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Artificial Intelligence (AI) in Healthcare Market Size, Share, Production, Consumption and Forecast 2020 to 2027

Press release   •   Mar 05, 2020 10:34 EST

​The global ​artificial intelligence in healthcare market size is anticipated to hit USD 32.8 billion by 2027, growing at a CAGR of 42.9% over a forecast period 2020 to 2027.

The rising demand to reduce healthcare costs, increasing adoption of precision medicine, growing importance of big data in healthcare, and declining hardware costs are some factors propelling adoption of AI technology in healthcare industry. Moreover, rise in potential applications of AI-based tools in medical care and growth in venture capital investments are anticipated to aid growth over the forecast period.

Artificial intelligence (AI) has the potential to revolutionize any piece of work that can be operated via binary commands and has a finite set of possibilities. The AI concept is currently being harnessed furiously, and the forever flourishing field of healthcare is leveraging it to attain greater goods for the humanity. Artificial intelligence is a combination of software programs with algorithms that can replicate human senses in analyzing medical data, which can often be very complex. Going forward, AI is poised to aid not only in diagnosis procedures but also help in drug development, devising personalized medicine, and monitoring of patients in a relentless manner. A vast number of pioneering technology vendors are currently involved in developing AI algorithms of the healthcare sector and the market for the same is prospering.

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According to the findings of this business intelligence study, the demand for artificial intelligence in healthcare sector across the globe will increase at an exuberant CAGR during the forecast period of 2016 to 2027. This report has been developed by healthcare IT professionals and aspires to serve as a credible business tool for targeted audiences such as healthcare software vendors, chipset companies, technology providers, doctors and hospitals, software solution providers, artificial intelligence system providers, and venture capitalist. The report includes comprehensive and figurative assessment of the demand potential of various market segments, analyzes various impacting factors including trends, drivers, and obstructions, and takes stock of the demand that can be expected out of different countries and regions. The report also contains a featured chapter on the competitive landscape.

Rise in the number of cross-industry collaborations is anticipated to fuel growth. For instance, in March 2018, Microsoft announced partnership with Apollo Hospitals, one of the prominent healthcare systems in India. The partnership was focused on developing and deploying new machine learning models for predicting the risk of developing cardiac diseases and aid doctors in treatment planning. Increase in venture capital funding is a key factor propelling growth of AI start-ups, which is further contributing to market growth.

The adoption of AI in healthcare is increasing, as healthcare providers are focused on enhancing patient care further. The adoption of this technology in healthcare has various benefits, both patients and healthcare providers. AI enables personalized care, based on body constitution and past medical history. Moreover, the shortage of physicians in some countries is anticipated to increase demand for AI in healthcare.

Trends and Opportunities

Greater new possibilities with big data, ability of AI to enhance patient care, strong imbalance between the pool of patients and healthcare professionals, and possibilities of reducing medical costs are some of the key factors expected to augment the demand for AI in the healthcare sector. Additionally, growing importance of precision medicine, increasing number of cross-industry collaborations, consistent inflow of venture capital investments, and increasing geriatric population are some of the other factors that are expected to reflect positively over this market. On the other hand, reluctance of medical practitioners in adopting new technologies, strong lack of a preset and universal regulatory guidelines, lack of curated healthcare data, and concerns of data privacy are curtailing the market from attaining higher grounds.

Technology-wise, the artificial intelligence (AI) in healthcare market can be segmented into querying method, deep learning, context aware processing, and natural language processing, whereas application-wise, artificial intelligence (AI) in healthcare marketcan be bifurcated into wearables, virtual assistant, research and drug discovery, in-patient care and hospital management, medical imaging and diagnosis, precision medicine, lifestyle management and monitoring, and patient data and risk analysis.

Rising funding in artificial intelligence in healthcare fuels the market growth

Artificial intelligence (AI) and Machine Learning (ML) are playing a very important role in healthcare industry. AI is predominantly used in clinical research, robotic personal assistants, and big data analytics. Classic venture capitalists and corporate strategic investors are both investing generously in this space. According to Mercom Research Report 2017, Health IT funding set a record in 2017 with AI and predictive analytics as top tech funded, with patient engagement, telehealth and clinical decision support close behind. Total corporate funding for healthcare technology companies climbed to $8.2 billion in 2017 reporting an increase of 47% from the $5.6 billion in 2016. The worldwide venture funding for digital health startups increased from $5.1 billion in 2016 to $7.2 billion in 2017 posing a growth of 42% in one year. According to TM Capital (U.S.), healthcare AI venture capital deal volume and funding was valued at $794 million in investments across 90 deals in the healthcare AI space and it was expected that AI-focused healthcare and wellness startups were to raise over $690 million from venture capital firms in 2017.

