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Journal of Governance and Regulation / Volume 12, Issue 2, 2023
176
FUTURE PROSPECTS AND CHALLENGES
OF INTEGRATING ARTIFICIAL
INTELLIGENCE WITHIN THE BUSINESS
PRACTICES OF SMALL AND MEDIUM
ENTERPRISES
Arbiana Govori *, Qemajl Sejdija **
* Haxhi Zeka University, Pejë, the Republic of Kosovo
** Corresponding author, Haxhi Zeka University, Pejë, the Republic of Kosovo
Contact details: Haxhi Zeka University, UÇK Street, 30000 Pejë, the Republic of Kosovo
Abstract
How to cite this paper: Govori, A., &
Sejdija, T. F. (2023). Future prospects and
challenges of integrating artificial
intelligence within the business practices
of small and medium enterprises. Journal
of Governance & Regulation, 12(2),
176–183.
https://doi.org/10.22495/jgrv12i2art16
Copyright © 2023 The Authors
This work is licensed under a Creative
Commons Attribution 4.0 International
License (CC BY 4.0).
https://creativecommons.org/licenses/by
/4.0/
ISSN Online: 2306-6784
ISSN Print: 2220-9352
Received: 07.10.2022
Accepted: 31.05.2023
JEL Classification: O11, O12, O14, O20,
O30, O31, O33, O34, O36
DOI: 10.22495/jgrv12i2art16
Artificial intelligence (AI) has become a popular technology of
this era due to its potential to transform businesses. Therefore,
various businesses are focused on adopting this technology to
enhance their business. However, due to challenges, not all
organizations can adopt AI for their business functions.
Considering the importance of AI and small and medium-sized
enterprises (SMEs) in the economy, this study aimed to examine
the challenges and prospects of AI for SMEs. The study
performed review-based research to examine past literature to
determine the key challenges facing SMEs in AI integration. It was
noted in the results that costs and technical requirements of AI
remain the topmost challenges for SMEs to implement AI. These
challenges remain the major hindrance to the adoption of AI, and
thus, this study analyzes these issues deeply to provide
organizations with the insight to overcome these problems.
The study also noted that the prospects of AI in SMEs are great as
the costs of AI are reducing, and with more research and
development, AI integration will become more convenient.
Therefore, this research provides key details into the problems
facing AI adoption contemporarily and how they can be solved in
the future.
Keywords: Artificial Intelligence (AI) Integration, Challenges,
Future Prospects, Small and Medium-Sized Enterprises (SMEs)
Authors’ individual contribution: Conceptualization — A.G. and Q.S.;
Methodology — A.G.; Validation — A.G. and Q.S.; Formal Analysis —
A.G. and Q.S.; Resources — A.G.; Data Curation — A.G. and Q.S.;
Writing — Original Draft — A.G. and Q.S.; Writing — Review &
Editing — A.G. and Q.S.
Declaration of conflicting interests: The Authors declare that there is
no conflict of interest.
1. INTRODUCTION
In the present era of digitalization, it is not possible
to overlook the significant contributions made by
artificial intelligence (AI) which holds the potential
to transform the economic system foundations of
small and medium-sized enterprises (SMEs) (Polas
et al., 2022). From healthcare to the retail sector, AI
has a high demand across industries for continuous
progress. Lu et al. (2022) signified that SMEs are
considered the driving force of economic growth and
employment and can successfully transform into
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
177
an emerging digital world. SMEs have been greatly
influenced by AI applications in services, customer
support, communication, and interactions (Krafft
et al., 2020). Drydakis (2022) further added that
SMEs are aiming to integrate digital technologies
facilitated by AI to improve their market value and
competitive edge. The investment in AI by the SMEs
is envisioned to improve their track of user’s
behaviours and habits while offering
recommendations to alter the purchasing intention
of the customers through media communication.
However, the outbreak of COVID-19 led to lockdown
measures which increased the vulnerability of SMEs
as opposed to large corporations, thereby leading to
higher uncertainties and greater challenges for SMEs
(Lu et al., 2022). Irrespective of the government
measures to curb the financial loss, SMEs have not
completely recovered from the losses and demand
urgent measures to adequately resolve
the challenges to sustain and promote their business
continuity. Due to this, more organizations are
willing to adopt AI to enhance their performance.
