ROCKVILLE, MARYLAND , August 14, 2026 — The healthcare agentic artificial intelligence market reached USD 3.2 billion in 2025. Demand is projected to rise from USD 3.9 billion in 2026 to USD 24.6 billion by 2036, recording a compound annual growth rate of 20.2% over the 2026–2036 forecast period and creating an absolute opportunity of USD 20.7 billion.

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Key Findings

• Market value stood at USD 3.2 billion in 2025 as healthcare IT teams expanded controlled pilots around clinical and administrative workflows.
• Value is estimated at USD 3.9 billion in 2026 and forecast to reach USD 24.6 billion by 2036 at 20.2% CAGR.
• Clinical Decision Agents are expected to hold 44.0% share by agent type in 2026.
• Clinical Decision Support is projected to account for 38.0% share by application in 2026.
• Hospitals are anticipated to capture 42.0% share by end user in 2026.
• Cloud-based deployment is estimated to represent 61.0% share in 2026.
• Large Language Models are forecast to hold 49.0% share by core technology in 2026.
• In September 2025, the Office of the Assistant Secretary for Technology Policy reported that 71% of U.S. non-federal acute care hospitals used predictive AI integrated with the EHR in 2024, up from 66% in 2023; 86% of system-affiliated U.S. hospitals used predictive AI in 2024 versus 37% of independent hospitals.

Growth Drivers

• Clinical workflow automation ranks high in relative impact, with geographic relevance in the USA, UK and Canada and a short-term timeline; agentic AI gains priority where repetitive tasks reduce time for direct care.
• Cloud and model infrastructure also ranks high, relevant across North America, Europe and Asia Pacific on a short-term timeline; enterprise platforms lower deployment friction through compute and security controls.
• EHR and data integration carries medium impact for hospitals and payer systems on a medium-term timeline; agents become more useful when approved patient context returns inside the workflow.
• Decision-support governance and care coordination pressure are medium-impact factors with medium- to long-term timelines in regulated and aging-care systems.

Segment Analysis

By Agent Type

Clinical Decision Agents are projected to account for 44.0% share in 2026. They support faster context retrieval and guided comparison with approved clinical guidance where decisions require consistent evidence review.

By Application

Clinical Decision Support is expected to hold 38.0% share in 2026. Hospitals need records and care protocols converted into usable guidance while clinicians retain final responsibility.

By End User

Hospitals are anticipated to lead with 42.0% share in 2026 because they combine clinical complexity with heavy administrative workload.

By Deployment Model

Cloud-based Deployment is estimated to represent 61.0% share in 2026 due to scalable model hosting and central governance needs. In March 2026, AWS launched Amazon Connect Health, a purpose-built agentic AI solution for EHR and contact-center workflows that automates administrative tasks across five specialized healthcare AI agents, including Patient Verification and Ambient Documentation, with Appointment Management, Patient Insights and Medical Coding capabilities available in preview.

By Core Technology

Large Language Models are forecast to hold 49.0% share in 2026 because healthcare agents rely on natural-language interaction and multi-step reasoning.

Country-Level Growth Comparison

The comparison covers a 4.2 percentage-point range between the USA and Singapore. In July 2026, NHS England said its AI triage tool in the NHS App was due to reach more than 200,000 patients within the next 12 months, while an initial Sussex trial reduced phone queues by 29%.

Competitive Landscape

Key companies include Microsoft Corporation, Google LLC, Oracle Corporation, NVIDIA Corporation, Salesforce, Inc., Amazon Web Services, Inc., IBM Corporation and Cognizant Technology Solutions Corporation. Competition centers on workflow fit and integration depth; vendors differentiate through clinical-assistant design and agent governance.

Recent Developments

• Microsoft Corporation (March 3, 2025): Microsoft Dragon Copilot provides the healthcare industry’s first unified voice AI assistant that enables clinicians to streamline clinical documentation, surface information and automate tasks.
• Oracle Corporation (March 4, 2025): Oracle Health Clinical AI Agent reduces physician documentation time by 30%.
• Salesforce (February 28, 2025): Salesforce prescribes Agentforce for Health to speed time to treatment and improve outcomes with digital labor.
• NVIDIA Corporation (January 13, 2025): NVIDIA partners with industry leaders to advance genomics, drug discovery and healthcare.
• PathAI (June 30, 2025): PathAI receives FDA clearance for AISight® Dx platform for primary diagnosis.
• U.S. Food and Drug Administration (January 6, 2025): FDA issues comprehensive draft guidance for developers of artificial intelligence-enabled medical devices.
• Amazon Web Services (March 5, 2026): Introducing Amazon Connect Health, agentic AI built for healthcare.
• NHS England (July 4, 2026): NHS accelerates artificial intelligence rollout to cut waiting times and improve care for millions.

Restraints

• Clinical trust and liability ranks high in relative impact globally on a short-term timeline; providers can slow deployment when recommendations and escalation rules are unclear.
• Health data access limits ranks high in regulated healthcare markets on a short-term timeline; permission gaps can restrict automation when agents cannot reach approved records.
• Integration cost and workflow disruption carries medium impact for hospitals and payers on a medium-term timeline.
• Skill and governance gaps carries medium impact in developing and mid-sized markets on a long-term timeline.

How to Choose: Buyer Decision Guide

Procurement and R&D teams evaluating healthcare agentic AI solutions should apply the following criteria drawn from the report’s strategic implications and analyst assessment:

1.     Assess the agent against a defined clinical or administrative workflow with a clear human-review point and measurable quality of underlying data.

2.     Require traceability before an agent moves from pilot use into routine care operations.

3.     Prioritize platforms that integrate with existing EHR, imaging, coding and patient-engagement workflows rather than requiring separate systems.

4.     Confirm security, model monitoring and central governance capabilities for regulated care settings.

5.     Verify that review responsibility and escalation rules are established from the start of any controlled pilot.

6.     Evaluate specialty clinical, revenue-cycle/coding, patient-engagement or research/trial agents according to the specific high-context workflow under consideration.

Report Scope

The Healthcare Agentic Artificial Intelligence Market covers autonomous and semi-autonomous AI agents used to support clinical decisions, documentation, coding, patient engagement and workflow coordination. Segmentation includes agent type (Clinical Decision Agents, Administrative Automation Agents, Patient Engagement Agents, Research & Discovery Agents), application (Clinical Decision Support, Medical Documentation, Virtual Patient Assistance, Drug Discovery), end user (Hospitals, Clinics, Telehealth Providers, Pharmaceutical Companies), deployment model (Cloud-based, Hybrid, SaaS, API Integration) and core technology (Large Language Models, Multi-agent Systems, Natural Language Processing, Predictive Artificial Intelligence). Regions covered are North America, Latin America, Europe, Asia Pacific and Middle East & Africa; countries profiled include USA, China, UK, Germany, Japan, Canada and Singapore. Forecast period is 2026–2036.

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 Flag: The quote attributed to analyst S.N. Jha is sourced directly from published commentary on the report page and requires standard PR media sign-off before official press wire dis