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Large pool of healthcare data supports the market growth

In the healthcare industry, big data comprise information generated from clickstream, and web and social media interactions; readings from medical devices such as sensors ECG X-rays and pulse oximeters; healthcare claims and other billing records; and EMRs, prescriptions, and biometric data among other sources. With the increasing digitalization and adoption of information systems in the healthcare industry, a large volume of data is being generated at various stages of the care delivery process. As a result, healthcare is one of the top 5 big data industries especially in the U.S. Moreover, in the coming years, the volume of big data in healthcare is expected to increase as a result of the use of bidirectional patient’s portals that allow patients to upload their own data and images to their EMRs. This will include unstructured data, such as, images, medications compliance, tracking report, and blood pressure & weight logs.

AI to reduce overall healthcare cost

According to OECD estimates, 20% of healthcare spend is wasted globally. The United States Institute of Medicine believes the figure is more like 30%. According to above mentioned data, the top 15 countries by healthcare expenditure waste an average of $1,100 and $1,700 per person annually. The average waste per-person across the top 15 countries is 10-15 times more than the average amount spent by the bottom 50 countries on healthcare, which currently spend an average of around $120 per person. Underlying reasons for this waste include preventable and rectifiable system inefficiencies such as care delivery failures, over-treatment, and improper care delivery. Technologies such as Artificial Intelligence (AI) can help minimize such inefficiencies, ensuring substantially more stream-lined and cost-effective health ecosystems. Accurate and effectively harnessed data enables more efficient decision making across the industries, including healthcare. As healthcare providers begin to move towards a standardized format for recording patient outcomes, large sets of data will become available for analysis by AI-enabled systems which can track outcome patterns following treatment and identify optimal treatments based on patients’ profiles. As a result of this, AI empowers clinical decision-making by ensuring the right interventions and treatments for each patient, creating a personalized approach of care. The immediate consequence of this will be a significant improvement in outcomes, which will eliminate costs associated with post-treatment complications, which is one of the key drivers of cost in most healthcare ecosystems across the world.

Key findings in the global artificial intelligence market in healthcare study:

Artificial intelligence services to post fastest growth

AI is a highly complex technology and requires implementation of sophisticated algorithms for a wide range of applications in the patient data & risk analysis, lifestyle management & monitoring, precision medicine, drug discovery, and medical imaging and diagnostics. In order to achieve the desired results from application of AI in healthcare, a variety of support services are required. These include installation and integration of AI solution in existing workflow environment and support & maintenance. Most companies that manufacture and develop AI systems and software provide online and offline support depending on the application. This segment is expected to grow at a highest CAGR during the forecast period.

Natural Learning Process (NLP) technology to grow at highest CAGR

In 2018, NLP holds the largest share among all the healthcare AI technologies. This segment is also expected to grow at a highest CAGR during the forecast period. The large share of this segment is attributed to the rising adoption of NLP in clinical documentation and automated coding in claims submissions. The demand for AI technologies in the healthcare is on the rise as healthcare companies are increasingly structuring huge volumes of patient data and using it for clinical inferences. Growing focus on personalized medicine is one of the major factors contributing to the growth of the Artificial Intelligence market for clinical applications. On the other hand, the use of AI in drug discovery and development applications is also supporting the growth of the Artificial Intelligence In Healthcare Market among pharma and biotech companies, CROs, and other non-healthcare provider end-user segments.

Hospital and diagnostic centers to witness largest demand through 2027

In 2018, hospitals and diagnostics centers end user segment accounted for the largest share of the global healthcare AI market. Rising adoption of IT in healthcare organizations, increasing focus towards development of precision medicine approaches, and increasing number of collaborations among hospitals and companies for the development and implementation of customized AI solutions are some of the major factors attributed to the large share of this end user segment.

Regional Analysis

The developed country of the U.S., which readily adopts new technology and houses a number of pioneering companies, is expected to maintain North America are the region with maximum demand potential, with little but significant demand added by Canada. While the European region is another key region for the vendors of artificial intelligence (AI) in healthcare market, emerging economies of Japan, South Korea, China, and India are expected to provide for decent demand over the course of the aforementioned forecast period.

