Overview


According to FutureWise analysis the market for artificial intelligence in healthcare in 2023 is US$ 14.6 billion, and is expected to reach US$ 332.83 billion by 2031 at a CAGR of 47.80%.

Artificial intelligence (AI) refers to the application of machine learning (ML) algorithms and other cognizable technologies in healthcare. The ability of computing device and other devices to mimic human cognition, learn, think, and make decisions or perform actions is the most basic definition of artificial intelligence (AI). As a result, artificial intelligence (AI) in healthcare refers to the use of machines to analyse and take action on medical data, typically with the intention of forecasting a particular outcome. Applying AI to healthcare data can mean the difference between life and death. Doctors, nurses, and other healthcare professionals use AI to help them with regular tasks. AI in healthcare improves patient outcomes by improving preventative care and quality of life, generating more precise diagnoses and treatment plans, and improving overall patient care. By examining data from the public and private sector, the medical industry, and other sources, AI also anticipates and monitors the development of dangerous diseases. As a tool for battling pandemics and epidemics, AI thus plays a significant role in improving global public health.

Artificial intelligence (AI) has significantly impacted the healthcare industry, changing how personnel identify, treat, and monitor patients. This technology significantly enhances healthcare research and outcomes by enabling more individualized therapies and delivering more precise diagnoses. AI in healthcare's capability to quickly analyse vast amounts of clinical documentation helps uncover disease signs and trends that medical experts would otherwise miss. Various applications of artificial intelligence (AI) in healthcare are possible, ranging from forecasting outcomes using electronic health records to radiological image analysis for early detection. Healthcare systems are becoming smarter, quicker, and more effective in providing treatment to millions of people worldwide by utilizing artificial intelligence in hospital and clinic settings. In fact, artificial intelligence in healthcare is the wave of the future, revolutionizing how patients receive high-quality treatment while lowering costs for providers and enhancing patient outcomes.

FutureWise Market Research has published a report that provides an insightful analysis of AI In Healthcare Market trends that are affecting the overall market growth. This report will provide a detailed analysis of market share, regional insights, and competitor analysis that includes stature of key manufacturers operational in this industry.

According to the analysis conducted by FutureWise research analysts, the AI In Healthcare Market is estimated to register a considerable growth rate over the forecast period. This report lists the market segments and potential prospects available across this industry, in addition providing crucial information on the total valuation currently held by the industry. Moreover, this report will assist key management individuals in an organisation to enhance their decisions pertaining to business expansion as well as strategic changes for increasing customer base.
  • IBM (Watson Health)
  • AiCure
  • APIXIO Inc.
  • iCarbonX
  • Insilico Medicine Inc.
  • Sophia Genetics
  • Welltok
  • Zebra Medical Vision Ltd.
  • Micron Technology
  • Amazon Web Services
  • Intel
  • Nvidia
  • Google
  • Microsoft
  • NVIDIA Corporation
  • General Vision, Inc.
  • General Electric (GE) Healthcare
  • Siemens Healthineers
  • Medtronic plc

Key factors propelling the market's expansion are the expanding datasets of digital patient health information, the rising desire for personalized treatment, and the rising demand for lowering healthcare costs. The increase in demand for early disease diagnosis and better understanding has been attributed to the growing global geriatric population, changing lifestyles, and rising prevalence of chronic diseases. Healthcare systems are increasingly adopting and integrating artificial intelligence (AI) and machine learning (ML) algorithms to precisely forecast diseases in their early stages based on past health records. There have been notable examples of how Deep Learning-based Artificial Intelligence techniques can be utilized for medical diagnostics to strengthen the medical community's trust and give input to the major research society on the areas where further advancement is most required. The growing need for customized pharmaceuticals and the need to protect digital health data significantly impact the market for artificial intelligence in healthcare. Additionally, the market has witnessed the utilisation of smart pills. Small electrical gadgets called Smart Pills are made to seem like typical medicine capsules. They carry out numerous extremely complex therapeutic activities, such as drug delivery utilizing pH or chemical sensors, biosensors, and sensing for imaging. They also incorporate cloud computing and wireless communication systems. The term "ingestible sensors," frequently used by specialists, is used to describe them in contrast to wearable and embedded sensors. Growing numbers of mergers and acquisitions, technology collaborations, and supportive government initiatives all played a vital part in advancing the application of AI in healthcare. This presents opportunities for new market entrants and established key players to expand their product portfolios for this target market. However, one of the challenges with using AI in healthcare is that it requires access to a lot of data to be useful. Additionally, different AI systems need to be more standardized, which could make it difficult to compare outcomes or combine data from different sources. One of the obstacles that can hinder the market for AI in healthcare is errors caused by big data analysis and errors that result in faults in patient monitoring.