However, there are specific challenges that are faced
by businesses. More specifically, SMEs face
significant problems when implementing AI.
However, there is no significant research available
that consolidates the challenges and future
prospects for AI adoption in SMEs. In this regard,
this study focuses on covering this gap. The primary
purpose of this study is to develop an insight into
future prospects and challenges for integrating AI in
SMEs’ business environments. The study focuses on
SMEs and the integration of AI, for which
the research objectives of the present study are:
1. To analyze the significance of AI integration
in SMEs by evaluating their applications.
2. To project the future implications and
challenges of AI in the business operations of SMEs.
3. To develop in-depth research regarding AI’s
possible applications and draw future
recommendations to implement on SMEs as
successive measures.
The remainder of the paper is organized as
follows. Section 2 reviews the literature relevant to
the study topic. Section 3 is the methodological
roadmap of the study, reflecting on where data is
collected and how the data will be analyzed to derive
the study results. Section 4 includes the results of
the study, and findings are represented to give
a comprehensive understanding of the study results.
Section 5 contains a detailed discussion of
the results of this study, with further comparison of
the cited literature to support the findings. Section 6
highlights the study’s conclusion that summarizes
the entire research.
2. LITERATURE REVIEW
Businesses have recently been using AI for chatbots
to communicate with their customers. Chan et al.
(2018) in the study stated that AI enhances
the performance (efficiency) of SMEs by increasing
their productivity. AI in SMEs helps to track user
activities and consumer behaviour and provides
recommendations, and media communication,
boosts trade activities, improving organizational
performance by reducing cost and time for business
processes and automating them. Recent application
of AI in SMEs includes QR code technology, which is
used worldwide for inventory management, data
recording, accounting, identifying consumer
preferences, and predicting future demands of
consumers through data analysis. A plethora of
studies have described the ability of SMEs to
transform by digitally integrating AI technologies
due to their precise business operations (Lu et al.,
2022; Drydakis, 2022; Polas et al., 2022). According
to the study of Hansen and Bøgh (2021), machine
learning and data analytics methods are used to
apply to Internet of Things (IoT) sensors, as IoT
sensors have a great capacity to store massive data.
SMEs are usually presented as less capable of
adopting AI, a factor of lacking resources. However,
certain tasks such as scheduling meetings,
responding to general queries of users, and
marketing campaigns to enhance consumer
purchasing decisions can be automated through AI
software in SMEs (Fan et al., 2020). Thus, there is
a high potential for SMEs to improve their business
capabilities through the integration of AI.
With these merits, AI becomes a motivation for
businesses to operate intelligently, reducing labour
costs and increasing accuracy. The most effective AI
application of SMEs is in marketing, in which
the systems embed machine learning algorithms for
data training and analysis for targeting customers
and constructing communication channels through
behaviuor analysis (Canhoto & Clear, 2020). It also
automates the tracking of marketing expenditures
minimizing the time spent on the manual tracking
process of marketing campaigns (Drydakis, 2022).
Moreover, AI enhances sales, which is recognized as
a revenue generator for a business. SMEs have
induced AI tools in sales to identify the best
strategies used by sales representatives compared
with the rest. This application of AI software helps
in training salespeople to communicate like affluent
sellers enhancing their operational performance and
productivity. Thus, AI marketing is direct marketing
evolution based on data analytics with AI models.
Moreover, the chatbots scale up customer
engagement reducing the resources to interact with
them, reflecting the efficient and successful
application of AI in SMEs. Online chatbots drive
customer engagement and retention by
automatically communicating with them for their
queries and reducing the waste of time consumers
are waiting for an immediate response (Hoikkala &
Ojala, 2022). Determining purchasing patterns,
consumer preferences, and responses to a certain
product helps businesses to make better decisions
to enhance product quality (Selamat & Windasari,
2021). As far as a competitive advantage is
concerned, it is difficult for businesses to manually
track the daily amount of data produced by
comparative businesses related to strategies (Conick,
2017). However, AI tools and software provide
a broad scope to address the challenge by tracking
business operations through social media sites,
applications, and websites, including pricing
strategies, PR activities, and technological initiatives.
