Agentic AI in Healthcare Market Entry Barriers for Topical Dermatology Products

Revenue, 2025

USD 0.79 Billion

Forecast, 2035

USD 33.66 Billion

CAGR, 2026-2035

45.6%

Report Coverage

Global

Agentic AI in Healthcare Market Trends for 2026

The global agentic AI in healthcare market size was estimated at USD 0.79 billion in 2025 and is predicted to increase from USD 1.14 billion in 2026 to approximately USD 33.66 billion by 2035, expanding at a CAGR of 45.6% from 2026 to 2035.

The escalating demand for personalized solutions in diverse sectors, including drug discovery and patient treatments, is impacting the adoption of agentic AI. Moreover, the industry is focusing on the integration of agentic AI systems into robotic surgery, with extensive outcomes.

Key Takeaways

• Agentic AI in healthcare industry poised to reach USD 1.14 billion by 2026.
• Forecasted to grow to USD 33.66 billion by 2035.
• Expected to maintain a CAGR of 45.6% from 2026 to 2035.
• North America was dominant in the agentic AI in healthcare market in 2025.
• Asia Pacific is expected to grow at the fastest CAGR during the forecast period.
• By agent system, the single agent systems segment dominated the market in 2025.
• By agent system, the multi-agent systems segment is expected to grow rapidly in the coming years.
• By product, the ready-to-deploy agents segment registered dominance in the market in 2025.
• By product, the build-your-own agents segment is expected to be the fastest-growing during 2026-2035.
• By technology, the machine learning segment accounted for a major share of the market in 2025.
• By technology, the context-aware computing segment is expected to witness rapid expansion in the stdied years.
• By application, the medical imaging segment led the agentic AI in healthcare market in 2025.
• By application, the personalized treatment & drug discovery segment is expected to grow at the fastest CAGR in the predicted timeframe.
• By end use, the healthcare companies segment was dominant in the market in 2025.
• By end use, the healthcare payers segment is expected to register the fastest growth during the forecast period.

What are the Major Applications of Agentic AI in Healthcare?

Primarily, the adoption of autonomous AI systems, goal-driven agents that can reason, plan, and implement multi-step workflows with lowered human oversight, is referred to as agentic AI in healthcare market. Inclusion of a substantial catalyst, like the leveraging agents in handling prior authorizations, claims processing, and billing, is impacting the overall market progression. Also, some agents are facilitating the conduction of proactive, empathetic patient monitoring, symptom assessment, & medication management.

Trends & Future Outlook of the Agentic AI in Healthcare Market

Elevating Proactive Clinical Decision Support (CDS)

Specifically, AI agents in ICUs and ERs are providing real-time diagnostic insights, evaluating imaging & patient history to recommend treatments.

Transforming AI in Medical Devices

The market is exploring the integration of agentic AI into robotic surgery and monitoring devices to improve procedures and understand patient data.

Fostering Modern Hospital Orchestration

The wider adoption of these agents is supporting the management of predictive maintenance of medical equipment, boost bed management, and synchronize staff scheduling based on real-time patient volume.

Quick Facts Table

Segmentation Analysis

Agent System Insights

How did the Single Agent Systems Segment Lead the Market in 2025?

In 2025, the single agent systems segment captured the largest share of the agentic AI in healthcare market. This is driven by its being easier to locate, integrate, and scale as compared to multi-agent architectures, & have significant application in targeted, high-friction, & repetitive tasks. They are now converting into more specialized forms, including virtual nurses for post-discharge follow-ups or emphasized diagnostic agents to assess specific imaging modalities.

Multi-Agent Systems

In the future, the multi-agent systems segment is expected to witness rapid growth. Ongoing advances in Large Language Models (LLMs) & Multi-Agent Reinforcement Learning (MARL) are enabling agents to unite, learn from experience, and adapt to novel protocols, which raises diagnostic accuracy and lowers medication errors. Moreover, their adoption is impelled by simplifying hospital operations, especially managing patient flow, automating report notifications, & enhancing resource administration to raise affordability.

Product Insights

Which Product Dominated the Agentic AI in Healthcare Market in 2025?

