare industry typically requires approval from different bodies including the Food and Drug Administration (FDA) or European Union. The approval process can be lengthy and costly. The prolonged process can delay AI adoption in healthcare and deter smaller companies with limited resources from entering the market. This factor acts as a major restraint for the market. Moreover, the regulations are important for data privacy and security concerns, such regulations and fluctuating guidelines may limit the development of AI systems for the healthcare industry.
There have been notable demonstrations of the capability use of Artificial Intelligence methods built on Deep Learning for medical diagnostics to grow confidence in the medical community and offer responses to the primary research society on aspects where sustained growth is most required.
The expanding set of patient health-related digital information, increasing demand for customized medicine, and the rising demand for reduced care costs are some of the significant leading forces of the market development. The growth of the global geriatric population, changing lifestyles and the increasing prevalence of chronic diseases have contributed to the increased demand for diagnosis and improved understanding of diseases in their early-stage diseases.
Technological advancements in AI for healthcare industry
Multiple technological advancements are observed to open a plethora of opportunities for the market to grow. Cloud computing is deployed in the healthcare sector with AI systems, it aims to offer scalable and cost-effective storage and processing capabilities for AI applications. This allows healthcare organizations to store and analyze enormous datasets securely. The penetration of IoT is also observed as a technological advancement in AI solutions. IoT devices such as wearable health trackers and monitors can be integrated with artificial intelligence, Ai can analyze this continuous stream of data to detect anomalies, predict potential health issues and improve patient outcomes.
One of the challenges of using AI in health care is that it requires access to large volumes of data to be efficient. Another problem is the risk of bias if the data used to form the algorithms do not represent the population as a whole. Lastly, there needs to be more standardization between different AI systems, which may make it difficult to compare outcomes or combine data from multiple sources.
The greatest challenge for AI in healthcare is not whether the technologies will be effective enough but how they will be adopted into daily clinical practice. Over time, clinicians can move into tasks that require uniquely human skills and the highest level of cognitive function, and the sole healthcare suppliers who will drop out on the full capability of AI in healthcare may be those who refuse to function alongside them.
Slower adoption in underdeveloped areas
Artificial intelligence systems deployed in the healthcare sector are costly to develop, implement and maintain. Underdeveloped regions often face financial constraints for the adoption of such services. This element delays the penetration of AI solutions in the healthcare sector. In underdeveloped areas, the healthcare sector or infrastructure may be inadequate, with limited access to healthcare facilities, medical equipment and trained healthcare professionals. Integrating artificial intelligence into such environments may not be possible or feasible until basic healthcare services are addressed. Thus, the slower adoption of AI-based services in the underdeveloped areas can pose a challenge for the market to grow.
Based on the component, the software segment was highest revenue holder in 2024. The increased adoption of the software solutions powered by artificial intelligence across the healthcare units and among the healthcare professionals, patients, and payers has led to the rapid growth of this segment. The rising investments in the adoption of the AI-based software technologies in the healthcare sector are propelling the growth of the software segment. The top healthcare companies are partnering with the software developers to design and develop artificial intelligence based software to be used in the healthcare sector.
The software segment is also anticipated to be the fastest-growing segment during the forecast period. This growth is attributed to the increasing penetration of the AI and machine learning based software in various healthcare applications across the globe. The rapid emergence and increasing adoption of the telehealth and telemedicine technologies across the global healthcare sector owing to the outbreak of the COVID-19 pandemic in 2020 has significantly contributed to the growth of the artificial intelligence software solution in the healthcare sector and this trend is expected to stay.
The clinical trials segment has dominated the market with highest market share in 2024 and dominated the global artificial intelligence in healthcare market. The rising investments in research, drug discovery, drug development, and clinical trials of the newly developed drugs have led to the increased revenue generation of the clinical trials segment in the artificial intelligence in healthcare market. The increasing number of patent expiry, growing need for fast clinical trial results, and increasing need for new drug developments has fueled the growth of this segment across the globe. Furthermore, the increasing uses of the artificial intelligence in the patient recruitment process is expected to reduce the time and costs, which is further driving the demand for the artificial intelligence in healthcare market. Moreover, the adoption of AI in the clinical trials helps in eliminating errors, produce accurate results, and save time. The favorable government policies and various healthcare startups are favoring the adoption of the AI, which is fostering the growth of this segment.
The virtual assistant is anticipated to be the most opportunistic segment during the forecast period. The integration of the AI in the virtual assistant segment is propelling owing to the lack of skilled professionals, improving access to internet, and increasing penetration of the smart devices. The rising investments in the adoption of the automated technologies in the healthcare sector are expected to fuel the growth of the virtual assistant segment.
The artificial intelligence in healthcare market is highly fragment owing to the presence of numerouskey market players. These key players are constantly engaged into various developmental strategies such as mergers, acquisitions, partnerships, collaborations, and new product launches to strengthen their position and expand their market share.
By Component
By Application
By Technology
By End User
By Geography
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