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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 9, Issue 10, October 2018, pp. 835–845, Article ID: IJMET_09_10_087
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=9&IType=10
ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

TRANSFORMING INDIAN INDUSTRIES

THROUGH ARTIFICIAL INTELLIGENCE AND
ROBOTICS IN INDUSTRY 4.0
T. Dhanabalan*
Department of Logistics Management

A. Sathish
Alagappa Institute of Management
Alagappa University, Karaikudi Tamilnadu, India
*Corresponding author

ABSTRACT
Artificial Intelligence (AI) the magic word has changed our personal as well as
working life. Owing to its prospective features, adoption of AI is being treated as an
important one in the industry 4.0. Since its emergence, it brings lot of opportunities to
different industries as well as challenges. Thus a lot of AI powered technologies have
been developed with potential to improve the economy by improving the quality of life
significantly. In India, AI contributes a lot in different spheres of the economy such as
agriculture, manufacturing, and services sector like finance, transportation, public
administration and defence. And thus it considerably drives GDP growth. As a result,
the gains from AI are also expected to have a magnified effect on the above sectors.
Thus, in the globalization era, no country can isolate itself from the impact of the
advances in technology. However, the benefits can be maximized and losses can be
minimized by putting necessary infrastructure and policy in place. Though several
countries have decided their strategy for AI, India has not yet formulated its strategy.
Hence, the present article reviews the relevance of AI in Indian industries at present
and to the future and by the way it suggests way forward for India.
Key Words: Artificial Intelligence; Robotics; Machine Learning; Industries;
Technology
Cite this Article: T. Dhanabalan,A. Sathish, Transforming Indian Industries Through
Artificial Intelligence and Robotics in Industry 4.0., International Journal of Mechanical
Engineering and Technology, 9(10), 2018, pp. 835–845.
http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=9&IType=10

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 T. Dhanabalan,A. Sathish

1. INTRODUCTION
Artificial intelligence (AI) is a swiftly developing field with robots impacting our lives with
growing intensity. It has attracted an important place in the recent years. With the help of the
technologies such as machine learning (ML), we could make the technologies with the capable
of promoting their own concert by deriving from the data over time. According to PWC (2017)
that India has been depending on three major supporters namely the government, private sector
and academia for the AI related research process and innovation. Further, there are steps have
to be taken from corner to corner of these three groups, and their possible impact would be on
employment-related concerns, governance challenges and impediments to develop an eco
system, thus it would helpful to speed up research and development process. As a result, in
India there have been several initiatives and developments in the sphere of AI, ML and robotics,
by the academic community within business processes and consumer lifestyles. Hence, the
Ministry of Commerce and Industry, Government of India, plans to stimulate the use of AI
towards India’s trade and industry transformation. Kamakoti et al., (2018) mentioned the
relevance of AI and its impact on various industries in India. The industries are manufacturing,
fnancial services, agriculture, education and defence, and so on. Further, they have provided
some of the recommendations to the government for utilizing the AI led economic development.
Further, 2018 financial statement also point out that the government’s intention towards
investing more in the research activities related to AI, robotics and automation as part of
industry 4.0. Moreover, the Government of India was tasked with set up of a national
programme to conduct research and development in the above and other new age technologies
(Mendonca, 2018). Whereas these efforts would be at a strategic level with long term plans for
promoting the research and development as well as commercialization of AI powered solutions.
Further the prospect initiatives would be expected to take on a more operational approach with
definite incentives aimed at smoothen the progress of the incorporation of the smart solutions
within sectors and its allied functions. In terms of providing financial support for AI
programmes, the Ministry of Electronics and Information Technology, Government of India,
has been funding projects by educational institutions in the areas of ubiquitous computing and
wireless sensor networks for real-time landslide monitoring and perception engineering
artificial sensing, perceptual robotics. The ministry has also been operating a scheme called
Technology Incubation and Development of Entrepreneurs (TIDE) for promoting technology
innovation over the last decade (Meity, 2017). Further, there are possible potentials available
for companies to set up a research and development centers with government support and
encouragement through initiatives such as Digital India and Make in India, which have created
a conducive and favourable regulatory framework. More than 37 percent of large scale financial
establishments have already invested in these technologies and around 70 percent of the plan to
clinch it in the upcoming days (Belgavi et al, 2017).
As far as Indian economy is concerned, its most revenue has been coming from agriculture
sector and it is contributing nearly 18 percent of share in the total Gross Domestic Product
(GDP) of the country (Sunder, 2018). Thus, though India is an agrarian country, it has been
adopting the latest technologies in the agriculture sector with a view to foster the growth. On
the other hand the government of India also plans to augment the share of GDP from the
manufacturing sector upto 25 percent by 2022 with the help of the Make in India initiative
(India Brand Equity Foundation, 2018). Further, the services sector in India such as finance,
transportation, public administration and defence are considerably contributing to the GDP
growth. As a result, benefits from AI are also expecting to have an overstated outcome on the
above mentioned sectors with a annual GDP growth rate of 7.5 percent towards the Indian
economy (Financial Express, 2018), it also plans to tap the untapped potential of 2.2 percent of
the population that is differently abled (Kamakoti, 2018). With the help of technological

