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Vol. 8 No. 1 (2026): August

Does Artificial Intelligence Democratisation Enhance Small Business Operations in Emerging Economies?

https://doi.org/10.35912/amor.v8.n1.p125-142.2026

Abstract

Purpose: This study examines the concept of Artificial Intelligence (AI) democratization and its relevance to Small and Medium-Sized Enterprises (SMEs), particularly in emerging economies.
Methodology: This study adopted a conceptual and exploratory approach and synthesized the extant literature on AI adoption, digital transformation, and small business performance.
Results: The study findings revealed that democratizing AI enhances SMEs’ operational efficiency, strategic decision-making, customer relationship management, and innovation capabilities by lowering barriers to entry through cloud-based and low-code solutions. Furthermore, the findings show that technology giants, governments, academic institutions, and internal organizational actors play critical roles in facilitating AI accessibility and adoption in the healthcare sector. Additionally, platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are instrumental in providing scalable and affordable AI solutions for small enterprises.
Conclusions: The study concluded that AI democratization is a crucial pathway for enabling SMEs to compete effectively in the digital economy and achieve sustainable growth.
Limitations: This study is limited by its conceptual and exploratory nature, as it relies exclusively on the existing literature rather than primary empirical evidence.
Contributions: This study contributes to the growing body of knowledge on AI by extending the discourse on AI democratization to the context of SMEs. This study further identifies the critical stakeholders and cloud-based platforms that facilitate AI accessibility for SMEs, thereby offering a structured reference for researchers, policymakers, and business practitioners seeking to promote inclusive AI adoption, particularly in emerging economies.

Keywords

Artificial Intelligence Democratization Cloud Platforms Customer Relationship Management Predictive Analytics Process Automation Small Business Operations

How to Cite

Chinwendu, W. S., Arachie, A. E., Okeke, . O. I. ., & Chiedozie, F. C. (2026). Does Artificial Intelligence Democratisation Enhance Small Business Operations in Emerging Economies?. Annals of Management and Organization Research, 8(1), 125–142. https://doi.org/10.35912/amor.v8.n1.p125-142.2026