The ready-to-deploy agents segment was dominant in the market in 2025. This primarily covers specialized, pre-built, and production-ready systems to operate complex, multi-step, autonomous tasks with minimal human involvement. Nowadays, these agents prefer integration with crucial EHR platforms, like Epic and Oracle Health, by leveraging FHIR standards.

Build-Your-Own Agents

In the coming era, the build-your-own agents segment is expected to expand rapidly. Globally accelerating need for tailored AI solutions to manage complex, domain-specific, and non-linear workflows is fueling the segmental expansion. Also, healthcare systems are demanding automated administrative tasks, like billing, scheduling, and documentation, which is also supporting the evolution of these agents. The market is encouraging the use of low-code/no-code platforms, which allow non-technical users to build and deploy these agents.

Technology Insights

Why did the Machine Learning Segment Lead the Market in 2025?

In 2025, the machine learning segment held a major share of the agentic AI in healthcare market. This technology assists these agents in the analysis of large volume, multi-modal data, like electronic health records (EHRs), imaging, & genomics, to offer customized, real-time insights. ML can boost diagnostic accuracy in radiology, dermatology, & pathology by detecting anomalies in CT scans, MRIs, and X-rays more rapidly than manual analysis.

Context-Aware Computing

Moreover, the context-aware computing segment is predicted to expand fastest. The worldwide progression is propelled by the use of sensors, IoT devices, and AI to recognize a patient's or provider's situation in real-time, providing tailored care, escalating safety, and escalating operational effectiveness. The most common instance is context-aware EHR systems, which explore automatic display of relevant data for the patient in a specific room.

Application Insights

Which Application Led the Agentic AI in Healthcare Market in 2025?

The medical imaging segment captured the dominating share of the market in 2025. Globally expanding burden of patient volumes & complex imaging studies is fueling the need for AI agents to pre-process images, find anomalies, and minimize interpretation times. These advanced agents are focusing on a combination of 2D/3D imaging with patient data for greater diagnostic precision.

Personalized Treatment & Drug Discovery

The personalized treatment & drug discovery segment is estimated to grow rapidly. AI agents are providing hyper-personalized medicine, which unites real-time data from IoT devices, wearables, Electronic Health Records (EHRs), & genomic profiles to adjust treatments as necessary. Many systems are executing simulation of complex biological interactions, estimation of potential side effects & effectiveness long before wet-lab testing.

End Use Insights

Why did the Healthcare Companies Segment Dominate the Market in 2025?

In 2025, the healthcare companies segment accounted for the biggest share of the agentic AI in healthcare market. This mainly encompasses leading technology providers, specialized AI players, and advanced healthcare, pharmaceutical, and diagnostics firms. Extensive AI agents serve as "additional staff" for documentation, also to lower cognitive load on clinicians & relieve burnout. Additionally, agents implement the analysis of molecular structures and simulate clinical trial outcomes to accelerate R&D.

Healthcare Payers

The healthcare payers segment will expand rapidly. A major driver is the use of agentic AI for consistent monitoring of transaction patterns to terminate fraud in real-time before payments, which crucially lowers the $17 billion lost per year to fraud. These payers are stepping towards touchless claims processing, where agents identify anomalies, cross-reference clinical context, and authorize claims autonomously.

Regional Insights

How did North America Dominate the Market in 2025?

North America registered dominance in the agentic AI in healthcare market, due to the increasing administrative burdens, rising need for operational effectiveness, and rigorous investments in AI-enhanced technologies. Whereas, the region is emphasizing AI scribes that listen to patient-doctor conversations, develop summaries, and combine directly with Electronic Medical Records (EMRs). Particularly, Canada Health Infoway is promoting this with an AI Scribe Program and facilitating 10,000 licenses to primary care clinicians.

U.S. Market Trends

However, the U.S. market implemented pre-trained, specialized AI agents for specific tasks, like in radiology, oncology, or scheduling, with direct integration into workflows.

For instance,

• In October 2025, Accenture joined with Gemini Enterprise to provide agentic AI solutions, progressing on the successful adoption of Google Cloud technologies for organizations across industries.