Collectively with natural language processing,
the business metrics propose evolving trends in
SMEs and competing markets. Moreover, business
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
178
gaps, quality assurance, strengths, and weakness
leads to businesses developing their strategy for
enhanced production and performance.
Irrespective of the growing opportunities,
cybersecurity in SMEs serve as the major challenge
that jeopardizes an organization’s reputation. With
the increasing AI proficiencies, cyber attackers also
evolve with techniques to steal data. AI-based
systems work on large data and process it according
to business needs, which is a risk factor for security
risk (Drydakis, 2022). AI systems merge with
machine learning to integrate special security
systems in software and applications. Machine
learning algorithms enable the system to detect
anomalous activity from any user, improving
the security aspects and preventing cyber threats
that large SMEs are facing (Chan et al., 2019).
Moreover, a lack of technical skills is the main
challenge highlighted in the study of Black and
van Esch (2020), who proposed another useful tactic
by providing jobs and recruiting intelligently from
AI software in SMEs. It has been a strategic concern
for SMEs to recruit talented and skilful individuals to
perform job duties. The process application reduces
mistakes by increasing efficiency and accuracy by
automating recruitment (Hamilton & Davidson,
2018). Therefore, AI aids by processing information
of the candidate for screening, interviewing, and
communicating.
Besides the immeasurable advantages, SMEs do
not usually opt for an organization’s use of AI-based
technology. The main concerns involve security and
privacy issues, lack of skill practice among SME
employees, and lack of resources to implement AI.
However, according to the OECD (2021), SMEs have
a higher capability to attain change promptly as
compared to larger firms for having limited layers of
management. Onu and Mbohwa (2021) proposed
that SMEs operating on a smaller scale have minimal
access to markets and resources, and the cost
applied to the integration of AI projects is much
higher. It raises the concern of increased cost and
a fear of difficulty in adopting the system
(Chatterjee et al., 2021). The users in SMEs, due to
lack of practice and training, vacillate between
adopting AI-empowered products (software),
although there is a great need for SMEs to manage
information efficiently and perform analysis to
reduce cost and make appropriate decisions for
business processes. Manually performed tasks need
to be transformed into automatic processes to
reduce the manual workforce and project innovative
measures against traditional business practices of
SMEs.
The study of Drydakis (2022) studied the
various aspects of AI applications, including cyber
security, automated communication, cash flow,
pricing, and prediction of consumer needs. These
applications are advantageous, but on the other
hand, SMEs do not implement AI in their business
processes at the initial stage of high cost and
requirement of technical skill set. However, these
strategies have been proven to be efficient during
external changes affecting business performance.
The theory of technology acceptance model (TAM) is
applied to the research as it is the most effective
model for implementing technological change and
acceptance in organizations. Applying this theory to
SME business models leads to accepting the changes
that can be informed or uninformed, as
the perceived ease of use and behavioural intentions
are factors that encourage the use of technology
across companies (Gamage, 2019). As AI
implementation is a form of digital innovation in
business, SMEs need to be analyzed based on
capacity and budget for adoption.
3. STUDY FRAMEWORK
The methodology used in this study is a systematic
literature review, which is a qualitative research
approach that systematically searches, selects,
appraises, and synthesizes existing literature on
a particular topic. The systematic literature review
was chosen for this study as it provided
a comprehensive overview of the existing research in
the area of AI integration in SMEs and allowed for
the identification of common themes and patterns
regarding the challenges and prospects of AI
integration.
The first step in the systematic literature
review was to conduct a comprehensive search of
multiple databases, including Scopus, Web
of Science, and Google Scholar. The search was
performed using a set of key terms, including ―AI
integration in SMEs‖, ―application of AI in SMEs‖,
―challenges of AI integration‖, ―future of AI in SMEs‖,
and similar terms. This search was conducted to
identify relevant articles that met the selection
criteria.
The second step was to select articles that met
the criteria of being published after 2016 and that
were relevant to the integration of AI in SMEs.
The reason for setting this criterion was to ensure
that the most recent information was gathered from
the literature review and that the results of
the study were up-to-date and relevant.
