IIARD International Institute of Academic Research and Development

INTERNATIONAL JOURNAL OF SOCIAL SCIENCES AND MANAGEMENT RESEARCH (IJSSMR )

E-ISSN 2545-5303
P-ISSN 2695-2203
VOL. 11 NO. 5 2025
DOI: 10.56201/ijssmr.vol.11no5.2025.pg30.64

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AI-Enabled Dashboards for Micro-Enterprise Profitability Optimization: A Pilot Implementation Study

Oyinomomoemi Emmanuel Akpe, Azubike Collins Mgbame, Abraham Ayodeji, Abayomi, Ejielo Ogbuefi, Oluwatobi Opeyemi Adeyelu

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Abstract

Micro-enterprises represent a critical segment of emerging economies, contributing significantly to employment generation and grassroots innovation. However, their sustainability and growth are frequently constrained by limited access to real-time financial insights and decision-support tools. This paper presents a pilot implementation study of AI- enabled dashboards designed to optimize profitability in micro-enterprises by automating data analysis and delivering actionable business intelligence in a visually intuitive format. These dashboards leverage artificial intelligence to aggregate and interpret transactional, inventory, and customer data, enabling micro-entrepreneurs to identify cost inefficiencies, forecast sales trends, and improve resource allocation. The study was conducted across a sample of 30 micro- enterprises operating in retail, food processing, and personal services sectors. Through a mixed-methods approach combining data analytics, field observations, and semi-structured interviews, the paper evaluates the impact of the AI-enabled dashboard on key profitability indicators such as gross margin, operating costs, and cash flow stability. Results reveal that enterprises using the dashboard achieved a 15–25% improvement in profit margins over three months, attributed to better inventory control, pricing strategy adjustments, and more informed purchasing decisions. Key features of the dashboard include natural language queries, predictive analytics, anomaly detection, and automated financial summaries tailored to the literacy levels and operational capacities of micro-entrepreneurs. The system’s low bandwidth requirement and mobile-friendly interface were specifically designed for underserved digital environments. Barriers encountered included initial resistance to technology adoption, data input challenges, and the need for localized training. To address these, the project incorporated onboarding support, itera

keywords:

AI-Enabled Dashboards, Micro-Enterprise, Profitability Optimization, Predictive Analytics, Financial Inclusion, Data-Driven Decision-Making, Business Intelligence, LowTech Solutions, SME Digital Tran

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