(RM) Uday Shankar Verma
(RM) Uday Shankar Verma
(RM) Uday Shankar Verma
Abstract
Just about two decade ago from now smart phones, laptops, digitalization, online
marketing, and voice based virtual assistants like Alexa and Google Home were not part
of the lives. Inclusion of Big Data and AI have significantly changed the situation. Now,
more than half of the people on planet earth have access to handheld devices that possess
more computing power than the space stations had in the early twentieth century. The
speed of transformation continues to pick up even at the faster pace. Technological
enhancement has led to the emergence of a new society that must adapt to changes. New
technologies have a great extent of social, economic, political and environmental
implications. Artificial Intelligence in particular started to shape our homes, businesses,
policies, governments and environment. Artificial intelligence, synonym with machine
intelligence, is a disruptive emerging technology with the potential to transform the
business in terms of new production, novel business practices and marketing strategies,
Research objectives
Literature review
With the potential to transform the business, AI is paving its way to SMEs at a
slower pace. Using qualitative analysis Nugroho et al. (2017) reported pressure from the
customer and ease of use as the motivating factor in AI adoption by SMEs in Yogyakarta,
Indonesia. However, there are barriers in the adoption of AI at multiple levels. Aarstad
and Saidl (2019) listed about 20 significant barriers from the organizational,
technological and environmental context in the adoption of AI by Nordic SMEs.
According to Watney and Auer (2021), integration of AI in SMEs demands large financial
investment in IT systems as well as hiring of technical talent which can be a costly affair
for small businesses. Nevertheless, there are multiple advantages of AI in SMEs. AI tools
can aid in competitive analysis to identify the strength and weakness of the competitors,
aid in managing marketing, build customer relationship management and sales
discussions with consumers. Especially in manufacturing sector SMEs, the use of AI has
boosted productivity. In a review of 37 publications with a main focus on manufacturing
SMEs, it was observed that AI and internet of things (IoT) supported analytic capabilities
like descriptive, diagnostic, predictive and prescriptive analytics (Hansen & Bøgh, 2021).
In literature there was limited empirical research on the knowledge of key drivers of AI
adoption in SMEs.
It is gathered from the literature that AI can benefit the organization manifold. In this
context, it can be inferred that SMEs can also gain from the AI by using their general AI tools
as a service platform. However, SMEs have several limitations like poor financial resources,
lack of skilled workers, hesitation to adopt advanced technology, government policies, etc.
Hence it is essential to explore the influence of factors from the context of organization,
technology and environment in the adoption of AI by SMEs. The focus of the present research
was to identify the factors that influences the preparedness of the Thai service sector SMEs to
adopt AI technologies.
Marketing mix
Marketing mix constitutes 4Ps, namely, products, price, promotion and place based on
which the marketers configure the offerings to suit customers' needs (Singh, 2012). Londhe
(2014) proposed 4Vs marketing mix model for the modern business which emphasizes valued
customers, value to the customer, value to the society and value to the marketer. According to
this, besides catering to the customer needs, for the marketer, the tangible and intangible
benefits associated with the products and services help to create a brand image/value which is
essential for survival in the competitive world. SMEs managers from Bolgatanga Municipality,
Ghana felt that adoption of marketing mix is limited due to lack of marketing knowledge and
their costly affair. Further, an already well-established customer base can limit the use of
marketing mix. The study has an implication for managers to establish the marketing mix not
for just short-term goals like improved sales but for long-term goals to develop the enterprise
Organizational context
Organization context refers to the number of employees, ownership, skilled personnel,
competitiveness, revenue, management support, etc. The characteristics of entrepreneur and
organization are important for the growth and development of small companies. An early study
on SME entrepreneurship indicated that resources and competitive strategy of the personnel
are more crucial for the SME entrepreneurs. In the present study, organizational context was
addressed using three items, namely, leadership level adoption, individual level adoption and
system openness. The level of adoption by leaders and employees had a higher influence than
system openness. In the implementation of AI in manufacturing SMEs, Truvé et al. (2019)
explored existing technical skills, readiness to direct adequate funds and the top management
support as the components of organizational context. Savola et al. (2018) included existing firm
size, technical skills, customer knowledge management, financial resources, top management
support, culture and ethical aspects as the main items for exploring the AI adoption in SMEs.
Jadhav (2021) found that enhanced IT sophistication and management support played a
significant role in effective AI adoption. Similarly, Ifinedo (2011) reported influence of
management support on adoption of internet and e-business technologies (IEBT) by Canadian
SMEs. According to the author, if top management employees extend their support in the
adoption of technology, then organizations as well as individual employees will consider it as
a priority for the project. The adoption of AI in government authorities was influenced by
management support and staff capacity. According to the author, skill and knowledge of an
individual as well as the support in the form of training will support the adoption of AI
(Stenberg & Nilsson, 2020). Aarstad and Saidl (2019) reported a multitude of organizational
barriers in the adoption of AI in European SMEs. Organizational factors like lack of prior AI
experience, resistance to change, employee’s age, lack of training, lack of AI competence,
financial and resources constraints, sceptical about AI trends, poor business strategies are likely
to hinder AI adoption in SMEs.