The third step involved extracting relevant
information from the selected articles, including
the authors, year of publication, and the main
findings.
The fourth step involved analyzing
the extracted information to identify common
themes and patterns regarding the challenges and
prospects of AI integration in SMEs. The findings
from the data analysis were then interpreted in
the final step to provide a comprehensive
understanding of the challenges and prospects of AI
integration in SMEs.
In conclusion, the systematic literature review
provided a comprehensive overview of the existing
research in the area of AI integration in SMEs and
allowed for the identification of common themes
and patterns regarding the challenges and prospects
of AI integration. The methodology used in this
study was systematic and structured, which ensured
that the results were reliable and consistent.
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179
4. RESULTS
The study by Hansen and Bøgh (2021) performed
a review-based study considering the use of AI and
the IoT in SMEs. The authors noted that there had
been a significant increase in the trend of AI and IoT
in SMEs due to the vast benefits they offer. The IoT
and AI are two of Industry 4.0’s most talked-about
subjects. There have been numerous publications on
these subjects, although they mainly concentrate
on larger businesses. However, SMEs are regarded as
the major economic support of many countries;
hence, it is essential that these businesses have
simple access to and the ability to implement new
technologies. SMEs should first focus on machine-
wise implementation because it is less expensive
than full production-wise adoption. However, a large
number of the cases involved computer usage
monitoring. Although it is a fantastic approach to
learning more about production, it does not cover
the whole range of IoT in Industry 4.0. SMEs have to
concentrate on utilizing IoT in additional situations,
including machine-based predictive analytics.
Additionally, observed were the lack of machine
vision applications and the fact that, provided
the necessary expertise is present, good results may
be obtained with a low-cost solution. Therefore, this
study showed that the prospects of AI are bright for
SMEs, and organizations should adopt the use of
this advanced technology to enhance their
operations and performances.
Moreover, another study by Onu and Mbohwa
(2021) performed a qualitative examination of AI,
Industry 4.0, and IoT in SMEs, especially in
developing countries. Emerging technologies are
developing quickly, and thus, they have also
intruded into the business landscape. Operations in
the industry are likewise evolving quickly.
As a result, the development and use of many
Industry 4.0 technologies, including big data
analytics and the IoT, show enormous promise for
launching sustainable production. In order to
improve the operational performance of SMEs and
future decisions to support technological
innovation, the present research examines
the potential and difficulties of Fourth Industrial
Revolution (4IR) implementation for sustainable
operations. SMEs may now include new technologies
to offer to utilize local manufacturing robots and,
soon, sophisticated technological solutions. As long
as they form a strategic alliance and advance along
with the trend of creative manufacturing and
effective production methods, these emerging
countries may become highly competitive to become
a centre of manufacturing and advanced technology
globally. Therefore, SMEs in developing nations must
take into account assisting the development of
digital connection skills and capacity, addressing
the usage of standards for interoperability, and
finding ways to improve governance. In order to
accept and benefit from the reality of the developing
technological paradigm, SMEs must mainstream
science, technology, and innovation.
Furthermore, Baabdullah et al. (2021) performed
a survey-based study to determine the factors that
influence the acceptance of AI in SMEs. A survey was
conducted with 392 B2B (―business-to-business‖)
SMEs, and the results were examined. The findings
of the study concluded that among AI enablers,
mindset and technological road mapping had
a substantial impact on the acceptance of AI
practices but not professional expertise.
Infrastructure and awareness, but not technicalities,
had a substantial impact on the AI readiness factors
related to the adoption of AI techniques.
The performance and governance of relational AI
systems, as well as SME business customer AI-based
interactions, were shown to be strongly impacted by
the adoption of AI practices. The study also notes
that the development of SMEs is a crucial strategy
for attaining economic growth in the Middle East,
and successful technology adoption is essential for
the survival of SMEs. AI is a member of a new
generation of technologies that can help businesses
gain a competitive edge, but there is presently no
proof of its use in Middle Eastern B2B SMEs. Hence,
it is important that SMEs promote the factors that
enhance their acceptance of AI so that they can
benefit in the form of better growth and expansion.
Moreover, another research by Polas et al.