Vendor Landscape

IBM Corporation, Welltok, Inc., Intel Corporation, Google, Inc., Next IT Corp., Microsoft Corporation, General Electric Company, Medtronic PLC, and Koninklijke Philips N.V. are some of the notable companies in artificial intelligence (AI) in healthcare market.

The report offers a comprehensive evaluation of the artificial intelligence (AI) in healthcare market. It does so via in-depth qualitative insights, historical data, and verifiable projections about market size. The projections featured in the report have been derived using proven research methodologies and assumptions. By doing so, the research report serves as a repository of analysis and information for every facet of the artificial intelligence (AI) in healthcare market, including but not limited to: Regional markets, technology, types, and applications.

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Scope of the Report:

Market by Product

  • Software
  • Services
    • Installation and Integration
    • Support and Maintenance
  • Hardware

Market by Application

  • Medical Imaging And Diagnosis
  • Patient Data And Risk Analytics
  • Hospital Workflow Management
  • Drug Discovery
  • Patient Management
  • Precision Medicine
  • Other Applications

Market by Technology

  • Natural Language Processing
  • Context Aware Processing
  • Machine Learning
  • Querying Method

Market by End User

  • Hospital & Diagnostic Centers
  • Pharmaceutical And Biotechnology Companies
  • Healthcare Payers
  • Patients
  • Other End Users

Market by Geography

  • North America
    • US
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Spain
    • Rest of Europe (RoE)
  • Asia-Pacific (APAC)
    • China
    • Japan
    • India
    • Rest of APAC (RoAPAC)
  • Latin America
  • Middle East & Africa

Key questions answered in the report:

Rising funding in artificial intelligence in healthcare fuels the market growth

  • How does the adoption of cloud computing in developed regions differ from developing countries like China, India, and Japan?
  • How is the competition between the major global and prominent local players in this market?
  • Which are the high growth market segments in terms of product, technology, application, end users, and geography?

Hospital and Diagnostics centers accounted for the largest share of the Artificial Intelligence in Healthcare Market

  • What factors are contributing to the frequent usage of artificial intelligence in healthcare market in hospital and diagnostic centers?
  • How does the penetration of artificial intelligence in healthcare in hospital and diagnostic centers differ from other end users?

Artificial Intelligence in Healthcare Market favors both global and local manufacturers that compete in multiple segments

  • Who are the top competitors in this market and what strategies do they employ to gain shares?
  • Which market segments have the most potential for revenue expansion over the forecast period?
  • What strategies should new companies look to enter in this market?
  • What are the major drivers, restraints, opportunities, and challenges in the artificial intelligence in healthcare market?
  • How is the value chain analysis of artificial intelligence in healthcare market?
  • What are the geographical trends and high growth regions/countries?

Recent partnerships, acquisitions, and expansions have taken place in the global artificial intelligence in healthcare market

  • Which companies have recently merged/acquired and how will these unions affect the competitive landscape of the artificial intelligence in healthcare market?
  • Which companies have created partnerships and how will these partnerships promote a competitive advantage?
  • Who are the major players in the global artificial intelligence in healthcare market and what share of the market do they hold?
  • What are the local emerging players in the global artificial intelligence in healthcare market and how do they compete with the global players?

The study is a source of reliable data on:

  • Market segments and sub-segments
  • Market trends and dynamics
  • Supply and demand
  • Market size
  • Current trends/opportunities/challenges
  • Competitive landscape
  • Technological breakthroughs
  • Value chain and stakeholder analysis

The regional analysis covers:

  • North America (U.S. and Canada)
  • Latin America (Mexico, Brazil, Peru, Chile, and others)
  • Western Europe (Germany, U.K., France, Spain, Italy, Nordic countries, Belgium, Netherlands, and Luxembourg)
  • Eastern Europe (Poland and Russia)
  • Asia Pacific (China, India, Japan, ASEAN, Australia, and New Zealand)
  • Middle East and Africa (GCC, Southern Africa, and North Africa)

The report has been compiled through extensive primary research (through interviews, surveys, and observations of seasoned analysts) and secondary research (which entails reputable paid sources, trade journals, and industry body databases). The report also features a complete qualitative and quantitative assessment by analyzing data gathered from industry analysts and market participants across key points in the industry’s value chain.

A separate analysis of prevailing trends in the parent market, macro- and micro-economic indicators, and regulations and mandates is included under the purview of the study. By doing so, the report projects the attractiveness of each major segment over the forecast period.

