Agentic AI in Healthcare Market By Component (Software {AI platforms, Agentic algorithms}, Services {Consulting, Integration}, Hardware {AI chips, Computing infrastructure}), By Technology (Machine Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Generative AI), By Application (Clinical Decision Support Systems, Medical Imaging & Diagnostics, Virtual Health Assistants, Drug Discovery & Development, Patient Monitoring & Management, Administrative Workflow Automation), By End-user (Hospitals & Clinics, Diagnostic Centers, Pharmaceutical & Biotech Companies, Research Institutes, Health Tech Companies, Others), Global Market Size, Segmental analysis, Regional Overview, Company share analysis, Leading Company Profiles And Market Forecast, 2025 – 2035

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What trends will shape Agentic AI in Healthcare Market in the coming years?

The Agentic AI in Healthcare Market accounted for USD 616.10 Million in 2024 and USD 897.04 Million in 2025 is expected to reach USD 38408.4 Million by 2035, growing at a CAGR of around 45.6% between 2025 and 2035. Agentic AI in Healthcare Market refers to the applied artificial intelligence that has autonomous decision-making and can learn novel, intricate data and can take actions independently of human instigation. These systems are more than conventional AI as they become intelligent agents in the clinical, diagnostic, and operational environment of healthcare.

The major trends impacting this market entail the integration of generative AI in medical imaging and diagnostics, autonomous virtual health assistants, and AI-guided clinical decision support. Adoption of personalized medicine, the growth in the amount of healthcare information, and a global concern with efficiency and reduced costs are all helping to hasten adoption. Particularly, agentic AI might transform patient care coordination, chronic disease care, and the drug discovery process in the future, thus impacting the healthcare value chain in significant ways. 

What do industry experts say about the Agentic AI in Healthcare Market trends?

"The potential of agentic AI in healthcare is immense, from autonomous robotic surgeries to AI-driven personalized medicine. But we need rigorous oversight to ensure these systems align with human values and clinical standards."

• Dr. Fei-Fei Li, Co-Director of Stanford’s Human-Centered AI Institute

Which segments and geographies does the report analyze?

What are the key drivers and challenges shaping the Agentic AI in Healthcare Market?

How is the rising demand for intelligent automation transforming healthcare operations?

Rapid demand for intelligent automation in global healthcare systems is providing the Agentic AI in Healthcare Market with a huge amount of traction. There is always an urge in hospitals and clinics to be more efficient, minimize human errors, and provide value-based care. Agentic AI, due to its autonomous nature, is contributing to the automation of workflows, including scheduling, billing, diagnostics, and treatment planning. These smart systems are decreasing the administrative load of healthcare professionals by performing tasks that are repetitive and rule based. This allows staff to focus more on patient-centric care, thereby enhancing service quality. 

Moreover, agentic AI guarantees 24/7 operation, consistency, and real-time analysis of massive healthcare datasets. Hospitals are achieving better clinical outcomes and operational performance through improved decision-making support. Government-backed digital healthcare initiatives are especially benefiting the market. In 2023, the National Institutes of Health (NIH) allocated $1.5 billion for AI-related healthcare research, including autonomous diagnostic systems and agentic AI for clinical decision support, further strengthening this transformation. From radiology to chronic disease monitoring, every segment is being automated. The Agentic AI in Healthcare Market is expected to grow rapidly, as automation becomes the new reality for smart healthcare systems.

Can AI-driven diagnostics enhance clinical accuracy and patient outcomes?

The Agentic AI in Healthcare Market is gaining momentum due to the innovative power of AI-based diagnostics in improving precision and patient outcomes. Conventional diagnostic techniques are often time-consuming and require manual interpretation, which can be prone to human error or inefficiency. AI systems with strong agentic capabilities, especially those utilizing deep learning and computer vision, can rapidly scan medical images, detect anomalies, and flag potential issues with a high degree of accuracy. These capabilities are particularly critical in areas like oncology, radiology, and pathology, where early and accurate diagnosis is essential.

Agentic AI minimizes diagnostic errors and enables real-time physician support, leading to quicker and more informed decisions. These systems continue to learn from new data, becoming increasingly accurate over time. New analysis from the Tony Blair Institute (TBI) highlights that better use of AI in triage and navigation services through general practice could free up 29 million appointments annually and yield productivity gains worth £340 million a year for 111 and GP reception teams. Such data reinforces the growing confidence clinicians have in AI tools for decision-making. As hospitals aim to standardize diagnostics across departments and meet rising demand for value-based care, the Agentic AI in Healthcare Market continues to expand, grounded in diagnostic efficiency and system-wide productivity.