(2022) examined the factors influencing
the adoption of blockchain technology (BT) by SMEs,
applying AI, and using risk-taking behaviour as
a mediating lens. In order to collect the data,
the researchers conducted a survey with
150 owners/top managers from 150 SMEs (one
informant from each). Structured equation
modelling was used to examine the combined effect
of internal and external factors on the desire to
utilize BT. The study’s conclusions suggest that
a favourable and significant influence on
the adoption of BT comes from knowing AI.
Additionally, the adoption of BT is positively and
significantly impacted by the beneficial value of AI
as well as by perceptions of AI’s usability and ease
of use. The study makes the key claim that
the perceived utility and usability of AI have a big
impact on technology adoption.
In addition, to ascertain if AI applications are
connected to decreased business risks for SMEs,
the study by Drydakis (2022) uses the International
Labor Organization’s SMEs COVID-19 pandemic
business risks scale. To measure the utilization of AI
applications in essential activities, including
marketing and sales, pricing, and cash flow, a new
10-item scale was created. The study was performed
in London, England, and data were acquired from
317 SMEs. The study noted that the usage of AI in
SMEs can have a favourable impact on both small
and medium-sized businesses’ performance by
reducing the business risks brought on by
the COVID-19 pandemic. Additionally, there are
fewer economic risks related to the COVID-19
pandemic due to AI apps that target customers
online, provide cash flow predictions, and ease HR
operations. In light of the principle of dynamic
capabilities, SMEs may be able to improve their
capabilities through the use of AI. Through more
accurate market trend prediction and customer
requirement facilitation, AI in advertising might
enhance SMEs’ sensing capacities during
the COVID-19 pandemic. Furthermore, AI in risk
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
180
analysis and pricing might help SMEs take advantage
of opportunities via better-informed financial
planning, while AI in human resources (HR) could
help SMEs adapt through smart decision-making to
devise enhanced informed operational strategies.
Furthermore, Borges et al. (2021) assert that
the use of AI technology is increasingly common in
business settings. The potential, which has been
demonstrated in reports from leading consultancies,
technical businesses, and white papers, is in part
responsible for this enthusiasm. High expectations
are thus linked to the business environment’s
competitiveness. Thus, there is an increasing need
for research on the strategic application of AI
to achieve competitive advantages. Therefore,
the purpose of the study by Borges et al. (2021) was
to conduct a thorough literature analysis to evaluate
the relationship between the use of AI and corporate
strategy. The study results a show that using AI can
help SMEs enhance their customer and employee
engagement. Smart systems based on AI can
automate various processes like communication
with customers, enhancing their experience and
positively impacting organizational performance.
Also, it has been noted in the study that the use of
AI can help businesses design and test new products
and services more effectively. This reduces their
chances of failure in the market and ensures greater
success.
The study by Ghobakhloo and Ching (2019)
focuses on the adoption of digital technologies,
particularly smart manufacturing, in SMEs.
The authors aim to examine the challenges and
prospects of AI integration in this context. The study
is based on a systematic review of previous
literature and highlights the major challenges faced
by SMEs in adopting digital technologies and AI.
The results of the study show that the main
challenges faced by SMEs in adopting AI include
the high costs of implementation and technical
requirements. The authors claim that as AI
technology continues to advance and costs decrease,
AI integration will become more convenient and
accessible to SMEs. The study concludes by
emphasizing the importance of addressing
the challenges faced by SMEs in adopting AI and
highlights the need for further research to
understand better the potential benefits and
limitations of AI in SMEs.
Moreover, Ciampi et al. (2021) focused on using
AI to predict default in SMEs. The authors aim to
provide a systematic literature review of the current
state of AI in SME default prediction and highlight
future perspectives. The study reviews previous
literature to identify the major challenges faced by
SMEs in adopting AI for default prediction.
The results of the study show that the main
challenges faced by SMEs in adopting AI for default
prediction include a lack of data, a lack of expertise
in AI technology, and a lack of trust in AI
predictions. However, the study also defines the
future of AI integration in SME default prediction as
it states that AI technology will become more
available, accurate and reliable for SMEs in
predicting default. The study concludes by
emphasizing the need for further research to
understand better AI’s potential benefits and
limitations in SME default prediction.
