2026 Global: Artificial Intelligence (Ai) In Medicine Market-Competitive Review (2032) report
Description
The 2026 Global: Artificial Intelligence (Ai) In Medicine Market-Competitive Review (2031) report features the global market size and projected growth/decline data for the period 2021 through 2032. The report primarily provides an examination of the business strategies for the ten largest global companies in the market and how their strategies differ.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for artificial intelligence (ai) in medicine market by geography and historical trend. The scope of the report extends to sizing of the artificial intelligence (ai) in medicine market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
PathAI, Tempus, Google (including DeepMind/Google Health), NVIDIA, and Microsoft are among the ten major companies shaping the Artificial Intelligence in Medicine market because each brings distinct strengths—PathAI in digital pathology and diagnostic augmentation, Tempus in clinical and genomic data integration for precision oncology, Google/DeepMind in breakthrough medical imaging and protein‑folding research, NVIDIA in high‑performance computing and healthcare model infrastructure, and Microsoft in cloud, clinical AI tools and documentation workflows. PathAI’s machine‑learning pathology tools improve diagnostic consistency and accelerate biomarker discovery for clinical trials, supporting both hospital workflows and pharma partnerships. Tempus aggregates molecular and clinical records to power decision support for oncology and expanding disease areas, enabling clinicians to match patients with targeted therapies and trials. Google/DeepMind’s imaging and research projects have demonstrated radiologist‑level performance in screening tasks and driven foundational advances such as AlphaFold for protein structure prediction, which underpins drug discovery and translational research. NVIDIA supplies GPUs, inference‑software and curated healthcare AI stacks used to train and deploy large medical models and imaging pipelines at scale, making it a critical infrastructure partner across industry and academia. Microsoft combines Azure health services, cloud data platforms, and clinical Copilot/documentation solutions to integrate AI into electronic health records, imaging, and care coordination for health systems.
Siemens Healthineers, Philips, GE HealthCare, Medtronic, and IBM/Merative complete the list of ten major players by contributing AI‑enabled devices, imaging, monitoring, and enterprise analytics that are widely deployed across hospitals and health systems. Siemens and Philips lead in AI‑driven imaging reconstruction, workflow automation, and diagnostic support across radiology, cardiology and lab diagnostics, delivering regulatory‑cleared algorithms and integrated platforms that accelerate diagnosis and treatment planning. GE HealthCare’s extensive portfolio includes hundreds of cleared AI/ML‑enabled devices for imaging and point‑of‑care diagnostics, along with analytic tools for precision medicine and operations. Medtronic embeds AI into a broad device ecosystem—from insulin pumps and cardiac devices to surgical systems—leveraging decades of physiological data to personalize therapy and enable predictive maintenance and remote monitoring. IBM’s Watson Health lineage (now Merative and related analytics offerings) and Accenture’s implementation capabilities support large‑scale AI adoption in clinical decision support, claims and population health by combining NLP, data integration and domain consulting to move pilots into production.