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 Transforming Indian Industries Through Artificial Intelligence and Robotics in Industry 4.0.

advancements this segments can be overcome the above mentioned barriers, by improving their
quality of life and contributing to their full potential towards the economy. With this backdrop
the present paper made an attempt to explore the relevance of AI and Robotics and their real-
life applications on the Indian industries.

2. RELEVANCE OF AI IN DIFFERENT INDUSTRIES

2.1 Manufacturing and Supply Chain Management
By the pressure of Industry 4.0, manufacturing industries are transforming themselves towards
digitization and developing their supply chain activities through Internet of Things (IoT).
Moreover, with the help of AI and ML techniques manufacturing sectors have been
transforming by incorporating better visibility, flexibility and operational competence in the
supply chain process. It includes robust demand forecasting and improved decision making
through structured scenario analysis. It also helps to the Inventory optimisation process by using
statistical modeling techniques. And thus it performs the inventory stock level as well as lost
sales scenario analysis (Hitachi. (2017). AI enabled manufacturing units are Optimising their
manufacturing processes by enhanced monitoring and auto-correction of processes; its result
the inefficient machines can be identified in the processes and adjusting parameters to get better
yields. All these things helps to the manufacturing industries to reduce cost of poor quality by
quantifying implicit and explicit costs associated with poor quality of work in progress (WIP)
and finished goods. The successful application of AI and robotics in the manufacturing and
supply chain sector has depended more on government and private sector intervention (Sharma,
2017).

2.2 Public Health and Safety

The Indian healthcare sector is already in pressure due to the high population density relative
to the number hospitals, medicinal facilities, physicians and care professionals. As a result, an
outsized segment of people is underprivileged position even for getting primary healthcare
services. While an absolute augment in the number of health care providers may not be instantly
possible, hence the AI enabled intelligent technologies can be utilized to boost up the efficiency
and accessibility of the existing resources and such a way that they can serve more patients with
the dual benefits of improved outcomes and at lower expenses (IANS, 2017). Indian start ups
and SMEs have leveraged AI to deal with the demand for high quality and affordable healthcare
services in the country. Start ups providing solutions and services in capturing patients related
data by using sensors in smartphones and wearable devices, remotely extracting information
from patient records for monitoring health, supporting diagnosis, enabling health trackers and
predicting onset of symptoms, and powering patient connectivity with specialists. These start
ups have been able to use big data and AI to detect conditions like cancer from medical imagery
and reports and to develop customized treatment plans for individuals. Thus, AI in India is
enhancing the productivity and availability of physicians (Tribune News Service, 2017). AI
powered robots can assist surgeons in conducting precise surgical procedures. AI platforms
have already established their credibility as expert systems for advising medical practitioners
on the diagnosis of diseases like cancer and recommending treatments. Other use cases for AI
include early identification of potential pandemics and tracking disease incidence to contain
spread, and image processing and diagnostics for radiology and pathology. Such assistive and
augmentative applications of AI play a critical role in enhancing efficacy, particularly that of
less experienced practitioners. In addition, they make healthcare accessible to a wider strata of
the society.

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 T. Dhanabalan,A. Sathish

2.3 Agribusiness
Agriculture and its allied sectors such as forestry and fisheries accounted for over 13 percent of
India’s GDP in 2013 and over 50 percent of the workforce (Kamakoti, 2018). Inadequate
demand prediction, lack of assured irrigation, soil degradation, overuse/misuse of pesticides
and fertilizers, availability of capital for farmers, and unorganized and low-tech practices are
some of the current challenges prevalent in the sector. And these challenges can be addressed
by utilizing AI powered intelligent solutions that would enable the farmers in smarter
production, processing, storage, distribution and consumption of agricultural products. Site
specific and timely data about crops facilitates the application of appropriate inputs on
fertilizers and chemicals, crop health and disease, spreads, monitoring health of farm animals,
and intelligent farm mechanization through autonomous machines such as harvesters, thus
improving the yield per square unit of land. Further down the value chain, AI and ML systems
can make commodity packaging and storage more effective with lower wastage and spoilage
(Kulkarni and Ganesh, 2017).

