Dissertation Proposal
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Information Systems
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Nov 24, 2024
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Dissertation Proposal
Topic:
The role of artificial intelligence (AI) in Indian SME's & its
impact on business performance
1
Table of Contents
Background
..................................................................................................................................................
2
Literature Review
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3
Purpose……………………………………………………………………………………………………………………………………………………4
Decision Problems
.......................................................................................................................................
4
Research Questions
.....................................................................................................................................
4
Research Objectives…………………………………………………………………………………………………………………………………5
Proposed Research Methodology
...............................................................................................................
5
Secondary Research
................................................................................................................................
5
Primary Research
.....................................................................................................................................
5
Descriptive Research
...............................................................................................................................
6
Data analysis
............................................................................................................................................
6
Limitations
...............................................................................................................................................
6
Significance of the Research
........................................................................................................................
6
References
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8
Background
The Indian SME- Small and Medium Enterprise sector, which includes over 42 million
businesses, is fragmented. These businesses confront several obstacles, such as a lack of capital,
a scarcity of competent staff, and a reluctance to embrace new technologies. In recent years, the
Indian government has launched several efforts to assist SMEs in growing and modernizing
(Baabdullah, et al 2021). Adoption of cutting-edge technology, such as Artificial Intelligence
(AI), remains limited in the SME sector. AI might be a game changer for SMEs. SMEs may
profit from AI-powered tools and technology by automating repetitive processes, boosting
productivity, and enhancing decision-making. SMEs may benefit from AI through increasing
customer engagement, retention, and satisfaction. Nonetheless, the use of AI in Indian SMEs is
still in its infancy (Basri, 2020). According to an EY and Nasscom report, just 7% of Indian
SMEs have adopted AI technology. According to the survey, most SMEs are ignorant of the
advantages of AI (Rizvi, et al 2021). Several reasons contribute to Indian SMEs' slow adoption
of AI. For starters, SMEs have considerable hurdles in data management and data protection.
2
SMEs often lack the data management and security infrastructure required by AI-powered
technology. Second, many SMEs lack the in-house skills required to develop and run AI-
powered solutions. The high cost of AI-powered solutions is the last roadblock for SMEs
(Chatterjee, et al 2020). Despite the aforementioned hurdles, numerous Indian SMEs have begun
to reap the advantages of AI. Niramai, a Bengaluru-based SME, has created an AI-based breast
cancer screening tool. The technology uses machine learning algorithms to identify breast cancer
at an early stage, when it is more treatable. Freshdesk, a small and medium-sized enterprise
(SME) in Chennai, India, created an AI-powered help desk service (Rizvi, et al 2021). The
platform's natural language processing (NLP) algorithms evaluate user enquiries and give
appropriate replies.
Literature Review
The integration of AI has the potential to transform SME businesses. By swiftly analyzing vast
amounts of data, identifying patterns, and producing forecasts or critical insights that SME
businesses can use for strategic decision-making, AI may provide SMEs with a competitive
advantage. Efficiency, cost, output, and decision-making are all able to be enhanced
(Dhanabalan, and Sathish 2018). It has been demonstrated that AI-generated data significantly
influences management decisions. If AI is used to automate routine tasks, managers may be able
to make decisions that place a greater emphasis on individuals and patterns that are otherwise
difficult to identify (Nayal, et al 2022). Individuals might be able to make better decisions if
resource allocation and risk evaluation are enhanced (Kumar, et al 2023). AI solutions, such as
chatbots, virtual assistants, and customer service software may increase consumer satisfaction
and loyalty, leading to a rise in revenue. The prospective impact of AI on the profitability of
small and medium-sized enterprises (SMEs) is substantial. By assessing financial data to identify
underserved markets, expedite operations, and zero in on the ideal consumer, AI may increase
sales and profitability. According to Belhadi et al., (2021); Zhou et al., (2019), the credit risk
assessment enabled by AI is advantageous for SMEs. The integration of AI into businesses is
fraught with challenges such as data security, ethical dilemmas and resistance to change, despite
the potential benefits (Nayal, et al 2022). SMEs must also contend with a lack of capital, cutting-
edge technology and qualified personnel. It may be difficult for some small and medium-sized
enterprises (SMEs) to devote the necessary time, money and personnel to thoroughly adopt AI
3
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(Nayal, et al 2022). AI integration has been proven to be advantageous for SMEs. Using AI to
optimize its delivery routes, one Indian logistics company, for instance, reduced delivery times
by 15% and petroleum expenses by 20% (Sharma, et al 2022). Using AI-based technology to
enhance client connection led to a 25% increase in the customer contentment at another Indian
SME (Chowdhury et al. 2022).
