Impact of AI-Driven Micro-Entrepreneurship: Opportunities, Risks, and Ethical Implications in Emerging Economies.

Publication Date: 18/12/2025

DOI: 10.52589/IJEBI-ABYSGGA2


Author(s): Ugonna Augustina Kalu-Okoro, Udoka Stephen Otika, Chuks Evans Odunna, Uchechukwu Christogonus Egwenike.
Volume/Issue: Volume 8, Issue 4 (2025)
Page No: 110-125
Journal: International Journal of Entrepreneurship and Business Innovation (IJEBI)


Abstract:

Artificial Intelligence (AI) has emerged as a transformative force in the micro-enterprise sector, particularly within emerging economies where resource constraints and infrastructural limitations have traditionally hindered scalability. This study empirically examines the opportunities, risks, and ethical implications of AI-driven micro-entrepreneurship in Nigeria, Kenya, and Bangladesh. Using a mixed-methods approach, data were collected from 367 micro-entrepreneurs through structured surveys and 30 in-depth interviews. Quantitative analysis reveals that AI adoption significantly enhances operational efficiency, customer engagement, and market expansion, with customer engagement emerging as the most impactful driver of performance. However, barriers such as digital skills gaps, high implementation costs, infrastructure limitations, and algorithmic bias hinder equitable adoption. Ethical concerns—particularly data privacy, transparency, and cultural sensitivity—were prominent across all contexts. Regression analysis confirmed a strong positive relationship between AI adoption and business performance, moderated by digital literacy. The study concludes that while AI offers substantial benefits for micro-entrepreneurs, sustainable integration requires targeted policy interventions, capacity building, and culturally adapted AI solutions. Recommendations are proposed for entrepreneurs, policymakers, NGOs, and AI developers to maximize benefits while safeguarding ethical standards.

Keywords:

Artificial Intelligence, Micro-Entrepreneurship, Emerging Economies, Digital Transformation, Ethical AI, Algorithmic Bias, Small-Scale Business Development.

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