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Key drivers include expanding data volumes, AI technological advancements, a shortage of healthcare workers, and rising chronic illness rates. AI applications in diagnostics, personalized medicine, and cloud computing enhance global healthcare efficiency.
AI in Healthcare Market
AI in Healthcare Market
Dublin, Oct. 06, 2025 (GLOBE NEWSWIRE) — The “AI in Healthcare Market Report by Offering, Technology, Application, End-User, Country & Company Analysis | Forecasts 2025-2033” has been added to ResearchAndMarkets.com’s offering.
The AI in Healthcare Market is expected to reach US$ 419.56 billion by 2033 from US$ 25.74 billion in 2024, with a CAGR of 36.36% from 2025 to 2033. Growing data quantities, technology breakthroughs, the need for precision medicine, a lack of workers, and the rise in chronic illnesses are the main drivers of AI in healthcare. AI-assisted diagnostics, cloud computing, and tailored treatment all increase efficiency and make it possible for global healthcare systems to embrace them more widely.
The application of machine learning, natural language processing, computer vision, and other AI technologies to evaluate intricate medical data and enhance clinical results is known as artificial intelligence (AI) in healthcare. It helps with imaging, personalized treatment, drug discovery, diagnostics, and administrative automation. Clinicians may better understand vast datasets, identify illnesses early, and optimize treatment pathways with the help of AI-driven tools. Furthermore, robotic systems, AI chatbots, and virtual nurses lessen the workload for clinicians while improving patient involvement. AI provides scalable, data-driven solutions to enhance accuracy, efficiency, and accessibility in a variety of medical domains, such as cardiology, radiology, oncology, and mental health, as healthcare systems deal with increasing demands.
The market for AI in healthcare is growing because of a number of important factors. Healthcare practitioners are using AI tools in response to the growing availability of medical data and the demand for quicker, more accurate diagnostics. These technologies increase patient monitoring and care delivery, automate administrative tasks, and strengthen clinical decision-making. Deployment is now more scalable and effective thanks to developments in cloud computing and AI algorithms. Furthermore, the need for AI-based solutions that customize treatment regimens for each patient is being driven by the increased emphasis on customized medicine. AI is becoming a crucial component of contemporary healthcare infrastructure as systems look to lower costs, enhance results, and manage resource limits.
Smarter, faster, and more scalable solutions are being made possible by the quick development of AI and cloud infrastructure, which is completely changing the way healthcare is delivered. Large medical datasets may be processed by AI algorithms to manage hospital procedures, automate diagnoses, and find anomalies. Cloud computing systems such as Google Cloud, AWS, and Microsoft Azure provide the processing capacity required for sophisticated AI applications in a range of healthcare contexts. “Agents of Care,” AI-powered virtual assistants that automate administrative duties like scheduling and documentation, were introduced by Innovaccer in February 2025. By doing so, they help decrease clinician fatigue and increase productivity. These developments signal a significant shift toward intelligent and connected health ecosystems by enabling healthcare systems to deliver precise, individualized, and prompt care while lowering operational burdens.
AI makes personalized medicine possible by evaluating clinical, lifestyle, and genomic data to customize treatments for each patient. Machine learning algorithms are able to identify illness risks, forecast treatment outcomes, and recommend the best drug combinations. In the fields of uncommon disease management, mental health, and oncology, this trend is especially prominent. PieX AI revealed its planned on-device AI necklace for mental health monitoring in January 2025. It will use patented Sensing Technology to provide individualized cognitive and emotional insights. This development demonstrates how AI is extending beyond clinics to wearable technology, allowing for individualized, real-time interventions. AI plays a crucial role in converting one-size-fits-all healthcare into precision medicine as people want more individualized treatment.
People no longer need to make regular excursions to medical facilities since remote patient monitoring allows them to monitor their health from the comfort of their own homes. Patient satisfaction increases as a result of less travel, waiting room, and other healthcare-related annoyances. It improves access to healthcare, especially for people living in rural or underdeveloped areas, enabling patients to communicate with medical professionals and obtain top-notch treatment wherever they may be. As an instance, the mCareWatch 241 is a virtual patient monitoring smartwatch that was introduced in July 2024 by the Australian company mCare Digital and the Georgia-based Internet of Things (IoT) startup KORE. The watch’s features include a geo-fence alarm, a pedometer, a call function, GPS tracking, reminders, a heart rate monitor, speed dialing, fall detection, a non-movement detection feature, a mobile app, and a web dashboard. By including an SOS button, users can request emergency assistance.
AI in healthcare is mostly dependent on private patient information, including genetic profiles, imaging, and electronic health records. This brings up serious issues with data privacy, particularly in light of laws like GDPR (EU) and HIPAA (USA). Serious harm, legal ramifications, and a decline in patient trust could arise from improper data processing or breaches. Strong access restrictions, encryption, anonymization, and safe data sharing are all requirements for healthcare businesses. Additionally, third-party AI providers need to adhere to stringent compliance guidelines. Managing innovation while maintaining patient privacy and ethical data use is still one of the biggest obstacles to the long-term, sustainable use of AI in healthcare.