By Technology

  • Natural Language Processing (NLP)
  • Machine Learning
    • Deep Learning
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
    • Others
  • Context-Aware Computing
  • Computer Vision

By Offering

  • Software
    • AI Solutions
      • On-Premises
      • Cloud
    • AI Platform
      • Machine Learning Framework
      • Application Program Interface
  • Hardware
    • Processor
      • MPU
      • GPU
      • FPGA
      • ASIC
    • Memory
    • Network
  • Services
    • Deployment and Integration
    • Support and Maintenance

By Application

  • In-Patient Care and Hospital
  • Patient Data and Risk Analysis
  • Medical Imaging and Diagnostics
  • Lifestyle Management and Monitoring
  • Virtual Assistant
  • Healthcare Assistant Robots
  • Wearable
  • Drug Discovery
  • Research
  • Precision Medicine
  • Emergency Room andSurgery
  • Mental Health
  • Cybersecurity

By End User

  • Hospitals andHealthcare Providers
  • Patients
  • Pharmaceuticals andBiotechnology Companies
  • Healthcare Payers
  • Others (ACOS and MCOS)

By Region

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East and Africa

This market research report also emphasis on factors affecting the growth rate in various regions listed above. A deep-down analysis of region will also be provided in the final version of this market which is based on conclusion of primary interviews and secondary data point gathered during the process.

By region, the market is segmented into North America, Latin America, Europe, Asia-Pacific, and Middle East & Africa. North America registered the highest share in the market in 2022 due to improvements in healthcare IT infrastructure, rising healthcare costs, increasing use of AI and ML technologies, supportive government efforts, lucrative funding opportunities, and the presence of multiple significant industry participants in the region. Additionally, the market in North America is developing due to factors such as an geriatric population, changing lifestyles, an increase in the prevalence of chronic diseases, a rise in the need for value-based care, and increased awareness of the use of AI-based technologies.

Moreover, based on application, medical imaging & Diagnostics are expected to grow at a higher rate during the forecast period. Artificial intelligence is increasingly used in medical imaging for analysis and early cancer diagnosis. The capability of real-time monitoring increases the patient's life expectancy. Artificial intelligence enables superhuman pattern recognition capabilities in medical imaging and diagnostics with the latest deep learning algorithms. Deep learning is also used in the development and identification of tumors, the measurement of blood flow, and the interpretation of medical data.
  • Tier 1 players- established companies in the market with a major market share
  • Tier 2 players
  • Emerging players which are growing rapidly
  • New Entrants
  • With an ever-increasing patient population, the healthcare database volume shall be consistently increasing thus making the AI technology more crucial for database management
  • Deep learning technology is currently at its nascent stage and further advancements in this technology shall expand the market significantly
  • To provide with an exhaustive analysis on the market By Technology, By Offering, By Application, By End User and By Region
  • To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
  • To evaluate and forecast micro-markets and the overall market
  • To predict the market size, in key regions (along with countries)— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
  • To record evaluate and competitive landscape mapping- product launches, technological advancements, mergers and expansions
  • Profiling of companies to evaluate their market shares, strategies, financials and core competencies
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Table of Contents


  • 1.   Market Introduction
    •   1. Objectives of the Study
        2. Market Definition
        3. Market Scope
         3.1. Years Considered for the Study
         3.2. Market Covered
        4. Currency
        5. Limitations
        6. Stakeholders
  • 2.   Research Methodology
    •   1. Research Data
         1.1. Secondary Data
          1.1.1. Key Data from Secondary Sources
         1.2. Primary Data
          1.2.1. Key Data from Primary Sources
        2. Market Size Estimation
        3. Market Breakdown and Data Triangulation
        4. Assumptions for the Study
  • 3.   Executive Summary
    •   1. Market Outlook
        2. Segment Outlook
        3. Competitive Insights
  • 4.   Artificial Intelligence in Healthcare Market Variables, Trends and Scope

    •   1. Market Lineage Outlook
        2. Penetration and Growth Prospect Mapping
        3. Industry Value Chain Analysis
        4. Cost Analysis Breakdown
        5. Technology Overview
        6. Regulatory Framework
         6.1. Reimbursement Framework
         6.2. Standards and Compliances