Purpose
This research aims to examine the impact of AI on SME performance in India, specifically
focusing on its potential to enhance productivity and profitability. It will assess the role of AI
technologies in data analysis, decision-making, automation, and revenue generation. The
research will also consider the challenges related to infrastructure, training, and adaptability of
AI.
Decision Problems
The management need to address certain problems such as, if AI integration in SMEs can
facilitate business growth and higher profits by resolving the issue of customer relationship
management. To see how AI-generated data influence management decisions by resolving the
issue of determining real time data insights and predictive analysis of future trends. How AI-
supported decisions can increase efficiency for businesses by resolving the issue of repetitive
tasks through process automation. Assess if businesses and their human resources can easily
adapt to AI integration because of the improved communication and increased engagement level.
Research Questions
What is the impact of AI integration on the business performance of SMEs in India?
Sub-questions
How are various AI techniques and technologies used by Indian SMEs and how might these AI
technologies especially assist SMEs enhance their operational efficiency?
What hurdles does AI integration provide for India's SMEs and how can we overcome these
obstacles?
4
What variables impact the decision to use AI in India's SMEs and how AI integration can
influence these variables?
How can Indian SMEs use AI into their operations in the most lucrative way?
How can Indian SMEs guarantee a seamless transition to AI-powered workflows and how if at
all, can AI assist them?
Research Objectives
This research aims to determine if AI will aid the expansion and success of Indian SMEs as
below.
Firstly, to search for the role, challenges of AI for enhancing productivity and profitability
of SMEs in India.
Secondly, to collect data regarding the impact generated by AI on SME performances in
terms of decision-making, automation, and revenue generation
Thirdly, to analyze the elements that promote the effective usage of AI in Indian SMEs, and
the performance of SMEs in India
Fourthly, to recommend strategic plan and techniques for incorporating AI in Indian SMEs
regarding the enhancement of performance and profitability.
Proposed Research Methodology
Secondary Research
To understand the present situation of AI in SME businesses in India, secondary research is
important. In our secondary research, we will consult the following sources.
External sources
Do library research using internet resources such as DOAJ, JSTOR and EBSCO. Forbes, MIT
Technology Review and Harvard Business Review are examples of trade publications and
industry magazines. SME businesses are the focus of AI research on the internet. Famous
consulting organizations such as McKinsey, Deloitte and PwC have provided reports and
research.
Primary Research
Exploratory Research
5
To better understand the difficulties SME businesses in India have while implementing AI into
their operations, exploratory research will be carried out. The following strategies will be
implemented:
Research through peer-reviewed articles
Support from supervisor (where needed)
Internet-based research on Indian SMEs.
Descriptive Research
To learn more about how AI is impacting SME businesses in India, descriptive research will be
done. The outcomes of exploratory research will be used to address the research questions. The
following methods will be employed:
The primary goal is to conduct secondary research to support the SMES in India. Peer reviewed
and journal articles will be utilized to gather the data and address the research aim and
objectives. To make sure the up-to-date information is used, the research will include the articles
no older than 2012.
Data analysis
To further understand the link between AI integration and financial success, the acquired data
will be statistically analyzed utilizing methods such as regression analysis. The gathered data
will also be analyzed using content analysis methods in order to uncover patterns and insights.
Limitations
The following limitations may be encountered during the research
SME businesses that have deployed AI may struggle to acquire access to their internal
data.
Because there is no historical data, it is difficult to compare how businesses performed
before and after AI integration.
Significance of the Research
The research on the impact of AI integration on the business performance of SMEs is crucial for
theory, practice, and policy.
1.
