Machine Learning Market in India (2018-2023) Overview, Share, Scope, Revenue, Trends, Drivers, Challenges, Growth Forecast and Data on City-Wise Job Split and Implementation in Business Functions (Finance, Accounting, IT, Operations, Admin, General Management)

  • Ample Market Research

    Machine learning (ML) is an emerging artificial intelligence (AI) technology which is being adopted aggressively by retail, transportation (especially airlines), and financial services companies operating in India. In 2018, this resulted in the creation of ~0.18 Mn to ~0.2 Mn new jobs, for professionals who have skills and expertise in machine learning applications.

    Global market insights:

    The global machine learning market is expected to reach a value of INR 543.18 Bn by the end of 2023, from INR 91.83 Bn in 2017, expanding at a compound annual growth rate (CAGR) of nearly 42.99%. This growth is attributed to technological advancements, and its proliferation in the field of data generation.

    India market insights:

    In India, though the adoption of AI applications is still at a nascent stage, it is anticipated that the market will grow at a high rate in the coming years. Among the various AI technologies being implemented in India, the highest investments are in the field of machine learning applications. In India, investments in artificial intelligence (which was INR 773.64 Bn in 2017) is expected to expand at a CAGR of 33.49% during the 2018-2023 period. The reason behind such high anticipated investments is the growing popularity of AI technologies, especially ML applications, across business functions like finance, accounting, general management, IT, operations, and administration.  

    Key growth drivers of the market:

    o The implementation of machine learning reduces the chances of human error. Also, it makes machines smarter, thereby reducing their reliance on operators. In a way, machine learning enhances technicians’ accuracy and efficiency, owing to which many companies are switching from traditional data interpretation methods, to machine learning. This, in turn, is providing growth opportunities for the market in India.

    o Cloud-based analytics, when used in conjunction with machine learning, helps analysts identify anomalies in real time, so that they can be rectified swiftly. The introduction of the concept of stream-based analytic platforms has opened up new avenues for the extensive use of machine learning applications in various sectors of the Indian market.

    Key deterrents to the growth of the market:

    Most machine learning applications are interlinked with cloud-based analytics. In order to update customer information on cloud-based platforms, front line employees ask customers to provide their personal details (such as social security numbers, financial information, etc.). However, customers are often reluctant to share such information, owing to concerns regarding privacy. Customers’ apprehensions regarding the safety of their information hinders the implementation of machine learning applications.

    Companies covered:

    o Artivatic Data Labs Pvt. Ltd.

    o Formcept Technologies & Solutions Pvt. Ltd.

    o PixelCrayons

    o QBurst Technologies Pvt. Ltd.

    o Active Intelligence Pte. Ltd.

    o Amazon Web Services, Inc.

    o Fair Isaac Corporation

    o International Business Machines Corporation

    o Microsoft Corporation

    o Xoriant Corporation

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  • Chapter 1: Executive summary

    Chapter 2: Socio-economic indicators

    Chapter 3: Introduction

    3.1. Indian machine learning market - definition and structure

    3.2. Application of machine learning across industries

    Chapter 4: Global machine learning market

    4.1. Market overview

    4.2. Market size and growth forecast – value-wise (2017-2023e)

    4.3. Number of machine learning applications published by global companies (2017)

    o IBM

    o Microsoft

    o Google

    o LinkedIn

    o Facebook

    o Intel

    o Fujitsu

    Chapter 5: Artificial intelligence market in India

    5.1. Market overview

    5.2. Artificial intelligence market size and growth forecast – investment-wise (2017-2023e)

    5.3. Artificial intelligence jobs – city-wise split (2017)

    o Bengaluru

    o Delhi NCR

    o Mumbai

    o Hyderabad

    o Pune

    o Chennai

    o Others

    5.4. Artificial intelligence applications – business function-wise

    o Precision agriculture

    o Healthcare

    o Indian language project

    Chapter 6: Machine learning market segmentation in India

    6.1. Machine learning software development – sector-wise split (2018)

    o IT services

    o Electronics and heavy electrical

    o Agriculture

    o Automobiles

    6.2. Machine learning software development – focus area-wise split (2018)

    o Surveillance

    o Robotics

    o Language processing

    o Recruitment

    o Virtual assistant

    o Process management

    o Customer analytics

    o Analytics

    o Decision making

    6.3. Machine learning market – company type-wise split (2018)

    o International

    o Domestic

    6.4. Popularity of machine learning applications – business functions-wise split (2018)

    o Finance function

    o Accounting

    o General management

    o IT function

    o Operations/production

    o Administration

    Chapter 7: Key growth drivers of the market

    Chapter 8: Key deterrents to the growth of the market

    Chapter 9: Competitive landscape

    9.1. Artivatic Data Labs Pvt. Ltd.

    o Corporate information

    o Business description

    o Products and services

    o Key people

    Note: Similar information areas will be covered for the remaining competitors

    9.2. Formcept Technologies & Solutions Pvt. Ltd.

    9.3. PixelCrayons.com

    9.4. QBurst Technologies Pvt. Ltd.

    9.5. Active Intelligence Pte. Ltd.

    9.6. Amazon Web Services, Inc.

    9.7. Fair Isaac Corporation

    9.8. International Business Machines Corporation

    9.9. Microsoft Corporation

    9.10. Xoriant Corporation

    Chapter 10: Recent developments

    Appendix

    1. Research methodology

    2. About Research On Global

     

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