A comparative examination of perceptions of artificial intelligence’s role in small businesses

Alainati, S.; Al-Hunaiyyan, A.; S. Senathirajah, A.R.; Haque, R.

doi:10.22034/IJHCUM.2026.02.04

A comparative examination of perceptions of artificial intelligence’s role in small businesses

https://doi.org/10.22034/IJHCUM.2026.02.04

Articles in Press, Accepted Manuscript
Available Online from 31 August 2025

International Journal of Human Capital in Urban Management

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

S. Alainati ¹

A. Al-Hunaiyyan ²

A.R. S. Senathirajah ³

R. Haque ⁴

¹ Management Department, College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait.

² Computing Department, College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait.

³ Business and Communication, INTI International University, Nilai, Malaysia

⁴ Business, Accounting, Finance, Law & Humanity (FOBAFLH), MAHSA University, Bandar Saujana Putra, Malaysia.

Abstract

BACKGROUND AND OBJECTIVES: As artificial intelligence increasingly transforms business potential, its adoption in small businesses has become a growing interest. This study explores college students’ perceptions of artificial intelligence in the context of small businesses, comparing insights from Kuwait and Malaysia. With small businesses playing a pivotal role in the economic growth of both countries, understanding how future employees perceive artificial intelligence can provide valuable guidance for educators, entrepreneurs, and policymakers. The research aims to investigate key factors such as artificial intelligence awareness, perceived benefits and challenges, willingness to adopt artificial intelligence technologies, and the perceived effectiveness of artificial intelligence in improving business operations. In addition, a bibliometric analysis was conducted to compare the research trends and national emphasis on artificial intelligence in business within the two countries.
METHODS: A quantitative research approach was employed using a structured survey distributed to a total of 834 university students from Kuwait and Malaysia. The survey collected data on various dimensions, including artificial intelligence awareness, perceived utility, anticipated challenges, and readiness to engage with artificial intelligence in small business settings. The data were statistically analyzed to determine significant differences and similarities across the two national contexts. Also, a bibliometric analysis was carried out to explore the scholarly output and collaboration trends related to artificial intelligence and business in both countries.
FINDINGS: Statistical analysis of the survey data from 834 students (433 from Malaysia and 401 from Kuwait) revealed high mean scores across all constructs, ranging from 3.90 to 4.08 on a 5-point Likert scale, indicating overall positive perceptions of AI’s role in small businesses. Independent-samples t-tests showed no significant differences (p > 0.05) between the two countries regarding AI awareness, perceived benefits, anticipated challenges, willingness to adopt AI, and perceived impact on SMEs. Reliability coefficients (Cronbach’s α) for the constructs ranged from 0.73 to 0.86, confirming internal consistency. Additionally, bibliometric analysis showed that Malaysia produced 105 relevant publications from 2010–2024, with 1,872 total citations, while Kuwait produced 10 publications from 2018–2024, with 234 citations. Despite fewer publications, Kuwait demonstrated higher average citations per paper (23.4 vs. 17.83), indicating a high-impact research contribution.
CONCLUSION: This study underscores the universal recognition of artificial intelligence's value in small businesses among young professionals in Kuwait and Malaysia. The findings highlight the need for context-sensitive policies, focused artificial intelligence education, and hands-on support mechanisms for small enterprises. Cross-cultural collaboration and targeted research initiatives are recommended to responsibly harness artificial intelligence’s potential and drive sustainable innovation in the small business sector.

Graphical Abstract

Keywords

Artificial Intelligence

Cross-National Study

SMEs

Student Perceptions

Sustainable Growth

Subjects

Information and communications technology in Urban Management

Ahmed, S. M., (2019). Artificial Intelligence in Saudi Arabia: Leveraging Entrepreneurship in the Arab Markets. 2019 Amity Int. Conf. Artif. Intell. (AICAI), Artificial Intelligence (AICAI), pp. 394–398 (5 pages)

Alainati, S.; Al-Hunaiyyan, A.; Alkhatib, H., (2023B). Instructors’ Digital Competencies for Innovative Learning: Human Resource Management Perspectives. Int. J. Prof. Bus. Rev., 8(10): e03750.

Albanay, M., (2024). Digital Transformation for Kuwaiti SMEs. Retrieved from Kuwait Mart.

Al-Doub, E.; Goodwin, R.; Al-Hunaiyyan, A., (2008). Students' Attitudes Toward E-learning in Kuwait's Higher Education Institution. Proc. 16th Int. Conf. Comput. Educ. (ICCE 2008). October 27-31, 2008: 27-31 (5 pages). Digital Transformation for Kuwaiti SMEs - Kuwait Mart Blog

Alhajri, R.; Al-Sharhan, S.; Al-Hunaiyyan, A.; Alothman, T., (2011). Design of educational multimedia interfaces: individual differences of learners. Proc. 2nd Kuwait Conf. e-Serv. e-Syst., 1-5 (5 Pages).

Al-Hunaiyyan, A.; Al-Sharhan, S., (2009). The Design of Multimedia blended e-learning Systems: Cultural Considerations. Proceeding of the 3rd Int. Conf. Signals, Circuits and Systems, November 6-8, 2009, 1-5 (5 pages).

