Report Code: CMI23469

Published Date: May 2023

Pages: 220+

Category: India

Report Snapshot

CAGR: 30%

Source: CMI

Study Period: 2024-2033
Fastest Growing Market: India
Largest Market: India

Major Players

  • Aindra Systems Private Limited
  • Artivatic Data Labs Private Limited
  • Advenio Tecnosys Private Limited
  • Niramai Health Analytix Private Limited
  • Others

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Reports Description

The India AI in Healthcare Market was estimated at USD 10 billion in 2021 and is anticipated to reach around USD 35 billion by 2030, growing at a CAGR of roughly 30% between 2022 and 2030. Our research report offers a 360-degree view of India AI in Healthcare market’s drivers and restraints, coupled with the impact they have on demand during the projection period. Also, the report examines global opportunities and competitive analysis for India AI in Healthcare market.

  • There are just 64 doctors in India for every 100,000 inhabitants, compared to an average of 150 worldwide. Primary health centers and subcenters in rural, outlying areas frequently have appallingly low staffing levels and lack essential facilities. In India, where more than 70% of the population lives in rural areas, this frequently leads to a shortage of high-quality diagnostic services.
  • In constrained healthcare capacity and delayed disease detection skills outside urban centers, leveraging predictive analytics by applying Artificial Intelligence (AI) for early detection can be an important tool for targeted public health interventions. India’s $372 billion healthcare business presents prospects for bridging these disparities and achieving AI maturity through AI-enabled solutions.
  • The Indian government-affiliated think tank NITI Aayog is currently validating the use of AI as a screening tool in eye care by comparing its diagnostic accuracy to that of retina specialists. NITI Aayog has been testing the application of AI in primary care for the early detection of diabetes complications. Expanding the capacity for eye exams and early detection, as well as enabling access in remote locations across the nation, is possible by integrating AI capabilities with portable screening devices like 3Nethra.
  • Oncology might use tools like this as well. The Comprehensive Archive of Imaging, India’s first de-identified cancer picture collection, was introduced by Tata Medical Center and the Indian Institute of Technology. AI-based tools can use high-quality de-identified photos to help machine-learning models find biomarkers and enhance the results of cancer research.

Report Scope

The study’s focus is on India AI in healthcare market analysis on a global scale, and market sizing includes the income generated by these solutions provided by different market players. In order to support the market projections and growth rates over the anticipated period of 2022-2030, the study additionally monitors important market factors, underlying growth influencers, and significant vendors active in the sector.

The study also examines how COVID-19 has affected the ecology generally. The scope of the study includes market sizing and forecast for segmentation by component and application.

Feature of the Report Details
Market Size in 2022 USD 10 Billion
Projected Market Size in 2030 USD 35 Billion
Market Size in 2023 USD 13.12 Billion
CAGR Growth Rate 30% CAGR 2022 and 2030
Base Year 2023
Forecast Period 2024-2033
Key Segment By Component, Application, and Region
Report Coverage Revenue Estimation and Forecast, Company Profile, Competitive Landscape, Growth Factors and Recent Trends
Regional Scope North America, Europe, Asia Pacific, Middle East & Africa, and South & Central America
Buying Options Request tailored purchasing options to fulfil your requirements for research.

