Global AI in Medical Imaging Market Set to Surge to USD 4.54 Billion by 2029 | MarketsandMarkets™

Delray Beach, FL, Nov. 25, 2025 (GLOBE NEWSWIRE) -- Rising Cross-Industry Partnerships, Expanding Big Data, and Emerging Market Potential Drive Strong 23.2% CAGR
The global AI in medical imaging market is expected to grow with a strong CAGR of 23.2%. It will increase from around USD 1.5 billion in 2024 to USD 4.5 billion by 2029. As healthcare systems worldwide confront workforce shortages, rising imaging demand, and escalating clinical complexity, AI-powered imaging solutions are becoming indispensable to diagnostic accuracy, clinical efficiency, and operational resilience.

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AI Emerges as a Strategic Imperative for Global Healthcare Leaders
What is driving this shift? Healthcare providers and governments are intensifying investments in AI to reduce radiologist workloads, enhance early detection, and improve patient outcomes. With the U.S. alone estimated to require 42,000 additional radiologists by 2033, AI solutions now play a critical role in automating routine tasks, streamlining workflows, and elevating decision support.
AI’s ability to process massive imaging datasets, integrate across modalities, and deliver interpretable insights that align with clinician workflows is also accelerating adoption. Strategic collaborations—such as those involving Microsoft, NVIDIA, GE HealthCare, AWS, Roche Pharma India, and regional governments—are further strengthening the ecosystem, propelling the development of human-aware AI systems tailored for real-world clinical use.

Market Drivers: Efficiency, Accuracy, and Workforce Support
The medical imaging industry is rapidly integrating AI to modernize diagnostics, reduce human error, and enhance imaging throughput. Leading tech companies—Microsoft, Google Cloud, IBM, Qure.ai, and others—are expanding cloud-based platforms that democratize access to regulatory-cleared AI tools. Governments are also implementing favorable regulatory frameworks, quickening deployment and fostering trust in AI’s clinical reliability.

Restraints: A Shortfall in AI Talent and Ambiguous Regulations
However, the path forward is not without barriers. A global shortage of AI specialists in cognitive computing, ML, and image analytics—combined with fragmented, evolving regulatory guidelines—continues to slow deployment. To fully unlock AI’s potential, healthcare leaders must address gaps in workforce readiness, standardize governance frameworks, and invest in training that strengthens AI proficiency across clinical environments.

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Emerging Markets: The Next Growth Frontier
Why do emerging markets matter now? Rapid healthcare investments in China, India, Brazil, Southeast Asia, Latin America, and Africa are creating high-demand environments for cost-effective, AI-enhanced imaging. With millions of new cancer cases emerging annually and rapidly expanding imaging volumes, these regions represent one of the largest untapped opportunities for scalable AI diagnostics.
Recent initiatives—such as NIRAMAI’s partnership with the Punjab Government and Roche Pharma India, Intel’s research center launch in Hyderabad, and Siemens Healthineers’ EUR 160 million innovation hub investment in Bengaluru—highlight the accelerating momentum.

Challenges: Physician Hesitancy and Perceptions of Clinical Risk
Despite growing adoption, some physicians remain reluctant to embrace AI over concerns regarding trust, tech over-reliance, and perceived threats to human-centered diagnostics. Yet as AI systems demonstrate superior accuracy in tasks such as tumor detection and workflow optimization, confidence is increasing. Radiologists and specialists are increasingly recognizing AI as an augmentative tool, not a replacement.

Market Ecosystem: Software Dominates, Hospitals Lead Adoption
Software commanded the largest market share in 2023 due to its role in advanced diagnostics, workflow optimization, and real-time analytics. Deep learning algorithms now routinely outperform traditional diagnostic approaches, reaching >90% accuracy in carcinoma detection.
Hospitals were the leading end users in 2023, driven by strong IT infrastructure, access to large imaging datasets, and rising adoption of AI for complex cases—including oncology, neurology, and cardiology.
North America maintained global leadership, fueled by high chronic disease prevalence, strong funding for ethical AI research, and significant investments in AI-driven health infrastructure.

Key Industry Players
Market leadership is defined by both global technology firms and fast-growing innovators, including:
Microsoft, NVIDIA Corporation, Merative, Intel Corporation, Google, Siemens Healthineers, GE HealthCare, Digital Diagnostics Inc., Advanced Micro Devices, Butterfly Network, Qure.ai, Lunit, Brainomix, Viz.ai, Nano-X Imaging, Enlitic, icometrix, Aidence, Therapixel, HeartFlow, InformAI, and others.

Recent Strategic Developments

• July 2024 - Microsoft partnered with Mass General Brigham and the University of Wisconsin to enhance AI models for medical imaging, boosting radiologist efficiency.
• March 2024 - Microsoft and NVIDIA expanded collaboration integrating Azure AI with the DGX Cloud and Clara suite.
• July 2024 - GE HealthCare teamed with AWS to accelerate AI-based diagnostic models.
• November 2023 - NVIDIA and the National Health Research Institute (Taiwan) adopted NVIDIA’s Blackwell platform for advanced biomedical research.
• November 2023 - Merative and Indica Labs integrated digital pathology with imaging systems to unify patient data and AI-driven analysis.

Market Insight: Why This Matters for Global Decision-Makers
As healthcare systems face rising patient loads, talent shortages, and cost pressures, AI in medical imaging is transitioning from optional innovation to strategic necessity. AI-driven insights are reshaping clinical pathways, enabling earlier interventions, reducing diagnostic variability, and strengthening system-wide capacity.
For technology leaders, investors, and healthcare executives, the next five years represent a critical window to leverage AI-driven imaging as a competitive differentiator across care delivery, patient outcomes, and operational efficiency.

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