Al-Hunaiyyan, A.; Al-Hajri, R.; Bimba, A. (2021). Towards an Efficient Integrated Distance and Blended earning Model: How to Minimise the Impact of COVID-19 on Education. Int. J. Interact. Mob. Technol. (iJIM)., 15(10): 173-192 (20 pages).

Al-Hunaiyyan, A.; Alhajri, R.; Al-Sharhan, S.; Al-Ghannam, B., (2021D). Factors Influencing the Acceptance and Adoption of Online Learning in Response to the COVID-19 Pandemic. Int. J. Web-Based Learn. Teach. Technol. (IJWLTT)., 16(6): 1-16 (16 pages).

Al-Hunaiyyan, A.; Alhajri, R.; Al-Sharhan, S.; Bimba, A., (2021C). Human-Computer Interaction Perspective on Mobile Learning: Gender and Social implications. Int. J. Interact. Mob. Technol. (iJIM)., 15(11): 4-20 (17 pages).

Al-Kandari, A.; Al-Sumait, F.; Al-Hunaiyyan, A., (2017). Looking perfect: Instagram use in a Kuwaiti cultural context. J. Int. Intercult. Commun., 10(4): 273-290 (18 pages).

Alkharafi, N.; Alsaber, A.; Alqatan, A.; Varghese, S.; Alainati, S.; Nafea, R.; Al Kandari, A., (2024). Comparison between sponsored and non-sponsored regarding personal administrative factors for SMEs from Kuwait during the COVID-19 pandemic. Humanit. Soc. Sci. Lett., 12(1): 117–132 (16 pages).

Almonawer, N.; Althonayan, A.; Alainati, S.; Al-Hammad, F.; Rasheedul Haque; Senathirajah, A., (2023). Transformational Leadership Style and School Transformation: The Case of Secondary Schools in Kuwait. Int. J. Oper. Quant. Manag., 29(1): 51–67 (17 pages).

Al-Sharhan, S.; Al-Hunaiyyan, A., (2012). Towards an effective integrated e-learning system: Implementation, quality assurance and competency models. In Digital information management (icdim). Seventh International Conference, Macau. 274–279 (6 pages)

Al-Sharhan, S.; Al-Hunaiyyan, A.; Gueaieb, W., (2006). Success Factors for an Efficient Blended eLearning. Proceeding of the 10th IASTED Internet and Multimedia Systems and Applications (IMSA 2006) Conference. 14/8/2006 - 16/8/2006. Honolulu, Hawaii, USA.: ACTA Press., 77-82 (6 pages).

Alzayed, A.; Al-Hunaiyyan, A., (2021). A Bird’s Eye View of Natural Language Processing and Requirements Engineering. Int. J. Adv. Comput. Sci. Appl. (IJACSA). 12(5): 81-90 (10 pages).

Baabdullah, A.; Alalwan, A.; Slade, E.; Raman, R.; Khatantneh, K. (2021). SMEs and artificial intelligence (AI): Antecedents and consequences of AI-based B2B practices. Ind. Mark. Manag., 98: 255-270 (16 pages).

Bhattacharya, Prithvi., (2020). Guarding the Intelligent Enterprise: Securing Artificial Intelligence in Making Business Decisions., 235-238 (4 pages).

Boucher, S.; Cullen, M.; Calitz, A., (2022). SMEs' Perceptions of the Use of AI and Cobots. Conference:. IBC Conf., 25-27 (3 pages).

Campbell, C.; Sands, S.; Ferraro, C.; Tsao, H.; Mavrommatis, A., (2020). From data to action: How marketers can leverage AI. Bus. Horiz., 63(2): 227-243 (17 pages).

Chalmers, D.; MacKenzie, N.; Carter, S., (2020). Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution. Entrepr. Theory Pract., 45(5): 1028-1053 (26 pages).

Chatterjee, S.; Kar, A., (2020). Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India. Int. J. Inf. Manag. Volume 53, 2020, 102103, ISSN 0268-4012.

Chowdhury, S.; Dey, P.; Joel-Edgar, S.; Bhattacharya, S.; Rodriguez-Espindola; O., Abadie, A.; Truong, L. (2022). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Hum. Resour. Manag. Rev. 33(1): 100899.

Crockett, K.; Colyer, E.; Gerber, L.; Latham, A., (2023). Building Trustworthy AI Solutions: A Case for Practical Solutions for Small Businesses. IEEE Trans. Artif. Intell., 4(4): 778-791 (14 pages).

Davenport, T.; Ronanki, R., (2018). Artificial Intelligence for the Real World. Harv. Bus. Rev., 96(1): 108-116 (9 pages).

Enholm, I.; Papagiannidis, E.; Mikalef, P.; Krogsite, J., (2021). Artificial Intelligence and Business Value: a Literature Review. Inf. Syst. Front. (2022) 24: 1709-1734 (26 pages).

Francis, U. O.; Rasheedul Haque, Senathirajah, A.; Al-Hunaiyyan, A.; Alainati, S.; Farha Zafira Agos Lokman; Majid Bin Md. Isa. (2023). The Impact of Digital Marketing on Consumer Purchasing Behaviour. Int. J. Oper. Quant. Manag., 29P 378-405 (28 pages).

Giuggioli, G.; Pellegrini, M. (2023). Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research. Int. J. Entrepr. Behav. Res., 29(4): 816-837 (22 pages).

Haenlein, M.; Kaplan, A., (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. Calif. Manag. Rev., 61(4): 5–14 (10 pages).