Highlights of the report:

  • A complete backdrop analysis, which includes an assessment of the parent market
  • Important changes in market dynamics
  • Market segmentation up to the second or third level
  • Historical, current, and projected size of the market from the standpoint of both value and volume
  • Reporting and evaluation of recent industry developments
  • Market shares and strategies of key players
  • Emerging niche segments and regional markets
  • An objective assessment of the trajectory of the market
  • Recommendations to companies for strengthening their foothold in the market

Table of Contents

Chapter 1 Research Methodology
1.1 Market Segmentation & Scope
1.2 Abbreviation: Market Related Terminology
1.3 Information Procurement
1.3.1 Purchased database:
1.3.2 Database
1.3.3 Secondary sources & third party perspectives
1.3.4 Primary research
1.4 Information Analysis
1.4.1 Data analysis models
1.5 Market Formulation & Data Visualization
1.6 Data Validation & Publishing
Chapter 2 Executive Summary
2.1 Artificial Intelligence in Healthcare Market Outlook, 2020-2027 (USD Million)
2.2 Artificial Intelligence in Healthcare Market Segment Outlook, 2020-2027 (USD Million)
2.3 Artificial Intelligence in Healthcare Market Competitive Insights Outlook, 2020-2027 (USD Million)
Chapter 3 Artificial Intelligence in Healthcare Market Variables, Trends & Scope
3.1 Artificial Intelligence in Healthcare Market Lineage Outlook
3.1.1 Parent market outlook
3.1.1.1 Healthcare Cognitive Computing Market Analysis
3.1.2 Related/ancillary market outlook
3.1.2.1 Connected Health Market Analysis
3.1.2.2 Augmented and Virtual Reality in Healthcare Market Analysis
3.2 Penetration & Growth Prospect Mapping
3.3 User Perspective Analysis
3.3.1 Consumer behavior analysis
3.3.2 Market influencer analysis
3.4 List of Key End-users
3.5 Technology Overview
3.5.1 Technology timeline
3.6 Regulatory Framework
3.6.1 Reimbursement framework
3.7 Artificial Intelligence in Healthcare Market Dynamics
3.7.1 Market driver analysis
3.7.2 Market restraint analysis
3.7.3 Industry challenges
3.8 Artificial Intelligence in Healthcare Market Analysis Tools
3.8.1 Industry analysis - Porter’s
3.8.1.1 Supplier power
3.8.1.2 Buyer power
3.8.1.3 Substitution threat
3.8.1.4 Threats from new entrant
3.8.1.5 Competitive rivalry
3.8.2 PESTEL analysis
3.8.2.1 Political landscape
3.8.2.2 Environmental landscape
3.8.2.3 Social landscape
3.8.2.4 Technology landscape
3.8.2.5 Economic landscape
3.8.2.6 Legal landscape
3.8.3 Major deals & strategic alliances analysis
3.8.3.1 Joint ventures
3.8.3.2 Mergers & acquisitions
3.8.3.3 Licensing & partnership
3.8.3.4 Market Divestment
3.8.4 Market entry strategies
Chapter 4 Artificial Intelligence in Healthcare Market - Competitive Analysis
4.1 Recent Developments & Impact Analysis, by Key Market Participants
4.2 Company/Competition Categorization
4.3 Vendor Landscape
4.3.1 List of key distributors and channel partners
4.3.2 Key company market share analysis/Company market position analysis, 2018
4.4 Public Companies
4.4.1 Company market position analysis
4.4.2 Company market share by ranking, by region
4.5 Private Companies
4.5.1 List of key emerging companies /technology disruptors/innovators
4.5.2 Regional network map
4.5.3 Company market position analysis
Chapter 5 Artificial Intelligence in Healthcare Market: Technology Qualitative Trend & Dynamic Analysis
5.5 Qualitative Trend & Dynamic Analysis
5.5.1 Machine Learning
5.5.2 Natural Language Processing
5.5.3 Computer Vision
5.5.4 Context Aware Processing
Chapter 6 Artificial Intelligence in Healthcare Market: Component Estimates & Trend Analysis
6.1 Definition & Scope
6.2 Component Market Share Analysis, 2018 & 2025
6.3 Segment Dashboard
6.4 Global Artificial Intelligence in Healthcare Market, By Component, 2020-2027
6.4.1 Software solutions
6.4.1.1 Software solutions market revenue estimates and forecasts, 2020-2027 (USD Million)
6.4.2 Hardware
6.4.2.1 Hardware market revenue estimates and forecasts, 2020-2027 (USD Million)
6.4.3 Services
6.4.3.1 Services market revenue estimates and forecasts, 2020-2027 (USD Million)
Chapter 7 Artificial Intelligence in Healthcare Market: Application Estimates & Trend Analysis
7.1 Definition & Scope
7.2 Application Market Share Analysis, 2018 & 2025
7.3 Segment Dashboard
7.4 Global Artificial Intelligence in Healthcare Market, by Application, 2020-2027
7.4.1 Robot assisted surgery
7.4.1.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.2 Virtual assistants
7.4.2.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.3 Administrative workflow assistants
7.4.3.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.4 Connected machines
7.4.4.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.5 Diagnosis