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References

  1. Adesina, A. A., Iyelolu, T. V., & Paul, P. O. (2024). Leveraging predictive analytics for strategic decision-making: Enhancing business performance through data-driven insights. World Journal of Advanced Research and Reviews, 22(3), 1927-1934. https://doi.org/10.30574/wjarr.2024.22.3.1961
  2. African Union & UNESCO. (2024). Continental artificial intelligence strategy: Harnessing AI for Africa’s development. African Union Commission. Retrieved from https://au.int/en/documents/20240715/continental-ai-strategy
  3. Ahmed, N., & Wahed, M. (2020). The de-democratization of AI: Deep learning and the compute divide in artificial intelligence research. arXiv preprint, 1-52. https://doi.org/10.48550/arXiv.2010.15581
  4. Arachie, A. E., Dibua, E., & Idigo, P. (2023). Artificial intelligence as a catalyst for the sustainability of small and medium scale businesses (SMEs) in Nigeria. Annals of Management and Organization Research, 5(1), 1-11. https://doi.org/10.35912/amor.v5i1.1719
  5. Arachie, A. E., Nwosu, K. C., Ugwuanyi, S. C., & Muhammed, A. I. (2025). Artificial intelligence adoption and business performance: Evidence from small and medium enterprises in emerging markets. International Journal of Public Administration and Management Research, 11(2), 69-86.
  6. Arachie, A. E., Nzewi, H. N., Emejulu, G., & Kekeocha, M. E. (2020). Digital literacy in a post-Coronavirus era: A management perspective for small businesses in Africa. Annals of Management and Organisation Research, 1(3), 203-212. https://doi.org/10.35912/amor.v1i3.410
  7. Arachie, A. E., Okwudiri, N. O., Anagwu, V. K., & Okeke, N. C. (2025). Assessing the technological readiness of small businesses for Artificial Intelligence-powered transformation: A West African context. African Journal of Management and Business Research, 20(1), 137-156. https://doi.org/10.62154/ajmbr.2025.020.01018
  8. Atta, S. R., & Bandapati, G. (2025). Democratizing AI across your organization using cloud - AWS, Azure, and GCP. International Journal of Computer Trends and Technology, 73(5), 7-13. https://doi.org/10.14445/22312803/IJCTT-V73I5P102
  9. Awasthi, A. (2024). Democratizing AI: How AutoML is transforming business operations. International Journal on Science and Technology (IJSAT), 16(1), 1-11. https://doi.org/10.71097/IJSAT.v16.i1.2659
  10. Azizi, O. (2011). AI-as-a-service: The democratization of automated intelligence through cloud computing. https://doi.org/10.13140/RG.2.2.17889.42089
  11. Basri, W. (2020). Examining the impact of artificial intelligence-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), 142-152. https://doi.org/10.2991/ijcis.d.200127.002
  12. Benedicta, U. C., Ebele, N. A., Ebuka, A. A., & Paulin, I. A. (2025). Digital literacy in the context of small and medium enterprises (SMEs): A performance dynamics. International Journal of Public Administration and Management Research, 11(1), 1-17.
  13. Birhane, A., Isaac, W., Prabhakaran, V., Diaz, M., Elish, M. C., Gabriel, I., & Mohamed, S. (2022). Power to the people? Opportunities and challenges for participatory AI. Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, 1-8. https://doi.org/10.1145/3551624.3555290
  14. Chan, C. M., Teoh, S. Y., Yeow, A., & Pan, G. (2019). Agility in responding to disruptive digital innovation: Case study of an SME. Information Systems Journal, 29(2), 436-455. https://doi.org/10.1111/isj.12215
  15. Chui, C., Manyika, J., Miremadi, M., Henke, N., Chung, R., Nel, P., & Malhotra, S. (2018). Notes from the AI frontier: Applications and value of deep learning. Chicago: McKinsey & Company.
  16. Costa, C. J., Aparicio, M., Aparicio, S., & Aparicio, J. T. (2024). The democratization of artificial intelligence: Theoretical framework. Applied Sciences, 14(18), 1-14. https://doi.org/10.3390/app14188236
  17. Cupać, J., Schopmans, H., & Tuncer-Ebetürk, İ. (2024). Democratization in the age of artificial intelligence: Introduction to the special issue. Democratization, 31(5), 899-921. https://doi.org/10.1080/13510347.2024.2338852
  18. Finley, T. (2019). The democratization of artificial intelligence: One library’s approach. Information Technology and Libraries, 38(1), 8-13. https://doi.org/10.6017/ital.v38i1.10974
  19. Friday, E. C., Onah, F. S., Onwudinjor, E. C., & Ezenwoke, M. L. (2024). Office automation and performance of small and medium scale enterprises in Anambra State, Nigeria. Journal of Public Administration, Policy and Governance Research, 2(4), 156-173.
  20. Hasbe, S., & Lippert, R. (2020). Democratization of machine learning and artificial intelligence with Google Cloud. Google Cloud Blog. Retrieved from https://cloud.google.com/blog/products/data-analytics/democratization-of-ml-and-ai-with-google-cloud
  21. Idris, M. M., Mustafa, M. Y., & Arief Putra, M. F. (2025). Entrepreneurship knowledge and vocational policy's effect on MSMEs business strategy: Artificial intelligence moderation analysis. Reviu Akuntansi, Manajemen, dan Bisnis, 5(2), 579-591. https://doi.org/10.35912/rambis.v5i2.6336
  22. Islam, M. M., Desai, K., Rabbani, M. M., Ahmad, S., & Snigdha, E. Z. (2025). AI-powered business intelligence in IT: Transforming data into strategic solutions for enhanced decision-making. The American Journal of Engineering and Technology, 7(2), 59-73. https://doi.org/10.37547/tajet/Volume07Issue02-09