2.4 Banking and Financial Services

AI, ML and robotics have a wide range of use cases in financial services. However, their
potential has not been tapped fully in India. On the upside, though, financial services giants and
Financial Technology frms have joined hands on proof of concept initiatives centered on the
use of AI and ML to automate and streamline work flows in institutions (Economic Times,
2017). This includes the use of Chatbots to facilitate automated conversational flows and
efficient customer service, intelligent agents such as robot-advisors for personalised financial
planning, and advanced algorithms to facilitate fraud detection and prevention of money
laundering. Large financial bodies such as payment regulators handle billions of transactions
each day across different channels such as ATM withdrawals, credit card payments, and e-
commerce transactions. Advanced analytical techniques and ML algorithms, combined with
human expertise allow institutions to flag transactions as potentially fraudulent at the time of
occurrence and hence contain the damage as early as possible (Sarkar, 2017). The advent of
intelligent technologies comes at a time when the government is pushing towards financial
inclusion across the Indian economy by introducing schemes like Jan Dhan and Cashless India.
The importance of AI systems for drawing insights from large volumes of data and ensuring
transparency, speed and efficiency and regulatory compliance cannot be overstated (PWC,
2018). In addition, automated work flows and algorithmic risk scoring in banking and non-
banking financial institutions can further reduce incidents of breaches in compliance arising
from malpractices, lapses in human judgement, and low visibility on financial exposure to
certain counterparties and more. This would be expressly valuable to the lending segment which
has recently come under the microscope with respect to the risk assessment techniques used.
Innovations in AI such as ‘lean data learning’ techniques could allow institutions to assess
micro businesses and SMEs on limited historical data and in turn improve capital access to
them. AI, ML and robotics can potentially revolutionize customer experience, especially at the
‘last mile’, by providing more personalised services and improving the back-office efficiencies
at financial institutions. The financial services sector is critical to economic stability and the
possible implications of data privacy and security concerns are significantly high in this sector
(PTI, 2017).

2.5 Education
Intelligent tutoring systems have been developed since the eighties. Several applications have
been in use for quite some time. With the advances in AI techniques such as natural language
processing, etc, it has become possible to develop a number of new applications (Sunil kumar,

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 Transforming Indian Industries Through Artificial Intelligence and Robotics in Industry 4.0.

2018). As education itself is crucial for growth in several domains, the net impact of AI in
education would be quite high. The applications of AI in education include answering the
queries of the students, asking questions and providing feedback, assessment of narrative
answers. A study has predicted that AI would transform education during the next 4-5 years
(Kanejiya, 2017). Indian start-ups are successfully using AI to improve the quality of education.
Data collected from students can be used to help them work on past mistakes through a process
of feedback and personalised recommendations provided through an AI platform (Dalal, 2017).
This in turn helps students improve their scores over time. To a certain extent, it also resolves
the problem of teachers being unable to provide individual attention to students and of the
differential pace of student learning. ML techniques are also used to provide feedback to
teachers themselves. For example, by identifying areas where students lack clarity, the platform
can help teachers act on their knowledge delivery and rectify the gaps. Robotic teaching
assistants connected over the cloud may alleviate the inaccessibility of experienced knowledge
practitioners in remote locations by emulating their teaching style, either on a standalone basis
or in real-time collaboration with human teachers (Fagella, 2017).

2.6 Marketing and Customer Care

AI-powered products and services such as digital assistants, customer service bots, and
recommendation engines for e-commerce and entertainment portals are just a few examples of
AI making inroads into the lives of consumers. AI has been deployed by Indian start-ups to
improve user experience by providing personalised suggestions, preference-based browsing
and image based product search. Additional uses for AI applications include personalised
design and production, deep learning for predicting customer demand and orders, and efficient
inventory and delivery management (Dhanrajani, 2017). In the retail store setting, shopper-
friendly robots can help assist shoppers by directing them towards the appropriate product
stocked in a particular section of the store. There are a number of product and service
recommender systems such as the one used by Amazon on its shopping portal (Sunil kumar,
2018). It keeps a track of which items have been purchased by the people over a period of time
and identifies certain patterns which are used to decide the products and services of interest to
the user. These patterns are not fixed and hard coded in the system but are created using machine
learning techniques (Alluhaidan, 2018). Chatbot is being used to order products and services
online. A chatbot has been developed to order coffee from Starbucks. The customer can order
coffee using spoken natural language describing the type of coffee, etc and the order is sent to
the nearest Starbucks unit. The payment is made automatically using the pre-registered
credit/debit card (Sarah Perez, 2018).