It takes a significant investment in infrastructure, data integration, qualified staff, and ongoing model training to implement AI solutions in the healthcare industry. The adoption of AI-specific software, secure cloud services, and compatible EHR systems by hospitals and clinics raises their operating and capital expenses. Furthermore, for AI models to continue to work well, they need big, high-quality datasets and constant upkeep. For small and rural healthcare providers, these financial and technical requirements can be particularly taxing. Early adoption may be discouraged by the potential years-long return on investment. Expanding access to AI in healthcare will depend on lowering costs through collaborations, government grants, and scalable cloud-based solutions.
Recent Developments in the AI in Healthcare Market:
In order to increase diagnostic precision and optimize operations, Wipro GE Healthcare introduced the Versana Premier R3 ultrasound system in March 2025. The technology, which is produced under the ‘Make in India’ initiative, helps clinicians manage the increasing burden of non-communicable diseases in India by providing improved picture clarity and flexible scanning.
Amgen announced in February 2025 that it would invest USD 200 million in a biotechnology innovation center located in Hyderabad. The center will advance drug development and discovery by concentrating on AI-driven healthcare innovation. By 2025, the initiative hopes to increase India’s contribution to global biopharmaceutical innovations and generate 2,000 new employment.
In January 2025, MedMitra AI obtained INR 3 crore in seed money to improve healthcare by implementing AI-powered solutions. By tackling inefficiencies in patient care, enhancing diagnostics, and integrating multimodal data, the startup seeks to enhance clinical decision-making. It focuses on chronic care and general medicine in India.
November 2024: In order to expedite the transition of Generative AI (GenAI) from Proof of Concept (POC) to large-scale, production-ready solutions, Boston Consulting Group partnered with Amazon Web Services, Inc.
Upstage and Amazon Web Services, Inc. partnered in June 2024. With the goal of leveraging state-of-the-art, secure cloud technology and services to enable clients to take advantage of new generative AI capabilities, this arrangement strengthened the two businesses’ collaboration.
In an effort to help healthcare professionals locate pertinent and reliable clinical information more quickly, Google (Alphabet Inc.) introduced a new generative AI tool in October 2023.
Key Attributes
Report Attribute
Details
No. of Pages
200
Forecast Period
2024-2033
Estimated Market Value (USD) in 2024
$25.74 Billion
Forecasted Market Value (USD) by 2033
$419.56 Billion
Compound Annual Growth Rate
36.3%
Regions Covered
Global
Key Topics Covered
1. Introduction
2. Research & Methodology
3. Executive Summary
4. Market Dynamics
4.1 Growth Drivers
4.2 Challenges
5. Global AI In Healthcare Market
5.1 Historical Market Trends
5.2 Market Forecast
6. Market Share Analysis
6.1 By Offering
6.2 By Technology
6.3 By Application
6.4 By End-User
6.5 By Countries
7. Offering
7.1 Hardware
7.2 Software
7.3 Services
8. Technology
8.1 Machine Learning
8.2 Context Aware Computing
8.3 Natural Language Processing
8.4 Others
9. Application
9.1 Robot-Assisted Surgery
9.2 Virtual Nursing Assistant
9.3 Administrative Workflow Assistance
9.4 Fraud Detection
9.5 Dosage Error Reduction
9.6 Clinical Trial Participant Identifier
9.7 Preliminary Diagnosis
9.8 Others
10. End-User
10.1 Healthcare Providers
10.2 Pharmaceutical and Biotechnology Companies
10.3 Patients
10.4 Others
11. Countries
11.1 North America
11.2 Europe
11.3 Asia-Pacific
11.4 Latin America
11.5 Middle East & Africa
12. Value Chain Analysis
13. Porter’s Five Forces Analysis
13.1 Bargaining Power of Buyers
13.2 Bargaining Power of Suppliers
13.3 Degree of Competition
13.4 Threat of New Entrants
13.5 Threat of Substitutes
14. SWOT Analysis
14.1 Strength
14.2 Weakness
14.3 Opportunity
14.4 Threats
15. Pricing Benchmark Analysis
15.1 Amazon Web Services Inc.
15.2 General Vision Inc.
15.3 Google Inc.
15.4 Intel Corporation
15.5 Medtronic
15.6 Micron Technology Inc.
15.7 Microsoft Corporation
15.8 Next It Corporation
15.9 Nvidia Corporation
15.10 Siemens Healthcare
16. Key Players Analysis
16.1 Amazon Web Services Inc.
16.2 General Vision Inc.
16.3 Google Inc.
16.4 Intel Corporation
16.5 Medtronic
16.6 Micron Technology Inc.
16.7 Microsoft Corporation
16.8 Next It Corporation
16.9 Nvidia Corporation
16.10 Siemens Healthcare
For more information about this report visit https://www.researchandmarkets.com/r/97wu56
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