Immersive Infrastructure & Higher Adoption are Driving the Asia Pacific

In the coming era, the Asia Pacific is predicted to witness the fastest expansion in the agentic AI in healthcare market. Significant drivers are having strong cloud-native infrastructure, 5G networks, and huge, various data sources. As well as, the region is majorly shifting towards agentic AI to convey greater productivity over the gen AI alone.

China Market Trends

Day by day, China is putting efforts into innovating "Agent Hospitals," by using specialized AI agents that integrate to handle patient cases, which can perform approximately 85% of standard clinical duties. Alongside, the Chinese government is spurring AI-assisted "intelligent terminals" and agents in major sectors by 2027.

Key Players' Offerings in the Agentic AI in Healthcare Market

SWOT Analysis

Strengths

• Agentic AI evolves personalized, dynamic treatment plans that rely on a patient’s ideal genetic, historical, and real-time behavioral data.
• They can serve as digital assistants for home care, monitoring patient metrics via wearables & bringing out follow-up actions, like scheduling a virtual visit.

Weaknesses

• Incomplete, inaccurate, or biased data can result in weak performance & inequitable outcomes, which affect patient care.
• The use of autonomous AI can develop risks of unpredictable behavior and hallucinations.

Opportunities

• Advanced AI agents will solely design and test drug candidates, which will majorly cut development timelines from years to months.
• Prospective agents will unite with surgeons, learning from previous procedures to strengthen surgical techniques and personalization.

Threats

• It can be possible manipulation of agents by an attacker to operate vulnerable actions, like exporting, deleting, or changing patient records.
• Specifically in multi-agent systems, a single error or hallucination in one agent can spread quickly to others.

What are the Prominent Developments in the Agentic AI in Healthcare Market?

• In February 2026, Superhealth launched SuperOS, an agentic AI operating system to run hospital operations across clinical & administrative functions.
• In January 2026, Greenway Health unveiled its Agentic AI Factory by collaborating with Amazon Web Services (AWS) to redefine prospects of healthcare technology.

Segments Covered in the Report

By Agent System

• Single Agent Systems
• Multi-Agent Systems

By Product

• Ready-to-Deploy Agents
• Build-Your-Own Agents

By Technology

• Machine Learning
  • Deep Learning
  • Supervised
  • Unsupervised
  • Others (Reinforcement Learning, Semi-supervised)
• Natural Language Processing
  • Smart Assistance
  • OCR (Optical Character Recognition)
  • Auto Coding
  • Text Analytics
  • Speech Analytics
• Classification & Categorization
  • Context-aware Computing
  • Computer Vision

By Application

• Medical Imaging
• Personalized Treatment & Drug Discovery
• Electronic Health Records (EHRs)
• Remote Patient Care
• Clinical Decision-Making
• Risk Prediction & Pandemic Preparedness
• Genomic Data Analysis
• Chronic Disease Management
• Hospital Resource Optimization
• Medical Research & Data analysis
• Others

By End Use

• Healthcare Providers
• Healthcare Companies
• Academic & Research Institutes
• Healthcare Payers
• Others

By Region

• North America
  • U.S.
  • Canada 
  • Mexico 
  • Rest of North America
• South America
  • Brazil
  • Argentina
  • Rest of South America
• Europe 
  • Western Europe 
    • Germany 
    • Italy
    • France
    • Netherlands
    • Spain
    • Portugal 
    • Belgium
    • Ireland
    • UK 
    • Iceland 
    • Switzerland
    • Poland
    • Rest of Western Europe
  • Eastern Europe 
    • Austria
    • Russia & Belarus 
    • Türkiye
    • Albania 
    • Rest of Eastern Europe 
• Asia Pacific
  • China 
  • Taiwan
  • India 
  • Japan 
  • Australia and New Zealand
  • ASEAN Countries (Singapore, Malaysia)
  • South Korea 
  • Rest of APAC 
• MEA 
  • GCC Countries
    • Saudi Arabia 
    • United Arab Emirates (UAE)
    • Qatar 
    • Kuwait 
    • Oman 
    • Bahrain 
  • South Africa
  • Egypt 
  • Rest of MEA