2.7 Energy Sector

AI is being used in energy sector in several ways (Jucikas, 2018). Making energy clean,
affordable and reliable has been recognized essential for fighting against several problems
including poverty. Google has applied AI successfully in reducing the energy usage by 41%
which means several millions of dollars. Google used the technology used in Deep Mind for
predictions on loads at different points and controlling equipments efficiently, accordingly. In
view of this success, National Grid in the UK is working with Deep Mind team to explore the
opportunities. Deep Mind aims to cut the national energy bill by 11% by balancing energy
supplies to the national grid. The extra power generated by the operators but not used leads to
the wastage of power. This is becoming possible due to the availability of past data which is
used for learning and predictions. IBM is working with the Department of Energy in US for
solar energy prediction. IBM has developed the technology by several forecasting models and
integrating data on weather, environment and atmospheric conditions, etc collected from
different sources such as weather stations, satellites, sensor networks, etc. IBM claims that the

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 T. Dhanabalan,A. Sathish

model developed is 30% more accurate than the best available solar forecasting model. After
its successful application in solar energy, IBM is exploring the possibility of using it in wind
and hydro-power plants. AI has also been used to understand the consumer behaviour for
prediction of load pattern. In order to gather this data, the energy provider companies are
installing smart meters which send information on the usage periodically. As different persons
and different communities have different consumption patterns, it is important to gather this
data for prediction of loads (Sunil kumar, 2018).

2.8 Defence and National Security

AI finds application in the fields of defence and security as well. It can be leveraged to protect
economic sectors and infrastructure such as airports and power plants that are vulnerable to
attacks. Anomalous behaviour detection in individuals and infrastructure disruption prediction
powered by the use of distributed sensors and pattern recognition are just a few examples of the
potential use cases of AI in this sector (Kumar, 2017). Along with AI applications in defence,
robots can be used to perform jobs which are unsafe for humans such as recovering explosives,
detecting mines, space exploration, deep water probes, scouting for hostile territories and
capturing video feed, to name a few. The usage of AI and robots in defence and military began
with unmanned aerial vehicles (UAVs) and unmanned ground systems (UGS) guided bombs
and missiles.

2.9 General Utility Services

For public sector entities such as large energy, power and utility companies, AI and ML hold
high potential in the areas of smart metering real-time information on energy usage which
reduces wastage and loss, efficient grid operation, and storage and predictive infrastructure
maintenance thus benefiting companies and consumers through cost-effective supply and usage
of energy and leading to more secure supplies and fewer outages. Customers can tailor their
energy requirements through the use of smart meters and thus reduce costs. The data generated
in the process could be used for customized tariffs and more efficient supply. AI, ML and IoT
form a crucial component of the government’s vision of smart cities and smart industrial zones.
Cities provide a wealth of information that can be captured through various sources mass
transportation tickets, cameras and sensors on roads, pavements, airports, malls, tax
information, police flings, etc. thus creating endless possibilities for improving the quality of
services for citizens. Deep learning algorithms can assimilate the volumes of data captured
using IoT devices and generate actionable insights. They make it possible to figure out patterns
of footfall in public spaces over a timeline, peak loads of vehicles and parking lots, and to
identify increased incidence of crime at locations, among various other applications. One of the
most prominent outcomes would be monitoring real-time resource usage of public facilities
power, heat, water, fuel, etc. and autonomously adjusting inputs based on usage patterns, thus
leading to significant saving. AI can further be applied to strengthen public infrastructure such
as railways, civil aviation, nuclear plants, telecommunication towers and power stations.
Predictive maintenance using advanced analytical models can help improve the availability of
such infrastructure and reduce safety incidents associated with them (Deity, 2015).

