Artificial Intelligence (AI) In Diagnostics Market Size, Share, Opportunities, And Trends By Component (Software, Hardware), By Diagnostic Type (Radiology, Pathology, Cardiology, Oncology, Neurology, Others), By Application (Disease Detection, Image Analysis, Risk Assessment, Predictive Analysis, Others), By End-User (Hospitals And Clinics, Diagnostic Laboratories, Research Institutions, Others), And By Geography - Forecasts From 2024 To 2029

The AI in diagnostics market is expected to grow at a CAGR of 33.47%, reaching a market size of US$7.268 billion in 2029 from US$1.716 billion in 2024.

The use of Artificial Intelligence (AI) in the diagnostics market has transformed medical diagnosis and therapy. AI algorithms and machine learning approaches have shown impressive skills in analyzing massive volumes of medical data and producing significant insights for accurate and efficient diagnosis. Artificial intelligence-driven diagnosis is promoting significant development in the medical sector, from radiology and pathology to cardiology and cancer diagnosis. With the enhanced skills of practitioners using AI-enabled technologies, diagnostic accuracies increase, saving valuable time.

In addition, these AI systems can learn from real-world data and improve over time, therefore proving to be very good companions for healthcare practitioners. The AI in diagnostics market growth has enormous promise for revolutionizing healthcare delivery by offering faster, more accurate diagnoses, improving patient outcomes, and saving lives.

Advancements in Machine Learning and Deep Learning Algorithms enhanced the AI in Diagnostics Market Growth.

Machine learning and deep learning algorithms have significantly contributed to the expansion of AI in the diagnostics business. These algorithms have shown an extraordinary ability to handle and analyze massive volumes of medical data, allowing for precise and rapid diagnosis. According to a report published by WHO, a deep learning system detected skin cancer with an accuracy of 94.5%, outperforming human dermatologists. Furthermore, according to a study published in the Journal of the American Medical Association, an AI system properly recognized breast cancer in mammograms with a sensitivity of 94.5%. These developments demonstrate the power of machine learning and deep learning algorithms in improving diagnostic accuracy and patient outcomes.

AI in Diagnostics Market: Integration of AI into Medical Imaging Technologies.

Medical imaging integrated with AI has brought several changes in the diagnostics industry. Several pieces of literature support the idea that the application of AI algorithms can improve the quality and efficiency of medical picture processing. A recent article in Nature shows evidence that an AI system outperforms radiologists at diagnosing lung cancer from CT images with 97% sensitivity. Another test in The Lancet Oncology reported that an AI system correctly diagnosed breast cancer on mammograms with 90.2% sensitivity. These studies are examples of the capability to improve diagnosis by integrating AI and medical imagery technology.

Improvement in Data Security and Privacy Measures Strengthen AI in Diagnostics Market.

Improvements in data security and privacy policies have facilitated AI use in the diagnostics sector. Data breaches and privacy issues have been among the major impediments to AI use in health. On the other hand, advances in encryption, anonymization methods, and secure data transport protocols have addressed these issues. Data security and privacy advancements have instilled trust in patients and healthcare professionals, allowing for the broad use of AI in diagnostics.

Enhanced Processing Power and Storage Capabilities in AI in Diagnostics Market.

AI in diagnostics has grown dramatically as processor power and storage capacity have improved. Because of the exponential development in processing power and the availability of large-scale storage options, massive volumes of medical data may now be analyzed in real-time. For example, research published in the Journal of the American Medical Association demonstrated that AI algorithms with an area under the receiver operating characteristic curve (AUC-ROC) of 0.936 may reliably detect diabetic retinopathy by analyzing retinal pictures. These processing power and storage advances have revolutionized diagnostic speed and efficiency, allowing for rapid and precise medical judgments.

AI in the Diagnostics Market Geographical Outlook

• North America is the Market Leader in the AI Diagnostics Market.

North America holds a significant share of the AI Diagnostics market. This can be linked to factors such as a strong healthcare infrastructure, new technologies, and a favorable regulatory environment. Several significant players in the AI business, including prominent healthcare facilities and research organizations, are located in the region. Furthermore, North America has seen major expenditures in AI research and development, which has fueled the expansion of AI in the diagnostics market. North America continues to employ AI for diagnostic purposes, thanks to an emphasis on innovation and technical developments.

AI in the Diagnostics Market Recent Development:

• In September 2024, Roche introduced new AI-driven cancer diagnostics by expanding its digital pathology open environment. The company's digital pathology environment will bridge many innovative AI-based pathology labs to help clinics improve patient care and extend personalized healthcare. It has integrated more than 20 advanced artificial algorithms from eight new collaborations. By applying AI technology, this, in turn, can support scientists and pathologists in cancer diagnostics and cancer research.
• In May 2024, GE HealthCare launched a new generation of radiation therapy computer tomography solutions, including novel software and hardware solutions. These solutions will contribute to increasing image accuracy while simplifying stimulation for personalized and seamless oncology pathways for both patients and health professionals.
• In March 2023, Philips Healthcare, one of the leading health technology companies, announced the release of its new AI-powered integrated diagnostics approach. It will help get fully interoperable smart imaging systems and informatics solutions connected with oncology, radiology, cardiology, and pathology to advance precision in diagnosis and treatment.

