Artificial Intelligence and Entrepreneurship: Implications for Sustainable Venture Creation in Nigeria

Abstract

Research Objective: This paper explored the impact of Artificial Intelligence (AI) on entrepreneurship and its implications for sustainable venture creation in Nigeria, focusing on how AI enhances the sustainability of new venture processes and outcomes.

Methodology: A qualitative research approach was adopted, drawing data from various documents, journals, and artefacts to assess the influence of AI on entrepreneurial processes.

Findings: The study revealed that advancements in AI technologies facilitated the identification and exploitation of market opportunities, significantly impacting how entrepreneurs develop, design, and scale their organisations. AI led to promising innovations, accelerated production, enhanced work processes, and improved efficiency.

Conclusion: As a key driver of the Fourth Industrial Revolution, AI has transformed entrepreneurial practices, albeit with implications for job displacement.

Recommendations: The study recommends that the Nigerian government implement a policy framework to establish AI-based entrepreneurial grants and provide low-interest loans to support existing and potential entrepreneurs utilising AI technology.

Keywords: Artificial Intelligence, Entrepreneurship, Sustainable Venture Creation, Nigeria.

References

Ahmed, K. (2015). Google’s Demis Hassabis – Misuse of artificial intelligence ‘could do harm. http://www.bbc.com/news/business-34266 425 Accessed: 6 November 2018.

Amabile, T. (2019). GUIDEPOST: Creativity, artificial intelligence, and a world of surprises Guidepost letter for Academy of management discoveries. Academy of Management Discoveries, 0(ja), null. https://doi.org/10.5465/amd.2019.0075

Arbussa, A., Bikfalvi, A.,& Marquès, P. (2017). Strategic agility-driven business model renewal: the case of an SME. Manag. Decis. 55, 271–293. doi: 10.1108/MD-05-2016-0355

Astebro, T., & Chen, J. (2014). The entrepreneurial earnings puzzle: Mismeasurement or real? Journal of Business Venturing, 29(1), 88–105. 

Baum, J. R.,& Locke, E. A. (2004). The relationship of entrepreneurial traits, skill, and motivation to subsequent venture growth. J. Appl. Psychol. 89, 587–598. doi: 10.1037/0021-9010.89.4.587

Binder, M., & Coad, A. (2016). How satisfied are the self-employed? A life domain view. Journal of Happiness Studies, 17(4), 1409–1433. 

Blanchflower, D. G. (2004). Self-employment: More may not be better. Swedish Economic Policy Review, 11(2), 15–74. 

Cagetti, M., & De Nardi, M. (2006). Entrepreneurship, frictions, and wealth. Journal of Political Economy, 114(5), 835–870. 

Carter, S. (2011). The rewards of entrepreneurship: Exploring the incomes, wealth, and economic wellbeing of entrepreneurial households. Entrepreneurship Theory and Practice, 35(1), 39–55. https://doi. org/10.1111/j.1540-6520.2010. 00422.x

Choudhury, P., Starr, E., & Agarwal, R. (2018). Machine learning and human capital: experimental evidence on productivity complementarities. Harvard Business School. 

Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation. National  Bureau of Economic Research.

Leigh, D. (2009). SWOT Analysis. Handbook of Improving Performance in the Work Place, Vol. 1. https://doi.org/10.1002/9780470592663.ch24

Ekbia, H.R. (2009). Digital artifacts as quasi-objects: Qualification, mediation, and materiality. Journal of the American Society for Information Science and Technology, 60(12), 2554–2566. 

Franco, J. Agustín (2013). Principles of Econometrics from the Giffen Demand. Technological and economic development of economy, 21(4), 557–576

Gaskin, J., Berente, N., Lyytinen, K., &Yoo, Y. (2014). Toward generalizable sociomaterial inquiry: A computational approach for zooming in and out of sociomaterial routines. MIS Quarterly, 38(3), 849–871. 

George et al (2016). Toward the development of a big data analytics capability. Information &Management 53(8),1049-1064.

Girish K, Syeda A & Ayesha S (2011). Magnetic Resonance Imaging (MRI) –A Review. International Journal of Dental Clinics 2011:3(1):65-70.

Gururaj, P. (2021). Artificial intelligence-application in the field of e-commerce. International 

Journal of Research – 9(4), 170–177.

Kaput, M. (2016). The Marketer’s Guide to Artificial Intelligence Terminology. https://www.marketingaiinstitute.com/blog/themarketers-guidetoartificialintelligenceterminology.

Kumar, V., Rajan, B., Venkatesan, R., &Lecinski, J. (2019). Understanding the role of intelligence in personalized engagement marketing. California Management Review, 61(4),135–155. https://doi. org/10.1177/0008125619859317 

Lincoln, Y. & Guba, E. G. (1985) Naturalistic Inquiry. Newbury Park, CA: Sage Publications.

Mahadevan, B. (2000). Business Models for Internet-Based E-Commerce: An Anatomy.California Management Review, 55-69. 

Majchrzak, A. & Malhotra, A. (2013). Towards an information systems perspective and research agenda on crowdsourcing for innovation. Journal of Strategic Information Systems, 22, 257–268.

Majchrzak, A. & Markus, M. (2013). Technology affordances and constraints theory (of MIS). In E. Kessler (Ed.), Encyclopedia of management theory (pp. 832–836). Thousand Oaks, CA: SAGE Publications. 

Nambisan, S. & Zahra, S.A. (2016). The role of demand-side narratives in opportunity formation and enactment. Journal of Business Venturing Insights, 5, 70–75. 

Palanivelu, V. R. & Vasanthi, B. (2020) Role of artificial intelligence in business transformation. International Journal of Advanced Science and Technology 29(4), 392-400.

Parker, G., Van Alstyne, M., & Choudary, S.P. (2016). Platform revolution: How networked markets are transforming the economy–and how to make them work for you. New York: W.W. Norton Publishing. 

Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. https://doi.org/10.5465/amr.2000.2791611(Long, 1983).

Song, X., Yang, S., Huang, Z., & Huang, T. (2019). The Application of Artificial Intelligence in Electronic Commerce. Journal of Physics: Conference Series (3), 1302–1302.

Thurman, N. (2018). Personalization of News. In: Vos, T. P., Hanusch, F., Dimitrakopoulou, D., Geertsema-Sligh, M. and Sehl, A. (Eds.), The International Encyclopedia of Journalism Studies. Massachusetts, USA: Wiley-Blackwell.

Vishnoi, S. K. & Bagga, T. (2019). Artificial intelligence enabled marketing solutions: a review. Indian Journal of Artificial Intelligence Economics & Business, Vo Enabled Marketing  17(4),67-17

Wiklund, J., Wright, M., & Zahra, S. A. (2019). Conquering relevance: Entrepreneurship research’s grand challenge. Entrepreneurship Theory and Practice, 43(3), 419–436. 

Yoo et al. (2010). The new organizing logic of digital innovation: An agenda for information systems research. Information Systems Research, 21(4), 724–735 

Zittrain, J. (2006). The generative Internet. Harvard Law Review, 119(7), 1975–2040.