2.10 AI Enabled Assistive Technology for Physically Challenged

AI-enabled assistive technology for differently abled individuals is an as yet untapped market
in India. While certain accessibility features are sometimes present in devices like smartphones,
they are often secondary and not necessarily built in keeping in mind consumer centricity for
the particular demographic (Umachandrani, 2017). An example of AI-embedded accessibility
features for the differently abled is the automatic captioning employed by leading video

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 Transforming Indian Industries Through Artificial Intelligence and Robotics in Industry 4.0.

streaming sites, aimed at catering to people with full or partial hearing impairment. Similarly,
AI holds high potential for easing the daily activities of people with visual, speech or mobility
impairments and allowing them to operate at higher levels of productivity. For example,
Smartphone apps with built-in image processing capabilities can describe an object or scene or
read the text of bills and documents to a visually impaired person (Mahalaskshmi, 2017). India
is growing in terms of the quality of smart prosthetics, incorporating newer designs and
technologies. However, it lags behind more developed countries when it comes to quality and
advancements. Also, affordability is a barrier for those differently abled people who fall within
the lower income groups. AI, in combination with other emerging technologies like 3D printing
and IoT, has great potential to fuel widespread availability, affordability and feasibility of
innovations in smart prosthetics (Simonite, 2017).

3. PRESENT SCENARIO OF AI STARTUPS IN INDIA

Several start-ups mushroom in the AI, ML, big data and cloud space which are attracting the
interest of investors, a significant number of whom offer products and services in healthcare,
Fintech, customer services and education (Kamakoti, 2018). This is further propelled by the
government’s flagship initiatives of Make in India and Startup India. Smaller and nimbler start-
up organisations are now becoming potent challengers to the existing market leaders through
innovation and the adoption of newer technologies. This shows great potential for AI/ML
growth in India. Large IT services companies are already coming up with their AI platforms,
while smaller niche AI start-ups are tracking specific problems, thus creating a holistic
ecosystem for AI to thrive in India. AI start-ups in India are venturing into multiple industries,
such as e-commerce, healthcare, education, and financial services, and retail and logistics
(Singh, 2016). Start-ups specialising in AI, ML and robotics have contributed significantly to
innovation in these fields over the last few years. Digital technologies have created
opportunities and allowed them to set up new revenue streams around these new technologies.
These startups and small and medium-sized enterprises (SMEs) can become suppliers of
comprehensive solutions which are either stand-alone or integrated applications which can be
adopted by businesses and consumers. Other than generating new revenue streams, they can
take advantage of new technologies to produce quality products at cheaper costs (Nair, 2017).

4. POLICY PLANNING PRIORITIES FOR THE FUTURE

4.1 The Road Ahead
India has a unique opportunity at this moment. Using the talent available within the country, it
can repeat the success story of IT industry. At the same time, if necessary steps are not taken in
time, it will lose the opportunity. AI can help in the major programmes of the Government viz.
Digital India, Make in India, and Skill India (Vempati, 2016; Ghosh & Mitra, 2017). In order
to accelerate development of AI technology and its applications, it is necessary to take steps for
Applications and Infrastructure Development, Policy and Regulations, Research and
Development and Human Resource Development.

4.2 Applications and Infrastructure Development

As in other countries, India can gain significantly by the adoption of AI technology. Most of
the applications developed elsewhere in the world can be developed in India as well. However,
the applications have to be customized for the local needs. Hence, the government of India must
create infrastructure to support development of AI applications. One critical infrastructure is
cloud which is needed for the development of applications. AI applications require high
computational power, large memory and storage space which are available on the cloud. Some

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 T. Dhanabalan,A. Sathish

systems which were possible but could not be built due to the unavailability of cloud
infrastructure earlier have been implemented on the cloud. Google translation system has
become possible only due to the availability of cloud. Several AI applications use public data
which is not supposed to be stored or processed outside the country. If one uses cloud space
from any vendor like Amazon, Microsoft, etc, the data may be hosted abroad; this is not
desirable due to several reasons. AI applications for public goods can be developed only if we
have adequate infrastructure for making it available to the developers. Often public data is not
made available for privacy reasons. However, such data can be anonymised before making it
available. High speed network is another requirement necessary for development of AI
applications. This is essential to collect and share large amount of data. Though connectivity
has become available in urban areas, it remains a problem for rural and remote areas.