Are ethical concerns limiting the deployment of autonomous AI in care?

A significant threat to the Agentic AI in Healthcare Market is the fact that there is an ethical issue of having autonomy during decision-making in patient care. Even though agentic AI has the potential to take actions without human prompting, it is questionable to make critical healthcare decisions based on it, and this aspect is, indeed, ethically and legally problematic. Accountability is a concern to its stakeholders, who would be accountable in case an AI system misdiagnoses a patient or prescribes the wrong treatment to the wrong treatment. Transparency is also viewed as important to both patients and practitioners when AI systems are operated as black boxes and make decisions that lack rationality. In addition, the fear of a possible algorithm bias, i.e., the likelihood of discrimination against particular groups of patients because of training data, occurs.

These concerns bring reluctance towards the complete implementation of autonomous AI, particularly in the critical care setting. The regulatory environment concerning AI ethics in medicine is also under development, which makes deployment more difficult. Healthcare professionals are therefore being conservative and adopting a position where they can be innovative and at the same time ethical. They may pose a drag on the otherwise high rate of growth of the Agentic AI in Healthcare Market, particularly in areas where the law protecting patient rights is stringent.

Can agentic AI accelerate drug discovery in pharmaceutical R&D pipelines?

The Agentic AI in Healthcare Market can develop fantastic potential in the field of pharmaceutical research, especially regarding the discovery of drugs. The conventional method of drug development is lengthy, uncertain, and highly expensive in most cases, consuming more than ten years and a billion dollars. This model has been challenged by agentic AI that can turn into an autonomous system capable of biomedical data analysis, molecular target identification, and compound interactions simulation at a scale never evident in the past. The systems may also be used to repurpose already existing drugs through a rapid mapping of their efficacy against new diseases, as observed during the COVID-19 pandemic.

Furthermore, agentic AI platforms evolve via learning machines, which allows the drug development practice to become more dynamic and data-informed. Biopharmaceutical firms are turning to AI companies more and more so as to incorporate these tools within their pipelines. Through this synergy, new therapeutics are being discovered much faster and could have a better likelihood of being approved by the regulatory bodies. The Agentic AI in Healthcare Market is quickly gaining prominence as a solution, and it is becoming the cornerstone of transforming the face of the medical field with the adoption of these innovations by pharmaceutical companies.

How will AI virtual agents reshape chronic disease remote patient care?

The great potential of the Agentic AI in Healthcare Market is evolving the remote care model as applied in the management of chronic illnesses with the use of AI-based virtual agents. Chronic diseases such as diabetes, high blood pressure, and COPD need to be monitored all the time, involve the patient, and should be dealt with at the right time. The AI virtual assistants have an agentic approach where they are able to monitor the patient data proactively, provide personal reminders on health, and even warn caregivers of irregular trends. These artificial intelligence agents are 24/7 digital companions with lower demand for regular visits and higher followability rates to treatment plans.

They apply natural language processing and predictive analytics to engage and communicate with patients in a natural manner by providing real-time advice and help. This promotes healthier outcomes and the satisfaction of the patients. Further, virtual agents are aiding in closing the underserved and rural opportunities, whereby access to care is poor. Since the demand for home-based care will only increase in the future, the Agentic AI in Healthcare Market has a great opportunity to offer scalable and effective digital health products, which can transform the delivery of chronic care.

What are the key market segments in the Agentic AI in Healthcare industry?

Based on the Component, the Agentic AI in Healthcare Market has been classified into Software, Services, and Hardware. Of them, the largest is Software related to the increased demand in AI platforms and agentic algorithms capable of operating autonomously to analyze medical data and make clinical decisions. The software solutions are part of diagnostics, patient monitoring activities, and the automation of administrative tasks.

Another service that takes prominence is consulting and integration, where healthcare providers seek advice on how to implement AI technologies. In the meantime, hardware components such as the AI chips and computing structure are used to sustain the performance of the system, but their level of priority falls short relative to the software.

Based on the Technology, the Agentic AI in Healthcare Market has been classified into Machine Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, and Generative AI. The biggest share is retained for Machine Learning, as it has the most extensive use in predictive analytics, diagnostic machines, and treatment suggestions.

NLP is growing fast, and more so in the field of patient interaction systems and electronic health record analysis (EHR). Computer Vision is changing medical imaging, and Generative AI is coming to the scene in drug discovery and synthetic data generation. The niche of Reinforcement Learning will advance in the realms of individual treatment approaches. 

Which regions are leading the Agentic AI in Healthcare Market, and why?