Environmental context
In the present study, in the context of environmental factors, namely three variables,
government regulations, industry characteristics and vendor partnership were evaluated. The
influence of environmental context in the adoption of AI in Thai SMEs was not highly
significant. In this study, the respondent’s response to government support for the AI adoption
in SME was found to be neutral. On the contrary, use of AI by peers of the industry and
additionally, SMEs tie up with relevant vendors for AI support. In agreement with the present
findings, Truvé et al. (2019) found that in manufacturing SMEs, competition threat, pressure
from other industries and customer expectation were not the antecedents of AI adoption. It was
likely that SMEs had not integrated AI into the manufacturing sector. Savola et al. (2018)
proposed perceived competitive pressure, legislation and media attention, and pressure from
customers as the environmental factors in the adoption of AI in marketing management system.
According to Jadhav (2021) among the three variables, mimetic and normative pressure not
regulatory pressure for SME leaders influences AI adoption in Indian SMEs. Environmental
factors such as dependence on external aid, higher price of an AI solution, in case of failure of
technology, higher risk of losing reputation and customer base are the likely reasons for lack
of AI adoption in SMEs. (Aarstad & Saidl, 2019). Ifinedo (2011) found that the Canadian
government did not extend the support to internet adoption in SMEs. Similarly, partner pressure
or customer pressure did not exert any influence on internet adoption. Nevertheless,
Research methodology
For this research technology-organization-environment (TOE) framework was adopted
to understand the preparedness of Thai SMEs in the adoption of AI. The three key elements of
TOE, namely, technological context, organization context and environmental context gives an
insight to the influence of these contexts in the process of innovation, adoption and
implementation of technology on an organization level (Baker, 2012). TOE framework alone
Res Militaris, vol.13, n°1, Winter-Spring 2023 528
or in integration with other theories like diffusion of innovation theory (DOI) and Institutional
Theory (INT) has been used in many empirical works related to adoption of technology,
namely, ICT in multiple discipline including SMEs (Alsheibani et al., 2018; Truvé et al., 2019;
Sastararuji et al., 2021). However, studies related to AI adoption by SME using the TOE
framework were found to be limited in literature. To further explore the importance of
marketing strategies, another component, namely, marketing mix was integrated into this
framework.
Demographics
Out of 320 respondents, 59.4% (190/320) of respondents were female and the
remaining was male. About 70% (226/320) of respondents were in the age range of 31-50 years
and with Bachelor’s (149/320; 46.6%) and Master’s degree (127/320; 39.7%). In the context
of occupation, the participants were mainly employed as business owner/senior
executive/managing director (105/320, 32.8%) and earned an income of more than 5,000,001
Baht (50.1%).
Research results
The main aim of this study was to explore the influence of organizational context in the
preparedness of SME in the adoption of AI. Large enterprises are already reaping the benefits
of AI; however, there has been a considerable lack of adoption of AI in small and medium
industries. Since SMEs are the economic backbone of many developing countries including
Thailand, the present study is an attempt to identify the factors essential for the adoption of AI
in SMEs. The findings of present study indicated a significant relationship between
organizational context and the preparedness of SME in the adoption of AI. Further, this relation
partially mediated the marketing mix.
• Looking at the technological context, participants were seen to largely agree that tech
competence, relative advantage, and ease of use supports of AI-related marketing.
Res Militaris, vol.13, n°1, Winter-Spring 2023 529
• The implication of this finding is that technological competence needs to be boosted
through large scale training programs.
• The managements need to constantly ensure that AI-related supplies and equipment are
easily accessible to the employees to enable smoother adoption.
• Looking at the organizational context, leadership and individual level of adoption, and
system openness to accept new challenges were affirmed by the majority of the
respondents.
• This implies the need for ensuring clear leadership and vision to overcome marketing
challenges arising through AI. Organizations must very explicitly spell out their
policies which must percolate throughout the organizations.
• Further, the need for having communication plans in place to make everyone aware in
the company on how to use AI in marketing is key. Managements have to be open to
accept new challenges and promote adoption of new technologies relevant to AI in
marketing.
Recommendations
1. As SMEs have limited resources, they could initially adopt AI adoption on a small
scale, followed by a slow expansion of technology.
2. Before investing in the AI tools, SMEs must evaluate both negative factors like data
security concern, task complexity, PDPA, etc.
3. Prior to AI adoption, data should be consolidated, followed by identification of the AI
tool required for the processing of collected data as AI is data driven.
4. AI integration can be used to resolve administrative issues like HR, accounting, finance
and internal communication.
5. Sales, being crucial to SMEs, necessitates training of salesperson in different aspects of
AI.
6. Top management with leadership qualities should be the first and foremost to accept
the importance of technology.
7. Massive company-wide training to work alongside digital tools, on digital skills,
fluency in data skills, etc. is suggested.
8. Talent acquisition involving sorting, selecting and hiring of talented individuals must
be brought under the AI ambit.
9. Further, AI implementation will overcome the tedious work and enable allocation of
human resources for more meaningful work.
10. As there is a fear of job loss, monitoring of workers' behaviour is necessary. The
workforce needs to be educated regarding the benefits of technological skills.
11. Considering that AI technology has potential in many key areas, to make an informed
decision about AI adoption, AI advisory committees must be created.
12. In Thai industry, the SME sector majorly contributes to GDP and employment.
Therefore, suitable policies on AI adoption to enhance the sustainable development of
SME must be worked on with government encouragement.
13. Since SMEs are crucial for Thai economy, public and private partnership must be
encouraged. To boost economic development, the government must increase the
financial investment in AI technology.
14. Regulatory bodies must oversee the maintenance of confidentiality and privacy of
customer data.
15. Integrated AI tools can predict the requirements for the marketing. New market models
must be created to promote the new products/pricing.
16. AI integration can help in the automation of non-routine tasks and re-organize the work
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schedule (e.g., use of chatbot / voicebot to enhance communication with consumers).
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