The global artificial intelligence in healthcare market is estimated to be valued at USD 28.91 Bn in 2025 and is expected to exhibit a compound annual growth rate (CAGR) of 38.9% during the forecast period (2025-2032), reaching USD 288.50 Bn by 2032.
The global artificial intelligence in healthcare market is expected to exhibit robust growth during the forecast period. This is mostly due to explosion of healthcare data, rising need for better diagnostic accuracy and patient outcomes, and mounting pressure to control healthcare costs.
Hospitals, diagnostic centers, pharmaceutical companies, and medical device companies are increasingly adopting advanced technologies like artificial intelligence. These technologies help them automate routine tasks, optimize operations, and reduce costs.
Top players are constantly introducing new AI solutions for pharmaceutical and healthcare industries. For instance, Exscientia launched AWS AI-powered Platform to advance drug discovery.
The novel platform uses Amazon Web Services (AWS) technology and combines generative AI for drug design with robotic lab automation. It helps the company create high-quality drug candidates more quickly and at a lower cost.
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In terms of component, hardware segment is estimated to contribute the highest market share of 40.5% in 2025. This is attributable to increasing investments in developing versatile AI hardware platforms and devices.
Healthcare providers have been actively investing in hardware infrastructure like computer systems, networking devices, computer peripherals, and accessories. These upgrades enable the efficient operation of complex AI algorithms and predictive models.
Top companies have introduced powerful servers, data storage systems, and GPU-enabled computers made for training deep learning models using large healthcare datasets. Advancements in high bandwidth internet connectivity have further aided real-time data transmission between different AI hardware endpoints.
Rising focus on miniaturizing AI hardware is paving way for the development of AI-powered portable medical devices. For example, Samsung India recently launched new AI-powered mobile CT systems in India. These solutions combine advanced imaging hardware with AI capabilities to improve diagnostics.
Players are incorporating sophisticated AI processors as well as sensory interfaces in portable devices like smart wearables, therapeutic robots, patient monitors, and surgical tools. This allows continuous health monitoring and delivery of personalized care outside hospitals.
Neuro prosthetics powered by AI hardware are also gaining popularity for restoring motor functions in patients. Furthermore, heavy R&D investments by industry players have reduced hardware costs, thus making advanced AI systems affordable for healthcare providers.
As per Coherent Market Insights’ latest artificial intelligence in healthcare market analysis, speech recognition segment is expected to dominate the industry, owing to its wide applicability across healthcare activities. It will likely account for a prominent market share of 36.5% in 2025.
AI-based speech recognition systems are minimally invasive and user-friendly. This is making them ideal for clinical documentation, decision support, and patient communication.
Healthcare professionals have switched to using voice enabled digital assistants and interactive voice response systems for accessing patient records, reviewing test reports, and receiving diagnostic advice. Natural language proficiency of these systems enhances user experience while gaining clinical insights from vast unstructured speech data.
Speech recognition in combination with computer vision enhances capabilities of robotic surgical assistants and rehabilitation robots. AI systems can comprehend vocal instructions of surgeons and therapists during complex procedures or therapies, while automating documentation of the session.
Pharmaceutical companies are also testing speech-based conversational agents for health monitoring and compliance of patients on long term medication. New speed recognition models are being introduced in the market. For instance, Speechmatic launched a new medical speech recognition model with 93% accuracy and 50% fewer critical errors.
Advancements in deep learning algorithms have significantly boosted speech recognition accuracy on medical terminology and slangs used in clinical conversations. This has amplified adoption across healthcare workflow touchpoints involving patient-doctor interactions.
Based on application, imaging & diagnostics segment is expected to account for 43.5% of the AI in healthcare industry share in 2025. This can be attributed to increasing usage of AI in medical imaging sciences.
Advanced algorithms are helping radiologists and image analysts in diagnostic labs to process high volumes of visual medical data and detect subtle anomalies. Deep learning models are trained on thousands of labeled images to recognize tissue patterns as well as abnormalities linked to diseases.
AI applications have demonstrated high accuracy in detecting signs of cancer, neurological disorders, and cardiovascular issues from medical images well before symptoms arise. As a result, there is a rising growing adoption of AI in diagnostic segment.
AI-powered imaging systems use computer vision and deep learning techniques to provide automated quantitative analysis as well as assist physicians in generating precise diagnostic reports. This significantly reduces workload of radiologists and pathology technicians.
Players are also developing AI-driven robotic imaging devices and imaging analytics suites integrated with EHR systems. Such solutions empower near real-time exchange of scan reports between labs and consulting doctors. This fosters collaborative diagnostics practices.
For instance, researchers at Imperial College London and Imperial College healthcare NHS trust developed a new AI stethoscope that can detect major heart conditions in about 15 seconds. This news solution can analyze tiny differences in heartbeat and blood flow undetectable to the human ear, and can take a quick ECG at the same time.
AI imaging tools have also proven effective in medical education and research by supporting data-driven investigations. Continued improvements in algorithm performance can integrate advanced diagnostics at the point-of-care.
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North America leads from the forefront when it comes to AI adoption in healthcare. As per the latest AI in healthcare market analysis, North America is expected to account for 40.8% of the global market share in 2025. This is attributable to rising adoption of AI in healthcare sector and strong presence of leading players.
Healthcare institutions across nations like the U.S. are incorporating AI tools for personalized care, treatment decisions, drug discovery, and precision diagnosis. This is expected to boost growth of the artificial intelligence in healthcare market during the forthcoming period.