Key Market Dynamics

  • India is one of the nations in the world with the most potential for innovative, sustainable, and scalable healthcare technology to improve lives because of its significant healthcare distribution inequalities, glaring lack of infrastructure & trained healthcare clinicians, and low government spending on healthcare. Although there are 1 billion people in the country, many of whom have smartphones and internet access, it is still challenging to think of more than a few instances of digital technologies that have had a big influence on healthcare outcomes or have been broadly adopted.
  • Designing and creating technology for India must consider regional limitations, including price. The Indian healthcare industry faces numerous regional and behavioural issues, but the cost is still a significant factor. New technology needs to be created to address its limitations and price for the nation to flourish and make an impact at scale.
  • There is always a continuous gap to fill, whether it be a spending gap, a geographic gap, an infrastructure gap, an urban-rural divide, or a difference in skills. The Indian healthcare system offers opportunities and incentives unmatched for piloting and operationalizing innovations because of its diversity and potential scale. Each area that the Indian healthcare system fails in offers a special opportunity for artificial intelligence or even just basic digital technology.
  • Over the past ten years, the country has seen the fast adoption of the internet and smartphones. As a result, it currently satisfies the requirements for the effective delivery of digital solutions. Both at the national policy level and locally, where individual states compete to adopt new technology that can help solve long-standing problems, government excitement for innovation and locally manufactured technology is at an all-time high. Public-private collaborations are often favored. This is a positive development for innovators, even though a good quantity of doubt about the actual ground circumstances should temper it.
  • Millions of people in India could benefit from a variety of healthcare challenges that are yet “virgin ground” for technology. A few of the numerous topics worth considering through the perspective of the technology, connection, and artificial intelligence available today include antibiotic resistance, health insurance, infectious diseases like malaria and tuberculosis, and new ones like diabetes.
  • In India, consumer-facing “health tech” has been discussed and accepted during the past five years by investors, the government, and progressively by the general people. Urban, educated consumers are increasingly turning to technology, mostly in the form of fitness applications, telemedicine, online health service aggregators, and home delivery of prescription medications. Online consultations or apps with chat-based basic healthcare services are two examples of how existing techniques are being used to reinvent the delivery of healthcare.
  • Recently, technology that performs or assists with fundamental healthcare or medical duties like analyzing radiology, pathology, or ophthalmology pictures has started to emerge for physicians. India has a critical need for technology to close resource gaps, and AI has the ability to provide cost-effective solutions on a large scale. Thus, India may soon be in a position to reap the rewards of these technologies on health outcomes.

India AI in Healthcare Market 2023–2032 (Billion)

The Clinical Trials Segment to Dominate India AI in Healthcare Market

  • Because of the increasing number of patent expirations and the increasing demand for quicker and more accurate clinical trials to meet the needs of new drug discoveries and drug development, the clinical trials application segment dominated the AI in healthcare market in 2021.
  • Although AI-based technologies in clinical trials were still in their infancy before the pandemic, there has been an explosion in their use due to the desire for speedier clinical trials that help trial design, study adherence, lowering dropout rates, and patient recruiting.
  • The India AI in healthcare market expansion is anticipated to be boosted by reducing the time needed to conduct clinical trials and improving their accuracy and dependability. Healthcare start-ups, government regulatory agencies, and companies in the life sciences are starting to support and implement AI-powered processes.
  • The virtual assistant market, on the other hand, is predicted to grow at the fastest rate over the forecast period.
  • The lack of qualified workers, the rising use of smartphones, and increased internet access contribute to the rapid expansion and penetration of AI-based technologies in the virtual assistant market.
  • In addition to the virtual assistant market, the robot-assisted surgery market is anticipated to experience profitable growth and hold significant promise in the years to come. This notable growth rate is due to the rise in collaborations between suppliers of AI technology and companies that make surgical robots.

Competitive Landscape

The main strategies players are concentrating on to get a competitive edge in the market include increasing investments in R&D, innovative product developments and launches, expanding technical collaborations, and service differentiation.

Our market analysis includes a section specifically devoted to key players operating in AI in healthcare market in India. Our analysts give an overview of each player’s financial statements, along with product benchmarking and SWOT analysis. The competitive landscape section includes key development strategies, market share analysis, and market positioning analysis of the mentioned competitors globally.

  • 2022: To advance India’s digital economy, Google revealed several cutting-edge AI-based technologies and partnerships with local firms. Healthcare, language, and agriculture were the focus areas.
  • 2022: Google announced to collaborate with Apollo Hospitals to establish a clinical intelligence platform.

India AI in Healthcare Market 2023–2032 (By Component)

List of the prominent players in the India AI in healthcare market:

  • Aindra Systems Private Limited
  • Artivatic Data Labs Private Limited
  • Advenio Tecnosys Private Limited
  • Niramai Health Analytix Private Limited
  • Predible Health Private Limited
  • Sigtuple Technologies Private Limited
  • Ai Technologies Private Limited
  • Tricog Health Services Private Limited
  • Microsoft Corporation (India) Private Limited
  • IBM India Private Limited
  • Others

The India AI in healthcare market is segmented as follows:

By Component

  • Hardware
  • Software Solutions
  • Services

By Application

  • Robot-Assisted Surgery
  • Administrative Workflow Assistants
  • Virtual Assistants
  • Connected Machines
  • Clinical Trials
  • Diagnosis
  • Fraud Detection
  • Dosage Error Reduction
  • Cybersecurity

On the basis of Geography

  • India

Table of Contents

  • Chapter 1. Preface
    • 1.1 Report Description and Scope
    • 1.2 Research scope
    • 1.3 Research methodology
      • 1.3.1 Market Research Type
      • 1.3.2 Market research methodology
  • Chapter 2. Executive Summary
    • 2.1 India AI in Healthcare Market, (2024 – 2033) (USD Billion)
    • 2.2 India AI in Healthcare Market : snapshot
  • Chapter 3. India AI in Healthcare Market – Industry Analysis
    • 3.1 India AI in Healthcare Market: Market Dynamics
    • 3.2 Market Drivers
      • 3.2.1 Expanding datasets of digital patient health information
      • 3.2.2 The rising desire for individualized treatment
      • 3.2.3 The rising demand for lowering healthcare costs.
    • 3.3 Market Restraints
    • 3.4 Market Opportunities
    • 3.5 Market Challenges
    • 3.6 Porter’s Five Forces Analysis
    • 3.7 Market Attractiveness Analysis
      • 3.7.1 Market attractiveness analysis By Component
      • 3.7.2 Market attractiveness analysis By Application
  • Chapter 4. India AI in Healthcare Market- Competitive Landscape
    • 4.1 Company market share analysis
      • 4.1.1 India AI in Healthcare Market: company market share, 2022
    • 4.2 Strategic development
      • 4.2.1 Acquisitions & mergers
      • 4.2.2 New Product launches
      • 4.2.3 Agreements, partnerships, cullaborations, and joint ventures
      • 4.2.4 Research and development and Regional expansion
    • 4.3 Price trend analysis
  • Chapter 5. India AI in Healthcare Market – Component Analysis
    • 5.1 India AI in Healthcare Market overview: By Component
      • 5.1.1 India AI in Healthcare Market share, By Component, 2022 and – 2033
    • 5.2 Hardware
      • 5.2.1 India AI in Healthcare Market by Hardware, 2024 – 2033 (USD Billion)
    • 5.3 Software Solutions
      • 5.3.1 India AI in Healthcare Market by Software Solutions, 2024 – 2033 (USD Billion)
    • 5.4 Services
      • 5.4.1 India AI in Healthcare Market by Services, 2024 – 2033 (USD Billion)
  • Chapter 6. India AI in Healthcare Market – Application Analysis
    • 6.1 India AI in Healthcare Market overview: By Application
      • 6.1.1 India AI in Healthcare Market share, By Application, 2022 and – 2033
    • 6.2 Robot-Assisted Surgery
      • 6.2.1 India AI in Healthcare Market by Robot-Assisted Surgery, 2024 – 2033 (USD Billion)
    • 6.3 Administrative Workflow Assistants
      • 6.3.1 India AI in Healthcare Market by Administrative Workflow Assistants, 2024 – 2033 (USD Billion)
    • 6.4 Virtual Assistants
      • 6.4.1 India AI in Healthcare Market by Virtual Assistants, 2024 – 2033 (USD Billion)
    • 6.5 Connected Machines