  23. Jabłońska, M. R., & Pólkowski, Z. (2017). Artificial intelligence-based processes in SMEs. Studies & Proceedings of Polish Association for Knowledge Management, 86.
  24. Jain, A., Kakade, K. S., & Vispute, S. A. (2025). The role of Artificial Intelligence (AI) in the transformation of small and medium-sized businesses: Challenges and opportunities. Artificial Intelligence-Enabled Businesses: How to Develop Strategies for Innovation, 209-226. https://doi.org/10.1002/9781394234028.ch12
  25. Kaddoumi, T., & Tambo, T. (2022). Democratizing enterprise AI success factors and challenges: A systematic literature review and a proposed framework. Information Systems, 640-652. https://doi.org/10.1007/978-3-030-95947-0_45
  26. Kalia, A. (2025). Democratizing enterprise content management: Low-code architectures for workflow innovation in post-digital organizations. Journal of Computer Science and Technology Studies, 7(5), 307-313. https://doi.org/10.32996/jcsts.2025.7.5.38
  27. Kshetri, N., Rojas-Torres, D., Hanafi, M. M., Al-Kfairy, M., O'Keefe, G., & Feeney, N. (2024). Harnessing generative artificial intelligence: A game-changer for small and medium enterprises. IT Professional, 26(6), 84-89. https://doi.org/10.1109/MITP.2024.3501552
  28. Kumar, A., & Kalse, A. (2021). Usage and adoption of artificial intelligence in SMEs. Materials Today Proceedings. https://doi.org/10.1016/j.matpr.2021.01.595
  29. Kuzmanov, I. (2024). Reform the Ivory Tower: AI and the democratization of higher education. Journal of New Research in Innovation and Design.
  30. Lin, T. (2024). “Democratizing AI” and the concern of algorithmic injustice. Philosophy & Technology, 37. https://doi.org/10.1007/s13347-024-00792-2
  31. Maslej, N., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Parli, V., Shoham, Y., Clark, J., & Perrault, R. (2023). Artificial Intelligence Index Report 2023. Stanford: Stanford University.
  32. Montes, G. A., & Goertzel, B. (2019). Distributed, decentralized, and democratized artificial intelligence. Technological Forecasting and Social Change, 141, 354–358. https://doi.org/10.1016/j.techfore.2018.11.010
  33. Moreau, E., Vogel, C., & Barry, M. (2019). A paradigm for democratizing artificial intelligence research. Innovations in Big Data Mining and Embedded Knowledge, 137–166. https://doi.org/10.1007/978-3-030-15939-9_8
  34. Nemitz, P. (2018). Constitutional democracy and technology in the age of artificial intelligence. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376, 1-14. https://doi.org/10.1098/rsta.2018.0089
  35. NMI. (2021). People have the AI power. Nature Machine Intelligence, 3, 275. https://doi.org/10.1038/s42256-021-00340-z
  36. Nnanna-Ohuonu, O., Chikwesiri, N. P., Okudo, A., & Chinwe, I. V. (2026). Artificial intelligence personalized marketing content and consumer behavior in Nigerian SMEs. Annals of Management and Organization Research, 7(3), 325-339. https://doi.org/10.35912/amor.v7i3.3418
  37. Nwabuike, C. C., Onodugo, V. A., Arachie, A., & Nkwunonwo, U. C. (2020). Blockchain technology for cyber security: Performance implications on emerging markets multinational corporations, overview of Nigerian internationalised banks. International Journal of Scientific & Technology Research, 9(8), 244-252.
  38. Nwosu, K. C., Westcott, S. C., Arachie, A. E., and Okafor, N. M. (2026). Artificial Intelligence Democratization in Developing Economies through the Lenses of Small Business Operations. African Journal of Management and Business Research, 22(1), 242-255. https://doi.org/10.62154/ajmbr.2026.022.01022
  39. Ocran, G., Yusuf, S. O., Owusu, P., Boateng, E. A., & Obeng, S. (2024). AI-driven business analytics for SMEs: Unlocking value through predictive and prescriptive analytic. International Journal of Science and Research, 13(1), 3009-3022. https://doi.org/10.30574/ijsra.2024.13.1.2001
  40. Okereke, C. C., Arachie, A. E., Onah, F. S., & Ndum, N. B. (2025). Artificial Intelligence (AI) adoption in supply chain management dynamics of manufacturing firms in emerging markets. African Journal of Management and Business Research, 21(1), 129-147. https://doi.org/10.62154/ajmbr.2025.021.01017
  41. Okwudiri, N. O., Nwosu, C. K., Arachie, A. E., Ndum, N. B., & Ibrahim, A. M. (2025). Digital disruption in the marketing landscape of small businesses: A strategic pathway to success. International Journal of Science and Research Archive, 16(2), 1034-1042. https://doi.org/10.30574/ijsra.2025.16.2.2420
  42. Okwudiri, N., Arachie, A. E., Elechi, S. J., & Egede, F. N. (2025). Effect of digital marketing adoption on the sustainable growth of small and medium enterprises (SMEs): Evidence from Nigeria. Corporate Sustainable Management Journal (CSMJ), 3(2), 38-44. https://doi.org/10.26480/csmj.02.2025.38.44
  43. Okwudiri, N.-O., Oliseh, P. S., Anagwu, V. K., Nwanya, C. C., & Chukwu, C. (2025). Technology adoption and social media marketing performance of small and medium enterprises. Annals of Management and Organization Research, 7(1), 127-140. https://doi.org/10.35912/amor.v7i1.3369
