The Global Artificial Intelligence in Diagnostics Market is analyzed in this report across component, diagnostic type, deployment mode, end-user, and region, highlighting major trends and growth forecasts for each segment.

Introduction

Artificial Intelligence (AI) is increasingly shaping diagnostic workflows, enabling healthcare providers to enhance the accuracy, speed, and efficiency of disease detection. AI-powered technologies are being deployed across medical imaging, pathology, genomics, cardiology, and remote diagnostics to support early identification, risk assessment, patient monitoring, and clinical decision-making.

The global AI in diagnostics market is projected to reach approximately USD 5.50 billion by 2030, driven by the growing burden of chronic diseases, an aging global population, and rising demand for early and precise diagnostics. With the added need for streamlined diagnostic workflows, the market, valued at around USD 1.69 billion in 2024, is expected to grow at a robust CAGR of 21.78% over the forecast period.

Market Dynamics

The AI in diagnostics market is expanding rapidly, propelled by a combination of clinical demand and technological advancement. Key growth drivers include the need for more accurate, timely diagnostics, the rising incidence of chronic and lifestyle-related diseases, and continued improvements in AI algorithms and computing power. AI integration in diagnostic workflows is helping providers reduce errors, optimize operations, and enhance clinical outcomes.

AI’s impact is particularly evident in areas such as medical imaging, pathology, genomics, cardiology, and remote diagnostics, where it enables faster image interpretation, pattern recognition, and risk stratification. The growing deployment of electronic health records (EHRs), digital imaging platforms, and wearable health technologies further supports AI adoption. Regulatory approvals from bodies such as the U.S. FDA have validated several AI-enabled diagnostic devices, reinforcing clinical trust and market uptake. In South Korea, government-backed programs, led by the Ministry of Science and ICT, have catalyzed the development and implementation of AI-driven diagnostic tools across healthcare systems.

Emerging opportunities include AI-assisted remote diagnostics, predictive disease modeling, and personalized diagnostic planning. Healthcare systems are increasingly turning to AI for early detection, patient triage, continuous monitoring, and clinical workflow automation. These innovations are also fueling growth in tele-diagnostics and virtual care models, which help extend access to diagnostics in underserved regions.

Key trends shaping the market include greater adoption of AI-driven predictive analytics for population health management, the rise of multimodal diagnostics that combine imaging, genomic, and pathology data, and a stronger emphasis on explainable, clinically validated AI tools. AI’s ability to detect subtle diagnostic patterns and predict disease progression is supporting a shift toward proactive, precision-based healthcare delivery.

Segment Highlights and Performance Overview

By Component
Software dominates the component segment, accounting for approximately 40%–45% of the market. As the core enabler of AI functionality, software solutions, ranging from analytics engines to AI-as-a-Service platforms, are in high demand across diagnostics providers seeking to improve accuracy and scalability.

By Diagnostic Type
Medical Imaging Diagnostics represents the leading segment, contributing approximately 55%–60% of market share. AI is widely adopted in radiology, CT, MRI, ultrasound, and X-ray imaging for its ability to enhance image analysis, detect anomalies, and streamline diagnostic workflows.

By Deployment Mode
Cloud-based deployment holds the largest share, roughly 50%–55%, driven by its scalability, accessibility, and lower infrastructure costs. Cloud platforms enable healthcare providers to implement AI tools remotely, without the need for extensive on-site resources.

By End User
Hospitals and clinics lead the end-user segment, accounting for approximately 50%–55% of the market. These institutions manage the highest diagnostic volumes and are investing in AI to improve clinical efficiency, shorten turnaround times, and support better patient outcomes.

Geographical Analysis

The global AI in diagnostics market is segmented across North America, Europe, Asia-Pacific, South & Central America, and the Middle East & Africa.

North America holds the dominant market share, approximately 50%, supported by advanced healthcare infrastructure, early adoption of AI-enabled diagnostic tools, and widespread use of EHRs and digital imaging technologies.

Asia-Pacific is poised to register the highest CAGR, estimated between 42% and 50%, driven by increasing healthcare digitization, significant investments in AI applications across China, India, and Japan, and the rapid deployment of innovative AI tools in regional healthcare systems.

Competition Landscape

The competitive landscape is defined by a mix of established healthcare technology firms, major IT vendors, and AI-focused startups, all competing through innovation, strategic alliances, and product expansion.

Key players profiled in this report include Siemens Healthineers, GE Healthcare, IBM, NVIDIA Corporation, Aidoc Medical Ltd, PathAI, Inc., Qure.ai, Tempus AI, AliveCor, Zebra Medical Vision, Inc., VUNO Inc., Arterys Inc., Digital Diagnostics, Inc., and Imagen Technologies.

Recent Developments

• On September 17, 2025, Siemens Healthineers announced a strategic partnership with Stryker to co-develop a robotic system for neurovascular diagnostics and interventions, including stroke and aneurysm treatments. This collaboration strengthens the role of AI-powered robotic solutions in diagnostics and is expected to expand the market for advanced surgical and imaging tools.
• On August 26, 2025, PathAI announced the expansion of its AISight® Dx primary diagnosis platform to support VENTANA DP 200 and DP 600 slide scanners. This upgrade enhances accessibility and compatibility for AI-driven pathology diagnostics, enabling broader integration across laboratories and accelerating the adoption of AI in clinical pathology.

Segmentation:

By Component:

• Software
  • AI algorithms & platforms
  • Imaging & diagnostic software
  • Predictive analytics & decision support tools
• Hardware
  • AI-enabled diagnostic devices
  • Imaging systems with embedded AI
• Services
  • Integration & deployment services
  • Consulting & training
  • Maintenance & support

By Diagnostic Type:

• Medical Imaging Diagnostics
• Laboratory Diagnostics
• Multi-modal Diagnostics
• Others

By Deployment Mode:

• Cloud-based
• On-premise 

By End User:

• Hospitals & Clinics
• Diagnostic Imaging Centers
• Research & Academic Institutes
• Pharmaceutical & Biotech Companies
• Others

Companies included in the report:

• Siemens Healthineers
• GE Healthcare
• IBM
• NVIDIA Corporation
• Aidoc Medical Ltd
• PathAI, Inc
• Qure.ai
• Tempus AI
• AliveCor
• Zebra Medical Vision, Inc
• VUNO Inc
• Arterys Inc
• Digital Diagnostics, Inc
• Imagen Technologies