Furthermore, Radanliev et al. (2020) examined
using AI to manage cyber risk in the industrial IoT
and Industry 4.0 supply chains. The authors aim to
provide an overview of the current state of AI in this
context and highlight future trends and prospects.
The study reviews previous literature to identify
the major challenges faced by organizations in
adopting AI for cyber risk management. The results
of the study show that the main challenges faced by
organizations in adopting AI for cyber risk
management include data privacy concerns, a lack of
trust in AI predictions, and the difficulty
of integrating AI technology into existing systems.
However, the study also highlights the future
prospects of AI integration in cyber risk
management. The authors note that as AI technology
continues to advance and more data becomes
available, AI will become more accurate and reliable
for organizations in managing cyber risk. The study
concludes by emphasizing the importance of
addressing the challenges faced by organizations in
adopting AI for cyber risk management and
highlights the need for further research to better
understand the potential benefits and limitations of
AI in this context.
The study by Türkeş et al. (2019) analyzed how
Romanian SMEs are implementing Industry 4.0
technologies, including AI. The authors want to
pinpoint the major factors influencing and impeding
SMEs’ adoption of Industry 4.0 technology while also
shedding light on the potential applications of AI
integration in the future. The research surveyed
SMEs in Romania to obtain information on
the difficulties and opportunities of AI integration.
On the other hand, exorbitant prices, a lack of
assistance from the government and financial
institutions, and a lack of skill and understanding of
Industry 4.0 technology are the key impediments to
its implementation. The survey also emphasizes
Romanian SMEs’ potential use of AI in the future.
The authors point out that SMEs in Romania will find
it easier and more practical to use AI as
the technology develops and more assistance
becomes available. The study’s findings indicate that
enhanced product quality, higher productivity, and
increased competitiveness are the primary forces
behind Industry 4.0 adoption by SMEs in Romania.
Table 1 presents the major findings of this
study, gained through the literature review.
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
181
Table 1. Findings of challenges and prospects of AI integration
Author(s)
Methods
Challenges of AI integration
Prospects of AI integration
Hansen and Bøgh
(2021)
Literature survey
The costs and complexity of AI implementation
make it difficult for SMEs to integrate these
systems with their business functions.
The costs o f AI i mplementation are on the
decline as research and development in this
area are increasing. Also, the implementation
of machine learning and data analytics requires
less complexity and costs, which can be
the beginning point of integration for SMEs.
Onu and Mbohwa
(2021)
Qualitative study
using interviews
Technological challenges and complexities of
AI are highlighted to be the main challenge
that does not allow SMEs to in tegrate AI.
The authors believe that AI integration is also
perceived as a risky process by businesses.
The r ise of Industry 4.0 i s en abling the use of
AI t echnologies in various organizations as
the vendors of these technologies are
increasing. Also, an increase in
the technological capabilities of firms is
enhancing AI integration.
Baabdullah et al.
(2021)
Qualitative study
using interviews
The study presents that infrastructure and
awareness of AI are the main factors that
influence its integration in SMEs. The stu dy
also finds that technicalities are n ot a major
challenge for AI integration.
The auth ors assert that the future of AI
integration in SMEs is substantial as it offers
various benefits for organizations to enhance
their performance and accomplish business
goals.
Polas et al.
(2022)
Quantitative analysis
using survey-
questionnaire
The study makes an important assertion th at
the perceived usefulness and ease of use o f AI
have a significant influence on the adoption of
technology. This means that organizations that
are aware of the benefits of AI and its poten tial
find it more convenient to integrate AI into
their operations.
The study also finds that AI has the potential
to transform the financial and economic
standings of SMEs. However , this potential h as
not been fully explored yet. In the future, it is
likely th at more growth of AI will be
experienced in SMEs as th e integration of
technology will become easier.
Drydakis
(2022)
Meta-analysis
Costs and high requirements for te chnical
skills are the major ch allenges for SMEs in
integrating AI. The costs are majorly associated
with hardware and human resources. Also, as
AI is an emerging field, it i s difficult to find
people with the highest skills.