Theory/Literature
: This research will contribute to the existing corpus of knowledge by
investigating the unique manner in which Indian SME's utilize AI approaches and
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technology. It will cover a void in the literature by providing insights into the impact of
AI on the growth and performance of small and medium-sized enterprises (SMEs). The
research findings can also be used to gain a better understanding of the variables that
influence the decision to employ AI, as well as the impact that effective integration has
on those variables.
2.
Practice
: The research will benefit Indian small and medium-sized businesses in the
actual world. If SMEs devote time and effort to investigating them, the challenges of AI
integration may be better understood, and solutions for overcoming them may be
developed. The research will provide guidelines to enable SMEs to effectively integrate
AI into their operations, thereby enhancing operational efficiency and commercial
performance.
3.
Policy
: The research findings may assist policymakers and government agencies in
comprehending the potential advantages and limitations of AI integration in SME.
Financial incentives, training and support programs, and the creation of a hospitable
regulatory environment are all examples of policy ideas that could be implemented to
encourage the adoption of artificial intelligence in small and medium-sized enterprises.
This has the potential to aid in the expansion and success of SMEs, as well as contribute
to the growth and prosperity of the Indian economy and the creation of new jobs.
7
References
Baabdullah, A.M., Alalwan, A.A., Slade, E.L., Raman, R. and Khatatneh, K.F., (2021). SMEs
and artificial intelligence (AI): Antecedents and consequences of AI-based B2B practices.
Industrial Marketing Management, 98, pp.255-270.
Basri, W., (2020). Examining the impact of artificial intelligence (AI)-assisted social media
marketing on the performance of small and medium enterprises: toward effective business
management in the Saudi Arabian context. International Journal of Computational Intelligence
Systems, 13(1), p.142.
Belhadi, A., Kamble, S.S., Mani, V., Benkhati, I. and Touriki, F.E., (2021). 'An ensemble
machine learning approach for forecasting credit risk of agricultural SMEs’ investments in
agriculture 4.0 through supply chain finance. Annals of Operations Research, pp.1-29.
Chatterjee, S., Nguyen, B., Ghosh, S.K., Bhattacharjee, K.K. and Chaudhuri, S., (2020).
Adoption of artificial intelligence integrated CRM system: an empirical study of Indian
organizations. The Bottom Line, 33(4), pp.359-375.
Chowdhury, S., Budhwar, P., Dey, P.K., Joel-Edgar, S. and Abadie, A., 2022. AI-employee
collaboration and business performance: Integrating knowledge-based view, socio-technical
systems and organisational socialisation framework.
Journal of Business Research
,
144
, pp.31-
49.
Dhanabalan, T. and Sathish, A., (2018). Transforming Indian industries through artificial
intelligence and robotics in industry 4.0. International Journal of Mechanical Engineering and
Technology, 9(10), pp.835-845.
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Kumar, P., Sharma, S.K. and Dutot, V., (2023). Artificial intelligence (AI)-enabled CRM
capability in healthcare: The impact on service innovation. International Journal of Information
Management, 69, p.102598.
Nayal, K., Raut, R., Priyadarshinee, P., Narkhede, B.E., Kazancoglu, Y. and Narwane, V.,
(2022). Exploring the role of artificial intelligence in managing agricultural supply chain risk to
counter the impacts of the COVID-19 pandemic. The International Journal of Logistics
Management, 33(3), pp.744-772.
Rizvi, A.T., Haleem, A., Bahl, S. and Javaid, M., (2021). Artificial intelligence (AI) and its
applications in Indian manufacturing: a review. Current Advances in Mechanical Engineering:
Select Proceedings of ICRAMERD 2020, pp.825-835.
Sharma, M., Luthra, S., Joshi, S. and Kumar, A., (2022). Implementing challenges of artificial
intelligence: Evidence from public manufacturing sector of an emerging economy. Government
Information Quarterly, 39(4), p.101624.
Zhu, Y., Zhou, L., Xie, C., Wang, G.J. and Nguyen, T.V., (2019). 'Forecasting SMEs' credit risk
in supply chain finance with an enhanced hybrid ensemble machine learning approach'.
International Journal of Production Economics, 211, pp.22-33.
9
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