{"id":749790,"date":"2025-07-01T14:30:01","date_gmt":"2025-07-01T14:30:01","guid":{"rendered":"https:\/\/www.abnewswire.com\/pressreleases\/?p=749790"},"modified":"2025-07-01T14:30:01","modified_gmt":"2025-07-01T14:30:01","slug":"artificial-intelligence-in-healthcare-market-to-reach-usd-19691-billion-by-2030-driven-by-diagnostics-and-imaging-applications","status":"publish","type":"post","link":"https:\/\/www.abnewswire.com\/pressreleases\/artificial-intelligence-in-healthcare-market-to-reach-usd-19691-billion-by-2030-driven-by-diagnostics-and-imaging-applications_749790.html","title":{"rendered":"Artificial Intelligence in Healthcare Market to Reach USD 196.91 Billion by 2030, Driven by Diagnostics and Imaging Applications"},"content":{"rendered":"
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\"Artificial<\/a><\/div>\n
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Artificial Intelligence in Healthcare Market<\/div>\n<\/div>\n<\/div>\n
Mordor Intelligence has published a new report on the Artificial Intelligence in Healthcare Market offering a comprehensive analysis of trends, growth drivers, and future projections.<\/div>\n

Introduction<\/strong><\/p>\n

According to a 2025 report on AI in healthcare market by Mordor Intelligence, the market is estimated at USD 39.92 billion in 2025 and is projected to reach USD 196.91 billion by 2030, growing at a CAGR of 37.60 percent during the forecast period.<\/p>\n

The artificial intelligence in the healthcare market<\/a> is witnessing rapid growth as hospitals, pharmaceutical companies, and healthcare providers increasingly adopt AI tools to improve patient care and operational efficiency. AI is used for a range of applications including diagnostics, imaging analysis, drug discovery, virtual assistants, and patient management.<\/p>\n

Key Market Trends <\/strong><\/p>\n

AI in Diagnostics and Imaging <\/strong><\/p>\n

AI tools are widely used to analyze medical images such as X-rays, MRIs, and CT scans. Hospitals and diagnostic centers are adopting AI-powered imaging solutions to detect diseases like cancer, neurological conditions, and cardiovascular diseases with higher accuracy and speed. This reduces diagnostic errors and supports clinicians in providing timely treatment.<\/p>\n

Use of AI in Drug Discovery and Development <\/strong><\/p>\n

Pharmaceutical companies are leveraging AI platforms to identify new drug candidates, analyze molecular structures, and predict drug responses. AI is helping reduce the time and cost involved in drug development by accelerating research, screening compounds efficiently, and supporting clinical trial processes.<\/p>\n

Growth of Virtual Health Assistants and Chatbots <\/strong><\/p>\n

AI-based virtual assistants are being used in hospitals and clinics for appointment scheduling, medication reminders, answering patient queries, and post-discharge follow-ups. This trend is helping healthcare providers reduce administrative workloads and improve patient engagement and satisfaction.<\/p>\n

Application of AI in Personalized Medicine<\/strong><\/p>\n

AI enables analysis of patient-specific data including genetic information, medical history, and lifestyle factors to recommend tailored treatment plans. This is supporting the growth of personalized medicine, especially in oncology, where targeted therapies are crucial for effective treatment outcomes.<\/p>\n

Adoption of AI for Administrative Workflow Automation <\/strong><\/p>\n

Hospitals and healthcare providers are using AI to automate administrative tasks such as billing, claim processing, and patient data management. This trend is helping reduce operational costs, minimize errors in records, and improve workflow efficiency across departments.<\/p>\n

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Market Segmentation <\/strong><\/p>\n

By Technology<\/strong><\/p>\n

Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI\/Foundation Models, Reinforcement Learning, Others<\/strong><\/p>\n

These technologies form the backbone of AI healthcare tools. Machine learning and deep learning power predictive analytics and image interpretation, while NLP supports automated documentation and clinical decision support. Emerging technologies like generative AI and foundation models which are expanding at roughly 48% CAGR represent the fastest-growing tech area.<\/p>\n

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By Application <\/strong><\/p>\n

Robot\u2011assisted Surgery, Virtual Assistants, Precision & Personalized Medicine, Remote patient Monitoring, Fraud Detection, Others <\/strong><\/p>\n

AI is applied across care delivery and support systems. It’s used in robotic surgery, intelligent scheduling assistants, and automated billing workflows. Diagnostic imaging remains a dominant use case, with AI helping analyze scans and track disease progression. AI also supports clinical trials with data management, and aids in fraud detection and cybersecurity in patient records<\/p>\n

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By Offering <\/strong><\/p>\n

Hardware, Software, Services <\/strong><\/p>\n

Offerings in AI healthcare span physical devices, digital tools, and consultancy\/support services. Software, which includes AI platforms and specialized applications, holds a significant market share given hospitals’ reliance on digital diagnostics, workflow optimization, and predictive analytics.<\/p>\n

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By End User<\/strong><\/p>\n

Hospitals & Healthcare Providers, Patients, Pharmaceutical & Biotechnology Companies, Healthcare Payers, Others <\/strong><\/p>\n

This segmentation captures the diverse customer base for AI solutions. Hospitals and providers make up the bulk of users for diagnostic or workflow tools. Patients benefit indirectly via virtual health apps or monitoring. Pharma and biotech firms use AI for drug discovery and trial enhancement. Payers leverage AI in claims processing, fraud detection, and cost management.<\/p>\n

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By Geography<\/strong><\/p>\n

North America, Europe, Asia\u2011Pacific, Middle East & Africa, South America <\/strong><\/p>\n

Geographic segmentation highlights regional differences: North America leads due to its healthcare infrastructure and investment capacity, while Asia\u2011Pacific is identified as the fastest-growing due to rising digital adoption and government-backed health tech initiatives<\/p>\n

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Key Players <\/strong><\/p>\n