The study also asserts th at the rapid growth of
AI will benefit SMEs a s the availability of
resources will become easier and cheaper. Due
to this, the business would be able to integrate
AI more effectively and enhance its operations.
Hoikkala and Ojala
(2022)
Qualitative review-
based study
The authors of the study show the challenges
of the use of AI chat bots for inexperienced
businesses. The development of AI chatbots i s
very difficult for SMEs as they do not have the
proficiency to implement and maintain them.
The study support s that the rigorous trend of
research and development in AI will enhance
the i mplementation of AI technology in
the future by making it simpler.
Chan et al.
(2019)
Research survey
The authors highlight how the implementation
of AI is challenging due to the lack of t echnical
expertise of SMEs. Small organizations are
unaware of advanced technical skills and lack
the finances to hire professionals in this area.
The study also presents that there is
a development of simpler AI methods an d
approaches th at will cause the cost of
implementation to go down in the future.
Ghobakhloo and Ching
(2019)
Quantitative study
using a survey
questionnaire
Technical requirements, costs
Reducing costs, an d convenience w ith research
and development
Ciampi et al.
(2021)
Qualitative study
using systematic
review
Lack of data and expertise, legal and ethical
considerations
Improved data analysis and prediction,
increased efficiency
Radanliev et al.
(2020)
Qualitative review-
based study
Integration with legacy systems, data privacy
and security, lack of expertise
Advancements in cyber risk analytics,
increased efficiency and safety
Türkeș et al.
(2019)
Qualitative interview-
based study
Lack of expertise and knowledge, high costs,
and lack of support from government and
financial institutions
Increased accessibility and convenience with
advancements in technology, government and
financial support
Borges et al.
(2021)
Qualitative study
using systematic
review
The study finds that the use of AI i s becoming
prevalent in various organizations; however,
SMEs find it challenging to u se AI technology
due to their limited resources. SME s often look
for tri ed and tested solutions, and AI is
an emerging field that needs some time t o
become stable for business use.
The growth of AI in the past decade has been
substantial, which shows that the future of AI
in SMEs i s huge. More organizations will adopt
AI as they will find it more adequate to survive
in the increasing market competition.
5. DISCUSSION
5.1. Challenges to AI integration in SMEs
It has been noted in the study that there are various
challenges that SMEs face during the integration of
AI in their business functions. One of the major
challenges is that AI requires significant technical
expertise that is limited available in SMEs (Lu et al.,
2022; Polas et al., 2022). The technical skillset and
the infrastructure are not well-developed in these
organizations, which makes it challenging for them
to adopt AI. Due to this, a significant number of
SMEs also believe that the additional expertise
required makes AI integration a risky process, which
can potentially harm their business objectives. Due
to this, the status quo does not allow these
organizations to change and adopt the use of AI.
Moreover, the results also show that organizations
often hesitate to integrate AI due to the costs
involved (Hansen & Bøgh, 2021). There is
a perception that AI integration will cost
organizations a large amount of money, which is
true to some extent, but not all areas of AI are
costly. Examples of these include data analytics and
machine learning, which are demanding in terms of
expertise but are not hardware intensive. Therefore,
SMEs can adopt AI technologies that are inexpensive
and start their journey toward AI integration.
Besides this, it is also true that the status quo, which
largely comprises investors, management, and
shareholders, is not adequately aware of
the potential usefulness of AI (Drydakis, 2022).
There is a general perception that AI is exaggerated
and does not significantly benefit organizations.
This acts as another major challenge for SMEs to
integrate AI into their business. The results assert
that a change in this perception and making
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
182
organizations aware of the usefulness and ease of
use of AI can significantly pave the way for
enhanced AI integration.
5.2. Future prospects of AI integration
The results of the study also found that AI
integration has major benefits for SMEs.
Organizations are often looking for growth and
expansion, and AI can play a major role in helping
these organizations accomplish their goals
(Baabdullah et al., 2021). The use of AI has intruded
into various business areas like recruitment,
marketing, customer and employee engagement, and
sales. Considering the rapid growth of AI in
the business world, the future prospects of AI are
bright for SMEs. The awareness and knowledge
regarding AI are on the rise, which is helping
the business become more competitive. Thus, this is
a positive trend that will help convince the status
quo regarding AI integration (Borges et al., 2021).
