
Region:Asia
Author(s):Meenakshi Bisht
Product Code:KROD1460
October 2024
81

The India AI Market is segmented into different factors like by technology, by end user industry and by region.
By Technology: The market is segmented by technology into machine learning, natural language processing (NLP), and robotic process automation (RPA). In 2023, Machine learning dominated the market due to its broad applications in predictive analytics, customer segmentation, and automated decision-making. Its widespread adoption across various industries has solidified its leading position in the market.

By End-User Industry: The market is segmented by end-user industry into healthcare, finance and retail. In 2023, healthcare, such as diagnostic tools and personalized medicine, have driven significant growth. The increasing focus on healthcare innovation and patient care is contributing to the sector's dominance due to the significant impact of AI in enhancing diagnostic accuracy and reducing human error.

By Region: The market is segmented by region into north, south, east and west. Southern region was dominating the market in 2023. The city's dominance can be attributed to its status as India's tech hub, housing numerous AI startups, research institutions, and tech giants. The presence of a well-established IT infrastructure, a large pool of skilled professionals, and favorable government policies have created an ecosystem conducive to AI innovation and growth.
|
Company |
Year of Establishment |
Headquarters |
|---|---|---|
|
IBM India Pvt. Ltd. |
1992 |
Bangalore, Karnataka |
|
Accenture |
1989 |
Dublin, Ireland |
|
Tata Consultancy Services (TCS) |
1968 |
Mumbai, Maharashtra |
|
Infosys Limited |
1981 |
Bangalore, Karnataka |
|
Wipro Limited |
1945 |
Bangalore, Karnataka |
The India AI Market is anticipated to grow substantially by 2028. The proliferation of AI applications in emerging sectors such as agriculture, education, and smart cities, combined with supportive government policies and initiatives, will drive this expansion. Advances in AI research and increasing collaboration between academia and industry will further enhance the market's growth prospects.
|
By Technology |
Machine Learning NLP Robotics |
|
By End-User Industry |
Healthcare Finance Retail |
|
By Region |
North South West East |
1.1. Definition and Scope
1.2. Market Taxonomy
1.3. Market Growth Rate
1.4. Market Segmentation Overview
2.1. Historical Market Size
2.2. Year-on-Year Growth Analysis
2.3. Key Market Developments and Milestones
3.1. Growth Drivers
3.1.1. Increasing Investments
3.1.2. Rising Adoption in Healthcare
3.1.3. Integration in Financial Services
3.1.4. Government Support
3.2. Restraints
3.2.1. Shortage of Skilled Professionals
3.2.2. Data Privacy and Security
3.2.3. High Implementation Costs
3.2.4. Regulatory and Ethical Challenges
3.3. Opportunities
3.3.1. Expansion in Healthcare
3.3.2. Financial Services Growth
3.3.3. Smart Cities Integration
3.3.4. Retail Innovations
3.4. Trends
3.4.1. AI in Healthcare
3.4.2. AI in Financial Services
3.4.3. AI in Smart Cities
3.4.4. AI in Retail
3.5. Government Regulation
3.5.1. India AI Mission
3.5.2. AI Research Centers
3.5.3. National AI Strategy
3.5.4. Tech Company Partnerships
3.6. SWOT Analysis
3.7. Stakeholder Ecosystem
3.8. Competition Ecosystem
4.1. By End User Industry (in Value)
4.1.1. Healthcare
4.1.2. Finance
4.1.3. Retail
4.2. By Technology (in Value)
4.2.1. Machine Learning
4.2.2. Natural Language Processing (NLP)
4.2.3. Robotics
4.3. By Region (in Value)
4.3.1. North
4.3.2. South
4.3.3. East
4.3.4. West
5.1 Detailed Profiles of Major Companies
5.1.1. IBM India Pvt. Ltd.
5.1.2. Accenture
5.1.3. Tata Consultancy Services (TCS)
5.1.4. Infosys Limited
5.1.5. Wipro Limited
5.2 Cross Comparison Parameters (No. of Employees, Headquarters, Inception Year, Revenue)
6.1. Market Share Analysis
6.2. Strategic Initiatives
6.3. Mergers and Acquisitions
6.4. Investment Analysis
6.4.1. Venture Capital Funding
6.4.2. Government Grants
6.4.3. Private Equity Investments
7.1. AI Standards
7.2. Compliance Requirements
7.3. Certification Processes
8.1. Future Market Size Projections
8.2. Key Factors Driving Future Market Growth
9.1. By End User Industry (in Value)
9.2. By Technology (in Value)
9.3. By Region (in Value)
10.1. TAM/SAM/SOM Analysis
10.2. Customer Cohort Analysis
10.3. Marketing Initiatives
10.4. White Space Opportunity Analysis
Ecosystem creation for all the major entities and referring to multiple secondary and proprietary databases to perform desk research around the market to collate industry level information.
Collating statistics on India AI Market over the years, penetration of marketplaces and service providers ratio to compute revenue generated for India AI Industry. We will also review service quality statistics to understand revenue generated which can ensure accuracy behind the data points shared.
Building market hypothesis and conducting CATIs with industry experts belonging to different companies to validate statistics and seek operational and financial information from company representatives.
Our team will approach multiple technologies companies and understand nature of product segments and sales, consumer preference and other parameters, which will support us validate statistics derived through bottom to top approach fromsuch industry specific firms.
The Indian AI Market was valued at USD 5 billion in 2023, driven by increasing investments in AI technologies, the rise of AI startups, and widespread adoption across industries such as healthcare, finance, and retail.
Challenges in Indian AI Market include a shortage of skilled AI professionals, data privacy and security concerns, high implementation costs, and regulatory and ethical issues surrounding the deployment of AI technologies.
Key players in the Indian AI Market include IBM India Pvt. Ltd., Accenture, Tata Consultancy Services (TCS), Infosys Limited, and Wipro Limited. These companies lead in AI development and deployment due to their robust technological infrastructure and extensive R&D capabilities.
The Indian AI Market is propelled by factors such as increasing investments in AI startups, rising adoption of AI in healthcare, integration of AI in financial services, and strong government support and initiatives to promote AI innovation and adoption.
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