Major tech and healthcare companies like Microsoft, Google, and NVIDIA are investing heavily in AI research. This has created strong AI expertise focused on improving patient care.
Many universities and research centers are at the forefront of using advanced AI and machine learning in healthcare. Their investment and strong infrastructure give North American companies and hospitals an advantage in using AI for personalized care, treatment choices, drug development, and accurate diagnosis.
Asia Pacific is emerging as the fastest growing regional market for artificial intelligence in healthcare. Countries like China, Japan, South Korea, and India offer a unique combination of large populations, growing healthcare needs, increasing consumer spending on wellness technologies as well as government initiatives to promote digital healthcare. This presents a massive opportunity for AI to make quality care more affordable and accessible for all.
Presence of a vibrant AI startup ecosystem and low-cost hubs for insourcing AI product development and testing helps global companies to establish Asia Pacific as their development and deployment center. Rapid advancements in infrastructure, along with rising medical standards, point towards Asia becoming the global leader in innovative AI technologies that can achieve healthcare for all.
The United States is expected to lead the global artificial intelligence in healthcare market revenue during the assessment period. Strong government support, high spending on healthcare transformation, and early adoption of new technologies are helping the market grow. Major healthcare providers and technology companies in the nation are integrating AI tools for predictive analytics, clinical decision-making, and workflow optimization.
For instance, in June 2025, Universal Health Services (UHS) began using Hippocratic AI’s Generative AI Healthcare Agents to improve post-discharge patient engagement. The AI agents assist UHS staff with patient follow-ups, symptom checks, care reminders, and alerts to clinicians when needed.
China is anticipated to emerge as the fastest-growing artificial intelligence in healthcare market during the assessment period. This is mostly due to government initiatives like the “Healthy China 2030” plan and heavy investments in AI innovation. The country’s large population, along with increasing healthcare digitization, has created strong demand for AI-driven diagnostics, telemedicine, and hospital management systems.
Leading Chinese tech firms such as Baidu, Alibaba, and Tencent are actively partnering with hospitals to deploy AI solutions in radiology, pathology, and patient monitoring. In addition, supportive regulations and pilot programs for AI-based medical devices are helping accelerate commercialization as well as adoption across healthcare facilities nationwide.
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| Report Coverage | Details | ||
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| Base Year: | 2024 | Market Size in 2025: | USD 28.91 Bn |
| Historical Data for: | 2020 To 2024 | Forecast Period: | 2025 To 2032 |
| Forecast Period 2025 to 2032 CAGR: | 38.9% | 2032 Value Projection: | USD 288.50 Bn |
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| Companies covered: |
GE Healthcare, Siemens Healthineers, Philips Healthcare, NVIDIA, Intel, Babylon Health, Komodo Health, Aidoc, Google Health, Exscientia, Butterfly Network, Relay Therapeutics, PathAI, Viz.ai, Canon Medical Systems, Microsoft, Oncora Medical, Biosymetrics, Arterys, Ada Health |
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The global artificial intelligence in healthcare market growth is driven by rising need to analyze vast amounts of patient data to improve outcomes and streamline clinical workflows. As data volumes and computing power continue increasing, AI can help providers to develop more personalized care plans and precision medicine approaches.
Healthcare industry around the globe has witnessed high adoption of artificial intelligence-based virtual assistants in recent years. Increasing workload on physicians and nurses as well as the need for improved patient experience are encouraging healthcare organizations to use AI technologies that can automate routine tasks and provide answers to common medical queries without human intervention.
Virtual healthcare assistants powered by conversational AI are capable of answering basic questions about symptoms, providers, prescription refills, and also scheduling routine appointments. This allows clinical staff to focus their time and expertise on more complex cases and procedures.
As these AI systems continue to learn from each patient interaction, they are getting better at understanding medical terms as well as the context of the questions. This has made virtual assistance a cost-effective first point of contact for many patients.
The trend is especially prominent in outpatient and after-hours care. When access to doctors and nurses is limited due to non-working hours or locations far from hospitals, a virtual presence that patients can reach out to with questions has provided much-needed support. This has helped address issues of overburdened emergency rooms as well. For healthcare providers, virtual assistants reduce menial tasks allowing clinicians to spend more one-on-one time with patients who truly need their expertise, leading to higher job satisfaction levels.
Precision medicine, which involves tailoring medical treatment to the individual characteristics of each patient, holds immense promise for delivering the right treatment to the right patient at the right time. However, implementing precision medicine approaches requires compiling and analyzing huge amounts of patient genetic and molecular data.
Healthcare systems have found it challenging to gather and process this volume of complex data through manual means. Thus, artificial intelligence plays a key role in unlocking the potential of precision medicine.
Advanced machine learning tools and computational capabilities of AI are helping researchers analyze disparate data sets and identify subtle patterns and correlations that otherwise would be difficult to detect. Genomic and molecular profiling of tumors can now be supplemented with clinical, lifestyle and environmental factors of individual patients.
AI's ability to evaluate huge genomic and health records data sets means that with each new record available, the systems become more effective in finding precision treatment matches. Healthcare providers are thus able to move away from a trial-and-error approach to a more predictive, pre-emptive model of treatment.
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About Author
Komal Dighe is a Management Consultant with over 8 years of experience in market research and consulting. She excels in managing and delivering high-quality insights and solutions in Health-tech Consulting reports. Her expertise encompasses conducting both primary and secondary research, effectively addressing client requirements, and excelling in market estimation and forecast. Her comprehensive approach ensures that clients receive thorough and accurate analyses, enabling them to make informed decisions and capitalize on market opportunities.
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