  44. Olan, F., Arakpogun, E., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organisational performance. Journal of Business Research, 145, 605–615. https://doi.org/10.1016/j.jbusres.2022.03.008
  45. Ragnedda, M., & Muschert, G. W. (2013). The Digital Divide: The Internet and Social Inequality in International Perspective. New York: Routledge.
  46. Rahwan, I. (2018). Society-in-the-loop: Programming the algorithmic social contract. Ethics and Information Technology, 20, 5-14. https://doi.org/10.1007/s10676-017-9430-8
  47. Rall, D., Fraunholz, T., & Bauer, B. (2023). AI-democratization: From data-first to human-first AI. Central European Conference on Information and Intelligent Systems, 261-267.
  48. Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). New York: The Free Press.
  49. Rubeis, G., Dubbala, K., & Metzler, I. (2022). “Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term. Frontiers in Genetics, 13, 1-11. https://doi.org/10.3389/fgene.2022.902542
  50. Sarioguz, O., & Miser, E. (2024). Artificial intelligence and participatory leadership: The role of technological transformation in business management and its impact on employee participation. International Research Journal of Modernization in Engineering Technology and Science, 6(2), 1618-1633. https://doi.org/10.56726/IRJMETS49539
  51. Seger, E., Ovadya, A., Garfinkel, B., Siddarth, D., & Dafoe, A. (2023). Democratising AI: Multiple meanings, goals, and methods. Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 715-722. https://doi.org/10.1145/3600211.3604693
  52. Shamkura, S. (2025). The transformative role of cloud computing in democratizing AI development. Journal of Computer Science and Technology Studies, 7(6), 1008-1013. https://doi.org/10.32996/jcsts.2025.7.119
  53. Shankar, V. (2018). How artificial intelligence (AI) is reshaping retailing. Journal of Retailing, 94(4). https://doi.org/10.1016/s0022-4359(18)30076-9
  54. Shen, L. (2017). Former U.S. CTO: The ‘Robot Apocalypse’ Could Happen. Here’s How You Stop It. Fortune. Retrieved from https://fortune.com/2017/11/14/megan-smith-cto-robot-apocalypse-elon-musk/
  55. Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
  56. Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2020). Artificial intelligence in business: From research and innovation to market deployment. Procedia Computer Science, 167, 2200–2210. https://doi.org/10.1016/j.procs.2020.03.272
  57. Torraco, R. J. (2016). Writing integrative reviews of the literature: Methods and purposes. International Journal of Adult Vocational Education and Technology (IJAVET), 7(3), 62-70. https://doi.org/10.4018/IJAVET.2016070106
  58. Ulas, D. (2019). Digital transformation process and SMEs. Procedia Computer Science, 158, 662–671. https://doi.org/10.1016/j.procs.2019.09.101
  59. Ulrich, Frank, & Kratt, 2021: Ulrich, P., Frank, V., & Kratt, M. (2021). Adoption of artificial intelligence technologies in German SMEs: Results from an empirical study. PACIS 2021 Proceedings, 189, 1-8.
  60. Umana, A. U., Garba, B. M. P., & Audu, A. J. (2024). Innovations in process optimization for environmental sustainability in emerging markets. International Journal of Multidisciplinary Research Updates, 8(2), 49-63. https://doi.org/10.53430/ijmru.2024.8.2.0053
  61. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
  62. Vuppalapati, C. (2021). Democratization of Artificial Intelligence for the Future of Humanity. Boca Raton: CRC Press.
  63. Vuppalapati, C., Ilapakurti, A., Kedari, S., Vuppalapati, J., Kedari, S., & Vuppalapati, R. (2020). Democratization of Artificial Intelligence (AI) to small scale farmers: A framework to deploy AI models to tiny IoT edges that operate in constrained environments. Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 652-657. https://doi.org/10.5220/0009358706520657
  64. Wisdom, J. P., Chor, K. H. B., Hoagwood, K. E., & Horwitz, S. M. (2014). Innovation adoption: A review of theories and constructs. Administration and Policy in Mental Health and Mental Health Services Research, 41(4), 480-502. https://doi.org/10.1007/s10488-013-0486-4
  65. Wolf, C. T. (2020). Democratizing AI? Experience and accessibility in the age of artificial intelligence. XRDS: Crossroads, The ACM Magazine for Students, 26(4), 12-15. https://doi.org/10.1145/3398370
  66. Wong, P. H. (2020). Democratizing algorithmic fairness. Philosophy & Technology, 33(2), 225-244. https://doi.org/10.1007/s13347-019-00355-w
  67. Yusuf, S. O., Durodola, R. L., Ocran, G., Abubakar, J. E., Echere, A. Z., & Paul-Adeleye, A. H. (2024). Challenges and opportunities in AI and digital transformation for SMEs: A cross-continental perspective. World Journal of Advanced Research and Reviews, 23(3), 668-678. https://doi.org/10.30574/wjarr.2024.23.3.2511
  68. Zimmermann, A., Di Rossa, E., & Kim, H. (2020). Technology can’t fix algorithmic injustice. Boston Review, 1-15.

Authors

1 Westcott Shulammite Chinwendu
Independent Research, Nigeria
2 Augustine Ebuka Arachie
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
3 Onyinye Ifeoma Okeke
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
4 Fredrick Chukwudi Chiedozie
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

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Vol. 8 No. 1 (2026): August
Section: Articles
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