Collectively these ten companies span the full AI in Medicine value chain—from foundational compute and cloud (NVIDIA, Microsoft), to algorithm research and clinical models (Google/DeepMind, PathAI, Tempus), to medical devices and imaging systems with regulatory footprints (Siemens Healthineers, Philips, GE HealthCare, Medtronic), and to enterprise deployment and services (IBM/Merative, Accenture)—creating interoperable ecosystems that accelerate diagnostics, personalized treatment, workflow automation and drug development while navigating regulatory and clinical validation requirements.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for artificial intelligence (ai) in medicine market by geography and historical trend. The scope of the report extends to sizing of the artificial intelligence (ai) in medicine market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
PathAI, Tempus, Google (including DeepMind/Google Health), NVIDIA, and Microsoft are among the ten major companies shaping the Artificial Intelligence in Medicine market because each brings distinct strengths—PathAI in digital pathology and diagnostic augmentation, Tempus in clinical and genomic data integration for precision oncology, Google/DeepMind in breakthrough medical imaging and protein‑folding research, NVIDIA in high‑performance computing and healthcare model infrastructure, and Microsoft in cloud, clinical AI tools and documentation workflows. PathAI’s machine‑learning pathology tools improve diagnostic consistency and accelerate biomarker discovery for clinical trials, supporting both hospital workflows and pharma partnerships. Tempus aggregates molecular and clinical records to power decision support for oncology and expanding disease areas, enabling clinicians to match patients with targeted therapies and trials. Google/DeepMind’s imaging and research projects have demonstrated radiologist‑level performance in screening tasks and driven foundational advances such as AlphaFold for protein structure prediction, which underpins drug discovery and translational research. NVIDIA supplies GPUs, inference‑software and curated healthcare AI stacks used to train and deploy large medical models and imaging pipelines at scale, making it a critical infrastructure partner across industry and academia. Microsoft combines Azure health services, cloud data platforms, and clinical Copilot/documentation solutions to integrate AI into electronic health records, imaging, and care coordination for health systems.
Siemens Healthineers, Philips, GE HealthCare, Medtronic, and IBM/Merative complete the list of ten major players by contributing AI‑enabled devices, imaging, monitoring, and enterprise analytics that are widely deployed across hospitals and health systems. Siemens and Philips lead in AI‑driven imaging reconstruction, workflow automation, and diagnostic support across radiology, cardiology and lab diagnostics, delivering regulatory‑cleared algorithms and integrated platforms that accelerate diagnosis and treatment planning. GE HealthCare’s extensive portfolio includes hundreds of cleared AI/ML‑enabled devices for imaging and point‑of‑care diagnostics, along with analytic tools for precision medicine and operations. Medtronic embeds AI into a broad device ecosystem—from insulin pumps and cardiac devices to surgical systems—leveraging decades of physiological data to personalize therapy and enable predictive maintenance and remote monitoring. IBM’s Watson Health lineage (now Merative and related analytics offerings) and Accenture’s implementation capabilities support large‑scale AI adoption in clinical decision support, claims and population health by combining NLP, data integration and domain consulting to move pilots into production.
Collectively these ten companies span the full AI in Medicine value chain—from foundational compute and cloud (NVIDIA, Microsoft), to algorithm research and clinical models (Google/DeepMind, PathAI, Tempus), to medical devices and imaging systems with regulatory footprints (Siemens Healthineers, Philips, GE HealthCare, Medtronic), and to enterprise deployment and services (IBM/Merative, Accenture)—creating interoperable ecosystems that accelerate diagnostics, personalized treatment, workflow automation and drug development while navigating regulatory and clinical validation requirements.
Table of Contents
32 Pages
- 1.0 Scope of Report and Methodology
- 2.0 Market SWOT Analysis and Players
- 2.1 Market Definition
- 2.2 Market Segments
- 2.3 Market Strengths
- 2.4 Market Weaknesses
- 2.5 Market Threats
- 2.6 Market Opportunities
- 2.7 Major Players
- 3.0 Competitive Analysis
- 3.1 Market Player 1
- 3.2 Market Player 2
- 3.3 Market Player 3
- 3.4 Market Player 4
- 3.5 Market Player 5
- 3.6 Market Player 6
- 3.7 Market Player 7
- 3.8 Market Player 8
- 3.9 Market Player 9
- 3.10 Market Player 10
- 4.0 Comparative Business Strategies
- 4.1 Comparative Business Strategies of Player 1 and 2
- 4.2 Comparative Business Strategies of Player 1 and 3
- 4.3 Comparative Business Strategies of Player 1 and 4
- 4.4 Comparative Business Strategies of Player 2 and 3
- 4.5 Comparative Business Strategies of Player 2 and 4
- 4.6 Comparative Business Strategies of Player 3 and 4
- 5.0 Appendix
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