The India AI in Precision Medicine Market was valued at $1.54 Million in 2024 and projected to reach to $5.49 Million by 2029, representing a compound annual growth rate of 18.5%. India's AI in Precision Medicine market is poised for substantial growth as healthcare providers increasingly adopt AI technologies to address the nation's disease burden and improve diagnostic accuracy.
| Market Size in | USD 26.32 MN |
| Market Forecast in | |
| CAGR | |
| Forecast Period | |
| Units Considered | Value (USD MN) |
India's AI in Precision Medicine market is projected to grow from USD 1.54 billion in 2024 to USD 5.49 billion by 2029, with a CAGR of 18.5%, significantly outpacing many developed markets in adoption velocity.
Government initiatives like Digital India and National Health Stack are accelerating AI adoption in diagnostic imaging, genomic analysis, and personalized treatment protocols across Indian healthcare institutions.
Rising prevalence of diabetes, cardiovascular diseases, and cancer in India is driving demand for AI-powered precision diagnostics and targeted therapies to improve patient outcomes and reduce healthcare costs.
India is establishing itself as a global center for AI-driven medical research and development, with increasing investments from both domestic startups and international pharmaceutical companies establishing R&D centers.
| Report Metric | Details |
|---|---|
| Base Year | 2024 |
| Fastest Growing Segment | IMAGE ANALYSIS (Tool) |
| Forecast Period | 2024-2029 |
| Growth Rate | CAGR of 30.7% from 2024 to 2029 |
| Largest Segment | SOFTWARE (Component) |
| Market Size Base Year (Billions) | ~USD 0.79 (2024) |
| Revenue Forecast (Billions) | ~USD 3.92 (2029) |
| Segments Covered | Application, Type, Therapeutic Area, Component, Tool, Deployment, End User, Deployment 2022-2030 |
8 segment dimensions are covered across the global market.
| Segment | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | CAGR (%) |
|---|---|---|---|---|---|---|---|---|---|---|
| HEALTHCARE PROVIDERS | 5.09 | 6.45 | 8.16 | 10.33 | 13.07 | 16.53 | 20.9 | 26.41 | 33.37 | 26.4 |
| MEDICAL DEVICE/EQUIPMENT COMPANIES | 3.26 | 4.11 | 5.18 | 6.53 | 8.22 | 10.35 | 13.03 | 16.4 | 20.63 | 25.9 |
| OTHER END USERS | 1.2 | 1.5 | 1.87 | 2.34 | 2.92 | 3.64 | 4.54 | 5.65 | 7.04 | 24.7 |
| PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES | 4.15 | 5.14 | 6.37 | 7.89 | 9.76 | 12.08 | 14.94 | 18.47 | 22.82 | 23.7 |
| RESEARCH CENTERS, ACADEMIC INSTITUTES, & GOVERNMENT ORGANIZATIONS | 2.53 | 3.11 | 3.82 | 4.69 | 5.76 | 7.06 | 8.67 | 10.63 | 13.03 | 22.7 |
| TOTAL | 16.22 | 20.3 | 25.4 | 31.77 | 39.73 | 49.67 | 62.07 | 77.56 | 96.89 | 25 |
India's AI in Precision Medicine market was valued at USD 1.54 billion in 2024 and is projected to grow to USD 5.49 billion by 2029.
India's AI in Precision Medicine market is expected to grow at a compound annual growth rate (CAGR) of 18.5% from 2024 to 2029.
Key drivers in India include rising chronic disease prevalence, healthcare digitalization, government digital health initiatives, telemedicine expansion, and India's competitive advantage in software and data analytics.
India's adoption spans diagnostic centers, hospitals, research institutions, and pharmaceutical companies utilizing AI for drug discovery, genomic analysis, diagnostic tools, and clinical decision support systems.
While the global market grows at 30.7% CAGR, India's 18.5% CAGR reflects a maturing but rapidly expanding market with significant growth potential driven by localized healthcare needs and cost-effective innovation.
The study involved significant activities to estimate the current size of the AI in precision medicine market. Exhaustive secondary research was done to collect information on the AI in precision medicine market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain using primary research. Different approaches, such as top-down and bottom-up, were employed to estimate the total market size. After that, the market breakup and data triangulation procedures were used to estimate the market size of the segments and subsegments of the AI in precision medicine market.
This research study involved the wide use of secondary sources, directories, and databases such as Dun & Bradstreet, Bloomberg Businessweek, and Factiva; white papers, annual reports, and companies’ house documents; investor presentations; and the SEC filings of companies. The market for the companies offering AI in precision medicine solutions is arrived at by secondary data available through paid and unpaid sources, analyzing the product portfolios of the major companies in the ecosystem, and rating the companies by their performance and quality. Various sources were referred to in the secondary research process to identify and collect information for this study. The secondary sources include annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases.
Various secondary sources were referred to in the secondary research process to identify and collect information related to the study. These sources included annual reports, press releases, investor presentations of AI in precision medicine vendors, forums, certified publications, and whitepapers. The secondary research was used to obtain critical information on the industry’s value chain, the total pool of key players, market classification, and segmentation from the market and technology-oriented perspectives.
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, and related key executives from various key companies and organizations operating in the AI in precision medicine market.
After the complete market engineering (calculations for market statistics, market breakdown, market size estimations, market forecasting, and data triangulation), extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. Primary research was also undertaken to identify the segmentation types, industry trends, competitive landscape of AI in precision medicine solutions offered by various market players, and key market dynamics, such as drivers, restraints, opportunities, challenges, industry trends, and key player strategies.
In the complete market engineering process, the top-down and bottom-up approaches and several data triangulation methods were extensively used to perform the market estimation and market forecasting for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to list the key information/insights throughout the report.
Breakdown of Primary Participants:
Note 1: Others include sales managers, marketing managers, and product managers.
Note 2: Tiers of companies are defined based on their total revenues in 2023. Tier 1 = >USD 1 billion, Tier 2 = USD 500 million to USD 1 billion, and Tier 3 = < USD 500 million.
To know about the assumptions considered for the study, download the pdf brochure
Both top-down and bottom-up approaches were used to estimate and validate the total size of the AI in precision medicine market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:

After arriving at the overall market size using the market size estimation processes explained above, the market was split into several segments and subsegments. The data triangulation and market breakup procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment. The data was triangulated by studying various factors and trends from both the demand and supply sides.
The AI in precision medicine market utilises AI technologies such as machine learning and natural language processing to analyse complicated biological and clinical data in order to provide possibly personalised healthcare solutions. It promotes applications such as drug discovery, diagnostics, predictive analytics, and tailored treatment plans by integrating genomics, proteomics, and real-world data using AI capabilities with the goal of improving patient outcomes and accelerating innovation benefits for stakeholders ranging from pharmaceutical companies and healthcare providers to researchers.
Full forecast, segment splits, and company analysis for all AI in Precision Medicine Market.
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