  • 5.   Market Overview
    •   1. Market Dynamics
         1.1. Market Driver Analysis
          1.1.1. Increasing focus of Artificial Intelligence in Healthcare Market Companies on Brand Protection
          1.1.2. Untapped Opportunities in Emerging Regions
         1.2. Market Restraint Analysis
          1.2.1. High Cost Associated with Implementation of Predictive Analysis
         1.3. Industry Challenges
          1.3.1. Presence of Ambiguous Regulatory Framework
  • 6.   Artificial Intelligence in Healthcare Market Analysis Tools
    •   1. Industry Analysis - Porter’s
         1.1. Supplier Power
         1.2. Buyer Power
         1.3. Substitution Threat
         1.4. Threat from New Entrants
         1.5. Competitive Rivalry
        2. Pestel Analysis
         2.1. Political Landscape
         2.2. Environmental Landscape
         2.3. Social Landscape
         2.4. Technology Landscape
         2.5. Legal Landscape
        3. Major Deals And Strategic Alliances Analysis
         3.1. Joint Ventures
         3.2. Mergers and Acquisitions
         3.3. Licensing and Partnership
         3.4. Technology Collaborations
         3.5. Strategic Divestments
        4. Market Entry Strategies
        5. Case Studies
  • 7.   Artificial Intelligence in Healthcare Market, By Technology Historical Analysis and Forecast 2023-2031 (USD Million)

    •   1. Natural Language Processing(NLP)
        2. Machine Learning
         2.1. Deep Learning
         2.2. Supervised Learning
         2.3. Unsupervised Learning
         2.4. Reinforcement Learning
         2.5. Others
        3. Context-Aware Computing
        4. Computer Vision

  • 8.   Artificial Intelligence in Healthcare Market, By Offering Historical Analysis and Forecast 2023-2031 (USD Million)

    •   1. Software
         1.1. AI Solutions
          1.1.1. On-Premises
          1.1.2. Cloud
         1.2. AI Platform
          1.2.1. Machine Learning Framework
          1.2.2. Application Program Interface
        2. Hardware
         2.1. Processor
          2.1.1. MPU
          2.1.2. GPU
          2.1.3. FPGA
          2.1.4. ASIC
         2.2. Memory
         2.3. Network
        3.Services
         3.1. Deployment and Integration
         3.2. Support and Maintenance

  • 9.   Artificial Intelligence in Healthcare Market, By Application Historical Analysis and Forecast 2023-2031 (USD Million)

    •   1. In-Patient Care And Hospital
        2. Patient Data And Risk Analysis
        3. Medical Imaging And Diagnostics
        4. Lifestyle Management And Monitoring
        5.Virtual Assistant
        6. Healthcare Assistant Robots
        7. Wearable
        8. Mental Health
        9. Drug Discovery
        10. Research
        11. Precision Medicine
        12. Emergency Room And Surgery
        13. Cybersecurity

  • 10.   Artificial Intelligence in Healthcare Market, By End User Historical Analysis and Forecast 2023-2031 (USD Million)

    •   1. Hospitals and Healthcare Providers
        2. Patients
        3. Pharmaceuticals and Biotechnology Companies
        4. Healthcare Payers
        5. Others (ACOS and MCOS)

  • 11.   North America Artificial Intelligence in Healthcare Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)

    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
         2.1. U.S.A
         2.2. Canada
         2.3. Mexico
        3. Market Size (USD Million) Forecast for North America 2023-2031

  • 12.   Latin America Artificial Intelligence in Healthcare Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)

    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
         2.1. Brazil
         2.2. Venezuela
         2.3. Argentina
         2.4. Rest of Latin America
        3. Market Size (USD Million) Forecast for Latin America 2023-2031

  • 13.   Europe Artificial Intelligence in Healthcare Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)

    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
         2.1. Germany
         2.2. U.K
         2.3. France
         2.4. Italy
         2.5. Spain
         2.6. Russia
         2.7. Poland
         2.8. Rest of Europe
        3. Market Size (USD Million) Forecast for Europe 2023-2031

  • 14.   Asia Pacific Artificial Intelligence in Healthcare Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)

    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
         2.1. Japan
         2.2. China
         2.3. India
         2.4. Australia and New Zealand
         2.5. ASEAN
         2.6. Rest of Asia Pacific
        3. Market Size (USD Million) Forecast for Asia Pacific 2023-2031

  • 15.   Middle East and Africa Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)

    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
         2.1. GCC
         2.2. Israel
         2.3. South Africa
         2.4. Rest of MEA
        3. Market Size (USD Million) Forecast for MEA 2023-2031