The North America Agentic AI in Healthcare Market is already high currently, and this is expected to rise as a result of high healthcare infrastructure development, high investment in AI-related research, and high ratings of early adoption in digital health technologies. Having such major technology companies as IBM, Google, Microsoft, and Amazon, and their active interactions with healthcare organizations, contribute to the extensive use of agentic AI solutions.

The innovations introduced by AI in the clinical environment are followed by regulatory support of the technology in various countries, especially the U.S., which moves the process of innovation and implementation to a faster pace. In addition, the region is characterized by high expenditures in healthcare and a rich development of the reimbursement model, making it suitable for artificial intelligence integration. 

The Asia-Pacific Agentic AI in Healthcare Market is becoming the region with the most significant growth due to the increasing digital infrastructure, a surge in the demand for healthcare facilities, and promote AI uses at the state or national level, such as in China, India, Japan, and South Korea. A combination of a high population, the rising prevalence of chronic diseases, and the expanding interest in affordable AI-based diagnostics offers a promising environment where agentic AI can help solve some of its problems.

Specifically, China is spending much on its AI healthcare companies, and India is using AI to serve its population in rural areas. The region is likely to experience exponential growth with the rapid urbanization, increased awareness of digital health, and the positive regulatory reforms that will be witnessed over the next few years.   

What does the competitive landscape of the Agentic AI in Healthcare Market look like?

The Agentic AI in Healthcare Market has an intense competitive rivalry with the characteristics of fast development, industry collaborations, and investment intensity of large tech and healthcare organizations. IBM Watson Health, Google Health, Microsoft Azure, Amazon Web Services, Oracle Health, and Siemens Healthineers are confident market leaders with their high-end AI standards and smart automation technology. Such companies concentrate on the creation of agentic and autonomously operating nature AI systems responsible for decision making in diagnostics, patient monitoring, and workflow streamlining. NVIDIA is facilitating real-time AI compute with AI-centered high-performance chips, and GE HealthCare and Philips are incorporating agentic into imaging and diagnostics.

Competitors such as Tempus Labs and Butterfly Network are using AI to do precision oncology and point-of-care imaging devices. The key strategic measures are cloud integration, AI-as-a-service concepts, renouncing of AI start-ups, and cooperating programs with medical institutions and research centers in R&D. The competitive model revolves around scalability, reality testing, and regulatory proof. Due to the increasing rates of adoption, personalized care, cost-effectiveness, and clinical reliability have become the key priorities of companies which developing a strong and innovative-driven market of agentic AI in healthcare.

Agentic AI in Healthcare Market, Company Shares Analysis, 2024

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Which recent mergers, acquisitions, or product launches are shaping the Agentic AI in the Healthcare industry?

• In March 2024, Hippocratic AI launched a safety-focused agentic AI model emphasizing patient safety through low-risk, non-diagnostic tasks such as medication adherence and post-discharge follow-ups.
• In January 2024, Google DeepMind introduced AMIE (Articulate Medical Intelligence Explorer), an AI system designed to assist in diagnostic reasoning and medical conversations. It aims to enhance doctor-patient interactions by providing real-time, evidence-based suggestions.

Report Coverage:

By Component

• Software
  • AI platforms
  • Agentic algorithms
• Services
  • Consulting
  • Integration
• Hardware
  • AI chips
  • Computing infrastructure

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision
• Reinforcement Learning
• Generative AI

By Application

• Clinical Decision Support Systems
• Medical Imaging & Diagnostics
• Virtual Health Assistants
• Drug Discovery & Development
• Patient Monitoring & Management
• Administrative Workflow Automation

By End-user

• Hospitals & Clinics
• Diagnostic Centers
• Pharmaceutical & Biotech Companies
• Research Institutes
• Health Tech Companies
• Others

By Region

North America

• U.S.
• Canada

Europe

• U.K.
• France
• Germany
• Italy
• Spain
• Rest of Europe

Asia Pacific

• China
• Japan
• India
• Australia
• South Korea
• Singapore
• Rest of Asia Pacific

Latin America

• Brazil
• Argentina
• Mexico
• Rest of Latin America

Middle East & Africa

• GCC Countries
• South Africa
• Rest of Middle East & Africa

List of Companies:

• IBM Watson Health
• Google Health
• Microsoft
• Amazon Web Services
• Oracle Health
• Siemens Healthineers
• GE HealthCare
• NVIDIA Corporation
• Philips Healthcare
• Epic Systems Corporation
• Cerner Corporation
• Medtronic plc
• Tempus Labs
• Butterfly Network
• C3.ai

Frequently Asked Questions (FAQs)