7.4.5.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.6 Clinical trials
7.4.6.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.7 Fraud detection
7.4.7.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.8 Cybersecurity
7.4.8.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
7.4.9 Dosage error reduction
7.4.9.1 Market revenue estimates and forecasts, 2020-2027 (USD Million)
Chapter 8 Artificial Intelligence in Healthcare Market: Regional Estimates & Trend Analysis, By Component and Application
8.1 Regional Artificial Intelligence in Healthcare Market Snapshot
8.2 List of Key Players, by Region
8.3. SWOT Analysis, by Factor
8.3.1 North America
8.3.2 Europe
8.3.3 Asia Pacific
8.3.4 Latin America
8.3.5 Middle East & Africa
8.4 Regional Artificial Intelligence in Healthcare Market Share Analysis, 2018
8.4.1 North America
8.4.1.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.1.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.1.3 Market share analysis by country (%), 2018
8.4.1.4 U.S.
8.4.1.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.1.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.1.5 Canada
8.4.1.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.1.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2 Europe
8.4.2.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.3 Market share by country (%), 2018
8.4.2.4 U.K.
8.4.2.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.5 Germany
8.4.2.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.6 Spain
8.4.2.6.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.6.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.7 France
8.4.2.7.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.7.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.8 Italy
8.4.2.8.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.8.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.2.9 Russia
8.4.2.9.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.2.9.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3 Asia Pacific
8.4.3.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.3 Market share by country (%), 2018
8.4.3.4 China
8.4.3.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.5 Japan
8.4.3.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.6 India
8.4.3.6.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.6.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.7 South Korea
8.4.3.7.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.7.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.8 Singapore
8.4.3.8.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.8.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.3.9 Australia
8.4.3.9.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.3.9.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.4 Latin America
8.4.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.4.3 Market share by country (%), 2018
8.4.4.4 Brazil
8.4.4.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.4.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.4.5 Mexico
8.4.4.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.4.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.4.6 Argentina
8.4.4.6.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.4.6.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.5 MEA
8.4.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.5.3 MEA market share by country, 2020-2027 (USD Million)
8.4.5.4 South Africa
8.4.5.4.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.5.4.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.5.5 Saudi Arabia
8.4.5.5.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.5.5.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
8.4.5.6 UAE
8.4.5.6.1 Market revenue estimates and forecasts, by component, 2020-2027 (USD Million)
8.4.5.6.2 Market revenue estimates and forecasts, by application, 2020-2027 (USD Million)
Chapter 9 Company Profiles
9.1 Company Profiles
9.1.1 IBM Corporation
9.1.1.1 Company overview
9.1.1.2 Financial performance
9.1.1.3 Product benchmarking
9.1.1.4 Strategic initiatives
9.1.2 Microsoft
9.1.2.1 Company overview
9.1.2.2 Financial performance
9.1.2.3 Product benchmarking
9.1.2.4 Strategic initiatives
9.1.3 Intel Corporation
9.1.3.1 Company overview
9.1.3.2 Financial performance
9.1.3.3 Product benchmarking
9.1.3.4 Strategic initiatives
9.1.4 NVIDIA Corporation
9.1.4.1 Company overview
9.1.4.2 Financial performance
9.1.4.3 Product benchmarking
9.1.4.4 Strategic initiatives
9.1.5 Nuance Communications, Inc.
9.1.5.1 Company overview
9.1.5.2 Financial performance
9.1.5.3 Product benchmarking
9.1.5.4 Strategic initiatives
9.1.6 DeepMind Technologies Limited
9.1.6.1 Company overview
9.1.6.2 Financial performance
9.1.6.3 Product benchmarking
9.1.6.4 Strategic initiatives

9.2 List of Other Players​

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