      • 6.5.1 India AI in Healthcare Market by Connected Machines, 2024 – 2033 (USD Billion)
    • 6.6 Clinical Trials
      • 6.6.1 India AI in Healthcare Market by Clinical Trials, 2024 – 2033 (USD Billion)
    • 6.7 Diagnosis
      • 6.7.1 India AI in Healthcare Market by Diagnosis, 2024 – 2033 (USD Billion)
    • 6.8 Fraud Detection
      • 6.8.1 India AI in Healthcare Market by Fraud Detection, 2024 – 2033 (USD Billion)
    • 6.9 Dosage Error Reduction
      • 6.9.1 India AI in Healthcare Market by Dosage Error Reduction, 2024 – 2033 (USD Billion)
    • 6.10 Cybersecurity
      • 6.10.1 India AI in Healthcare Market by Cybersecurity, 2024 – 2033 (USD Billion)
  • Chapter 7. India AI in Healthcare Market – Regional Analysis
    • 7.1 India AI in Healthcare Market Regional Overview
    • 7.2 India AI in Healthcare Market Share, by Region, 2022 & – 2033 (USD Billion)
  • Chapter 8. Company Profiles
    • 8.1 Aindra Systems Private Limited
      • 8.1.1 Overview
      • 8.1.2 Financials
      • 8.1.3 Product Portfolio
      • 8.1.4 Business Strategy
      • 8.1.5 Recent Developments
    • 8.2 Artivatic Data Labs Private Limited
      • 8.2.1 Overview
      • 8.2.2 Financials
      • 8.2.3 Product Portfolio
      • 8.2.4 Business Strategy
      • 8.2.5 Recent Developments
    • 8.3 Advenio Tecnosys Private Limited
      • 8.3.1 Overview
      • 8.3.2 Financials
      • 8.3.3 Product Portfolio
      • 8.3.4 Business Strategy
      • 8.3.5 Recent Developments
    • 8.4 Niramai Health Analytix Private Limited
      • 8.4.1 Overview
      • 8.4.2 Financials
      • 8.4.3 Product Portfolio
      • 8.4.4 Business Strategy
      • 8.4.5 Recent Developments
    • 8.5 Predible Health Private Limited
      • 8.5.1 Overview
      • 8.5.2 Financials
      • 8.5.3 Product Portfolio
      • 8.5.4 Business Strategy
      • 8.5.5 Recent Developments
    • 8.6 Sigtuple Technologies Private Limited
      • 8.6.1 Overview
      • 8.6.2 Financials
      • 8.6.3 Product Portfolio
      • 8.6.4 Business Strategy
      • 8.6.5 Recent Developments
    • 8.7 Qure.Ai Technologies Private Limited
      • 8.7.1 Overview
      • 8.7.2 Financials
      • 8.7.3 Product Portfolio
      • 8.7.4 Business Strategy
      • 8.7.5 Recent Developments
    • 8.8 Tricog Health Services Private Limited
      • 8.8.1 Overview
      • 8.8.2 Financials
      • 8.8.3 Product Portfolio
      • 8.8.4 Business Strategy
      • 8.8.5 Recent Developments
    • 8.9 Microsoft Corporation (India) Private Limited
      • 8.9.1 Overview
      • 8.9.2 Financials
      • 8.9.3 Product Portfolio
      • 8.9.4 Business Strategy
      • 8.9.5 Recent Developments
    • 8.10 IBM India Private Limited
      • 8.10.1 Overview
      • 8.10.2 Financials
      • 8.10.3 Product Portfolio
      • 8.10.4 Business Strategy
      • 8.10.5 Recent Developments
    • 8.11 Others
      • 8.11.1 Overview
      • 8.11.2 Financials
      • 8.11.3 Product Portfolio
      • 8.11.4 Business Strategy
      • 8.11.5 Recent Developments
List Of Figures