  • 16.   Market Share Analysis and Competitive Landscape
    •   1. Global Landscape - Key Players, Revenue and Presence
        2. Global Share Analysis - Key Players (Tier 1, Tier 2, Tier 3)
        3. Global Emerging Companies
        4. North America - Market Share Analysis and Key Regional Players
        5. Europe - Market Share Analysis and Key Regional Players
        6. Asia Pacific - Market Share Analysis and Key Regional Players
        7. Global Key Player - Growth Matrix
  • 17.   Company Profiles (Competition Dashboard, Competitors Deep Dive, Products Offered and Financial Layouts)

    •   1. IBM
         1.1. Company Overview
         1.2. Product Portfolio
         1.3. SWOT Analysis
         1.4. Financial Overview
         1.5. Strategic Overview
        2. AiCure
         2.1. Company Overview
         2.2. Product Portfolio
         2.3. SWOT Analysis
         2.4. Financial Overview
         2.5. Strategic Overview
        3. APIXIO Inc.
         3.1. Company Overview
         3.2. Product Portfolio
         3.3. SWOT Analysis
         3.4. Financial Overview
         3.5. Strategic Overview
        4. ICaronX
         4.1. Company Overview
         4.2. Product Portfolio
         4.3. SWOT Analysis
         4.4. Financial Overview
         4.5. Strategic Overview
        5. Insilico Medicien Inc.
         5.1. Company Overview
         5.2. Product Portfolio
         5.3. SWOT Analysis
         5.4. Financial Overview
         5.5. Strategic Overview
        6. Sophia Genetics
         6.1. Company Overview
         6.2. Product Portfolio
         6.3. SWOT Analysis
         6.4. Financial Overview
         6.5. Strategic Overview
        7. Welltok
         7.1. Company Overview
         7.2. Product Portfolio
         7.3. SWOT Analysis
         7.4. Financial Overview
         7.5. Strategic Overview
        8. Zebra Medical Vision Ltd.
         8.1. Company Overview
         8.2. Product Portfolio
         8.3. SWOT Analysis
         8.4. Financial Overview
         8.5. Strategic Overview
        9. Micron Technology
         9.1. Company Overview
         9.2. Product Portfolio
         9.3. SWOT Analysis
         9.4. Financial Overview
         9.5. Strategic Overview
        10. Amazon Web Services
         10.1. Company Overview
         10.2. Product Portfolio
         10.3. SWOT Analysis
         10.4. Financial Overview
         10.5. Strategic Overview
        11. Intel
         11.1. Company Overview
         11.2. Product Portfolio
         11.3. SWOT Analysis
         11.4. Financial Overview
         11.5. Strategic Overview
        12. Nvidia
         12.1. Company Overview
         12.2. Product Portfolio
         12.3. SWOT Analysis
         12.4. Financial Overview
         12.5. Strategic Overview
        13. Google
         13.1. Company Overview
         13.2. Product Portfolio
         13.3. SWOT Analysis
         13.4. Financial Overview
         13.5. Strategic Overview
        14. Microsoft
         14.1. Company Overview
         14.2. Product Portfolio
         14.3. SWOT Analysis
         14.4. Financial Overview
         14.5. Strategic Overview
        15. NVIDIA Corporation
         15.1. Company Overview
         15.2. Product Portfolio
         15.3. SWOT Analysis
         15.4. Financial Overview
         15.5. Strategic Overview
        16. General Vision, Inc.
         16.1. Company Overview
         16.2. Product Portfolio
         16.3. SWOT Analysis
         16.4. Financial Overview
         16.5. Strategic Overview
        17. General Electric (GE) Healthcare
         17.1. Company Overview
         17.2. Product Portfolio
         17.3. SWOT Analysis
         17.4. Financial Overview
         17.5. Strategic Overview
        18. Siemens Healthineers
         18.1. Company Overview
         18.2. Product Portfolio
         18.3. SWOT Analysis
         18.4. Financial Overview
         18.5. Strategic Overview
        19. Medtronic plc
         19.1. Company Overview
         19.2. Product Portfolio
         19.3. SWOT Analysis
         19.4. Financial Overview
         19.5. Strategic Overview

  • 18.   Pre and Post COVID-19 Impact
    •   1. Positive influence on the healthcare industry
        2. The financial disruption of the manufacturing sector
        3. Impact of COVID-19 on emerging companies
        4. Significant mandates in the healthcare regulations initiated by administrations
        5. The overall economic slowdown of the developing and developed nations
  • 19.   FutureWise SME Key Takeaway Points for Client

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