AI in the Diagnostics Market Company Products:

• IBM Watson Imaging AI: This product uses deep learning techniques to help with medical picture analysis. It helps radiologists discover and characterize anomalies in multiple imaging modalities, such as X-rays, CT scans, and MRIs, enhancing diagnostic accuracy and efficiency.
• AIRx: An image reconstruction method based on artificial intelligence (AI) that improves the clarity and resolution of medical pictures derived from computed tomography (CT) scans. By decreasing image noise and boosting picture clarity, AIRx helps radiologists make more accurate diagnoses and improve patient outcomes.
• AI-Powered Radiology Solutions: Aidoc practices deep learning algorithm analysis of medical images such as CTs, MRIs, and X-rays. Utilizing AI technologies, the company can help radiologists identify key diagnostics, such as cerebral hemorrhages, pulmonary embolisms, and fractures. Aidoc automates radiological workflow for faster diagnosis, flagging problem results, and issuing automatic notifications.

AI in the Diagnostics market is segmented and analyzed as given below:

• By Component
  • Software
  • Hardware                
• By Diagnostic Type
  • Radiology
  • Pathology
  • Cardiology
  • Oncology
  • Neurology
  • Others       
• By Application
  • Disease Detection
  • Image Analysis
  • Risk Assessment
  • Predictive Analysis
  • Others    
• By End-User
  • Hospitals And Clinics
  • Diagnostic Laboratories
  • Research Institutions
  • Others    
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain    
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • Japan
    • China
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

1. INTRODUCTION

1.1. MARKET OVERVIEW

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY  

2.1. Research Data

2.2. Sources

2.3. Research Design

3. EXECUTIVE SUMMARY

3.1. Research Highlights

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porters Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

5. AI IN DIAGNOSTICS MARKET, BY COMPONENT

5.1. Introduction

5.2. SOFTWARE

5.3. HARDWARE                 

6. AI IN DIAGNOSTICS MARKET, BY DIAGNOSTIC TYPE

6.1. Introduction

6.2. Radiology

6.3. Pathology

6.4. Cardiology

6.5. Oncology

6.6. Neurology

6.7. Others        

7. AI IN DIAGNOSTICS MARKET, BY APPLICATION

7.1. Introduction

7.2. Disease Detection

7.3. Image Analysis

7.4. Risk Assessment

7.5. Predictive Analysis

7.6. Others     

8. AI IN DIAGNOSTICS MARKET, BY END-USER

8.1. Introduction

8.2. Hospitals and Clinics

8.3. Diagnostic Laboratories

8.4. Research Institutions

8.5. Others     

9. AI IN DIAGNOSTICS MARKET, BY GEOGRAPHY

9.1. Introduction

9.2. North America

9.2.1. United States

9.2.2. Canada

9.2.3. Mexico

9.3. South America

9.3.1. Brazil

9.3.2. Argentina

9.3.3. Others

9.4. Europe

9.4.1. United Kingdom

9.4.2. Germany

9.4.3. France

9.4.4. Italy

9.4.5. Spain

9.4.6. Others

9.5. Middle East and Africa

9.5.1. Saudi Arabia

9.5.2. UAE

9.5.3. Others

9.6. Asia Pacific

9.6.1. Japan

9.6.2. China

9.6.3. India

9.6.4. South Korea

9.6.5. Indonesia 

9.6.6. Taiwan

9.6.7. Others

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

10.1. Major Players and Strategy Analysis

10.2. Emerging Players and Market Lucrativeness

10.3. Mergers, Acquisitions, Agreements, and Collaborations

10.4. Vendor Competitiveness Matrix

11. COMPANY PROFILES

11.1. IBM CORPORATION

11.2. GENERAL ELECTRIC (GE) COMPANY

11.3. SIEMENS HEALTHINEERS AG

11.4. AIDOC MEDICAL LTD.

11.5. ZEBRA MEDICAL VISION LTD.

11.6. BUTTERFLY NETWORK, INC.

11.7. VIZ.AI, INC.

11.8. IMAGEN TECHNOLOGIES, INC.

11.9. ALIVECOR, INC.

11.10. PATHAI, INC.  

Ibm Corporation

General Electric (Ge) Company

Siemens Healthineers Ag

Aidoc Medical Ltd.

Zebra Medical Vision Ltd.

Butterfly Network, Inc.

Viz.Ai, Inc.

Imagen Technologies, Inc.

Alivecor, Inc.

Pathai, Inc.