Figures No 1 to 21

List Of Tables

Tables No 1 to 2

Report Methodology

In order to get the most precise estimates and forecasts possible, Custom Market Insights applies a detailed and adaptive research methodology centered on reducing deviations. For segregating and assessing quantitative aspects of the market, the company uses a combination of top-down and bottom-up approaches. Furthermore, data triangulation, which examines the market from three different aspects, is a recurring theme in all of our research reports. The following are critical components of the methodology used in all of our studies:

Preliminary Data Mining

On a broad scale, raw market information is retrieved and compiled. Data is constantly screened to make sure that only substantiated and verified sources are taken into account. Furthermore, data is mined from a plethora of reports in our archive and also a number of reputed & reliable paid databases. To gain a detailed understanding of the business, it is necessary to know the entire product life cycle and to facilitate this, we gather data from different suppliers, distributors, and buyers.

Surveys, technological conferences, and trade magazines are used to identify technical issues and trends. Technical data is also gathered from the standpoint of intellectual property, with a focus on freedom of movement and white space. The dynamics of the industry in terms of drivers, restraints, and valuation trends are also gathered. As a result, the content created contains a diverse range of original data, which is then cross-validated and verified with published sources.

Statistical Model

Simulation models are used to generate our business estimates and forecasts. For each study, a one-of-a-kind model is created. Data gathered for market dynamics, the digital landscape, development services, and valuation patterns are fed into the prototype and analyzed concurrently. These factors are compared, and their effect over the projected timeline is quantified using correlation, regression, and statistical modeling. Market forecasting is accomplished through the use of a combination of economic techniques, technical analysis, industry experience, and domain knowledge.

Short-term forecasting is typically done with econometric models, while long-term forecasting is done with technological market models. These are based on a synthesis of the technological environment, legal frameworks, economic outlook, and business regulations. Bottom-up market evaluation is favored, with crucial regional markets reviewed as distinct entities and data integration to acquire worldwide estimates. This is essential for gaining a thorough knowledge of the industry and ensuring that errors are kept to a minimum.

Some of the variables taken into account for forecasting are as follows:

• Industry drivers and constraints, as well as their current and projected impact

• The raw material case, as well as supply-versus-price trends

• Current volume and projected volume growth through 2030

We allocate weights to these variables and use weighted average analysis to determine the estimated market growth rate.

Primary Validation

This is the final step in our report’s estimating and forecasting process. Extensive primary interviews are carried out, both in-person and over the phone, to validate our findings and the assumptions that led to them.
Leading companies from across the supply chain, including suppliers, technology companies, subject matter experts, and buyers, use techniques like interviewing to ensure a comprehensive and non-biased overview of the business. These interviews are conducted all over the world, with the help of local staff and translators, to overcome language barriers.

Primary interviews not only aid with data validation, but also offer additional important insight into the industry, existing business scenario, and future projections, thereby improving the quality of our reports.

All of our estimates and forecasts are validated through extensive research work with key industry participants (KIPs), which typically include:

• Market leaders

• Suppliers of raw materials

• Suppliers of raw materials

• Buyers.

The following are the primary research objectives:

• To ensure the accuracy and acceptability of our data.

• Gaining an understanding of the current market and future projections.

Data Collection Matrix

Perspective Primary research Secondary research
  • Manufacturers
  • Technology distributors and wholesalers
  • Company reports and publications
  • Government publications
  • Independent investigations
  • Economic and demographic data
  • End-user surveys
  • Consumer surveys
  • Mystery shopping
  • Case studies
  • Reference customers

Market Analysis Matrix

Qualitative analysis Quantitative analysis
  • Industry landscape and trends
  • Market dynamics and key issues
  • Technology landscape
  • Market opportunities
  • Porter’s analysis and PESTEL analysis
  • Competitive landscape and component benchmarking
  • Policy and regulatory scenario
  • Market revenue estimates and forecast up to 2030
  • Market revenue estimates and forecasts up to 2030, by technology
  • Market revenue estimates and forecasts up to 2030, by application
  • Market revenue estimates and forecasts up to 2030, by type
  • Market revenue estimates and forecasts up to 2030, by component
  • Regional market revenue forecasts, by technology
  • Regional market revenue forecasts, by application
  • Regional market revenue forecasts, by type
  • Regional market revenue forecasts, by component

Prominent Players

  • Aindra Systems Private Limited
  • Artivatic Data Labs Private Limited
  • Advenio Tecnosys Private Limited
  • Niramai Health Analytix Private Limited
  • Predible Health Private Limited
  • Sigtuple Technologies Private Limited
  • Ai Technologies Private Limited
  • Tricog Health Services Private Limited
  • Microsoft Corporation (India) Private Limited
  • IBM India Private Limited
  • Others


The key factors driving the market are expanding datasets of digital patient health information, the rising desire for individualized treatment and the rising demand for lowering healthcare costs.

The key players operating in the India AI in Healthcare market are Aindra Systems Private Limited, Artivatic Data Labs Private Limited, Advenio Tecnosys Private Limited, Niramai Health Analytix Private Limited, Predible Health Private Limited, Sigtuple Technologies Private Limited, Qure.Ai Technologies Private Limited, Tricog Health Services Private Limited, Microsoft Corporation (India) Private Limited, IBM India Private Limited, Others.

The India AI in Healthcare market is expanding growth with a CAGR of approximately 30% during the forecast period (2023 to 2032).

The India AI in Healthcare market size was valued at USD 10 Billion in 2023 and it is projected to reach around USD 35 Billion by 2032.












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