4.3 Constructing Regulatory Framework for Data Privacy and Security

As AI applications touch several aspects of human life, regulations are needed to ensure safety
of the people, protection of privacy, etc. For instance, in the area of transport, if autonomous
vehicles are to be permitted on the roads or air, regulations are needed to ensure public safety.
A self-driving car must take care of enormous number of possible situations on the road. While
deciding the permission to use the autonomous vehicles, it is necessary to assess the potential
risks in both the situations i.e. when conventional vehicles are used and when AVs are used.
Regulations may be linked to the performance of the products. In this case, further use depends
on the performance. If AI-based applications / services are found to be safer than human-based
applications/services, more use may be permitted. If it is found to be less safe, the use should
be restricted till the further development of technology. Regulations are needed to permit the
use of AI in the critical domains like healthcare where the autonomous systems are expected to
advice on the diagnosis and treatment which may affect the recovery of the patient. At the
moment, people are often not comfortable with the machines taking such decisions with major
implications. In the beginning, it may be necessary to keep human doctor in the loop so that the
decisions could be reviewed. Regulations need to be made to ensure that the applications
developed are not biased towards a specific view. The biasing may be intentional when it is
incorporated by the developer of the application. Sometimes, it may be incorporated due to the
training data set. The developer may not do it intentionally.

4.4 RESEARCH AND DEVELOPMENT

Government has a major role to play in funding R&D and innovation projects. Most of the
developed and several developing countries are investing heavily in R&D and innovation in the
area of artificial intelligence. India needs to initiate a Programme to support R&D and
innovation in this area. Involvement of industry is necessary while funding R&D projects. A
major problem faced in India is that the R&D results don’t lead to commercial products. The
main reason of this situation is the absence of interaction between the R&D centres/academic
institutions and industry. In order to get the input from the industry, it is necessary to hold
discussions with them through regular workshops/meetings. Industry associations can play a
role in this matter. They can provide a consolidated view of the companies on the issues. The
companies need to be persuaded to form a consortium and so that a common fund could be
made available to support the projects at the R&D centres academic institutions for carrying
out research and development on the topics of common interest. Government agencies may
provide complementary financial support to these R&D centres academic institutions in the
high risk projects. Feasibility studies need to be conducted before initiating R&D or application
development projects. The success of AI projects depends on the tasks and domains.

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 Transforming Indian Industries Through Artificial Intelligence and Robotics in Industry 4.0.

4.5 Updating the Workforce on Bar With New Age Employability

In order to cope up with the problems due to the loss of jobs, the workforce will have to be
retrained to take up new types of jobs which may emerge with the automation of the processes.
As the people lose jobs, they must be retrained and re-employed by providing the necessary
training. For this, there is a need to look into education and training infrastructure and re-align
it with the needs of the present day. Both formal and informal education systems should be
reviewed to produce the manpower who can deal with the changing needs of the society. Indian
startup companies find it quite difficult to recruit engineers with AI background (Punit, 2018).
Several steps need to be taken. There is a need to initiate educational programmes in this area.
Most of the universities in the developed countries offer graduate programmes in AI. In contrast
to that, very few universities in India offer programmes in AI. Some educational institutions
offer AI as one subject in the B. Tech. or M. Tech. Programme. This is not sufficient in the field
like AI. The universities and technical education institutions need to be supported by the
Government for initiation of these programmes. There is a need to attract bright students to do
research in the area of AI. Doctoral and Post-doctoral fellowships should be instituted and made
available to the people interested in research in the area of AI. The fellowships should carry
higher stipend and other benefits to attract the talented students. These students should be
encouraged to work in the areas which can lead to useful applications.

5. CONCLUSIONS
India has a unique opportunity to apply the technology to solve some of its biggest problems
such as shortage of healthcare facility, low quality of education, etc. It is not possible to meet
the target of providing good healthcare or quality education using conventional methods. For
instance, the number of doctors needed, to provide good quality healthcare is so large that it
cannot be achieved in several years. AI technology provides an alternative to achieve the same.
The report has reviewed national status of adoption of artificial intelligence technology. While
the technology has potential to increase the economic growth rate considerably. Based on these,
it has suggested a way forward for India, which involves infrastructure development, policy,
regulations, research and development, and human resource development. All the stakeholders
need to come together to discuss on these issues. Government has a major role to play in
infrastructure development, applications in public sector, policy and regulations, technology
development and HRD. However, these can be successfully done with the support from
industry. Though the report has brought out the relevance of AI in Indian industries, it is
necessary to institute some studies to collect the precise information for deciding the steps on
infrastructure development, construction of regulatory frameworks, and technology
development, etc.

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