Besides this, the costs of AI are also declining
gradually as more research and development are
being carried out in this area. In the future, it is
likely that AI will become more stable, and this will
lead to the development of completed solutions for
businesses to be employed effectively. This will
certainly reduce the efforts, time, and money
required by organizations to accomplish AI
integration and enhance their performance (Onu &
Mbohwa, 2021). Hence, based on these findings, it
can be asserted that AI integration will become more
convenient for SMEs in the future, enabling them to
excel in their performance and growth more
efficiently.
5.3. Managerial implications
The research presents important managerial
implications for the adoption of advanced
technologies, particularly AI and IoT, by SMEs.
The studies highlight the vast benefits of adopting
these technologies in terms of enhancing operations,
performance, and competitiveness. Hence, SMEs
should focus on implementing these technologies,
with machine-wise implementation being the first
step. Additionally, SMEs in developing nations must
develop their digital connection skills and capacity,
address the usage of standards for interoperability,
and find ways to improve governance to become
competitive globally. Moreover, the study indicates
that factors such as mindset, technological road
mapping, infrastructure, awareness, and governance
impact the acceptance and readiness of SMEs for AI
adoption. Therefore, SMEs must promote these
factors to enhance their acceptance of AI and benefit
from better growth and expansion.
The research’s findings also imply that views of
artificial intelligence’s usefulness and usability, as
well as its perceived simplicity of use, have
a positive and substantial influence on how widely
blockchain technology is adopted. Therefore, greater
understanding of the usability and benefits of AI can
significantly increase the use of blockchain
technology in SMEs. Finally, it is also indicated that
the usage of AI in SMEs can have a favourable impact
on reducing the business risks brought on by
the COVID-19 pandemic. Therefore, SMEs should
consider adopting AI apps that target customers
online and implement AI technology to enhance
marketing and sales, pricing, and cash flow activities
to reduce business risks during pandemics and
other uncertain times. Overall, these studies
highlight the importance of SMEs adopting advanced
technologies such as AI and IoT to enhance their
operational performance and competitiveness in
the business world.
6. CONCLUSION
In the end, it can be concluded that AI integration
has great potential for SMEs as it can help them
accomplish their goals. AI has proven to be a great
asset for various organizations, and rapid research
and development in the area is evidence that this
technology will transform businesses in the future.
Although there are some challenges of AI integration
for SMEs, which include costs and technical
complexities, they are likely to be mitigated with
more development. The high costs of integration of
AI make it highly problematic for SMEs to adopt
the technology. However, it has been noted that
there is increasing research and development in this
field, which would enhance the implementation of AI
in businesses. Therefore, it is likely that in
the future, AI will become more applicable all over
the business world as technology becomes more
available and advanced. This study has found that
the key challenges to the adoption of AI in SMEs are
their high costs and technical complexity. Thus,
more research is required in this area to pave
a smoother path for the adoption of AI in
organizations.
These technologies have enormous potential to
enhance the operational performance of SMEs,
especially in developing countries, and contribute to
sustainable production. The study provides evidence
that SMEs should consider adopting these advanced
technologies and highlight the factors that can
facilitate or hinder their adoption. For example,
the results emphasize the importance of mindset,
infrastructure, and awareness in promoting
the acceptance of AI in SMEs. However, there are
also some limitations of the research that should be
considered in future studies. It was noted during
this research that reliance on surveys or reviews
might not provide a complete understanding of
the factors that influence the adoption and
implementation of these technologies in SMEs.
Moreover, the studies mainly focused on
the adoption and implementation of these
technologies in SMEs but did not investigate their
impact on the wider economy or society. Therefore,
future research should aim to overcome these
limitations and provide a more comprehensive
understanding of the adoption and implementation
of AI, IoT, and BT in SMEs. This may involve using
more diverse research methods, including case
studies and experimental designs, and investigating
the broader implications of these technologies on
the economy and society. Additionally, future
research should also consider the ethical and social
implications of these technologies and how SMEs
can ensure that their adoption and implementation
align with broader societal values and goals.
Journal of Governance and Regulation / Volume 12, Issue 2, 2023
183
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