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AI for Economic Inclusion: Empowering Underserved SMEs Through Intelligent Systems
Subject area: Science,Engineering and Technology · Area of research: Artificial intelligent
DOI: https://doi.org/10.64388/IREV9I3-1710480
Abstract
This paper examines the transformative role of artificial intelligence (AI) in addressing systemic barriers faced by underserved small and medium-sized enterprises (SMEs), particularly those owned by women, minorities, and businesses in rural areas. Through an in-depth review of academic literature, policy frameworks, and case studies, the study highlights how AI-driven tools such as chatbots, predictive analytics, AI-enabled financial planning platforms, and Natural Language Processing (NLP) technologies are democratizing access to critical business resources and fostering equitable economic participation. The findings reveal AI?s potential to enhance SME competitiveness by improving operational efficiency, financial decision-making, and customer engagement, while also identifying persistent challenges related to AI bias, data privacy, digital literacy gaps, and onboarding costs. The paper is structured to first explore academic perspectives on economic inclusion and AI?s application in business, followed by an analysis of digital transformation trends within SME ecosystems. Subsequent sections examine the barriers impeding SME innovation, AI-driven solutions addressing these challenges, and the broader economic impacts of AI empowerment. The study concludes with policy recommendations and strategic pathways to ensure inclusive AI adoption, emphasizing the need for sustained ecosystem support and collaborative public-private initiatives. The anticipated implications for economic policy and innovation ecosystems are profound. AI has the capacity to bridge opportunity gaps, fuel SME-led economic revitalization, and align with broader goals of equity and resilience. However, achieving these outcomes requires intentional policy design, ethical AI deployment principles, and targeted capacity-building efforts to ensure no business is left behind in the digital economy.
Keywords
Artificial Intelligence, SME Competitiveness, Economic Inclusion, AI-Driven Innovation, Digital Transformation, Predictive Analytics, NLP, Financial Access, AI Policy, Digital Equity, Minority-Owned Businesses, Rural SMEs.
How to cite this paper
@article{1710480,
author = {Nkemdirim Mbah},
title = {AI for Economic Inclusion: Empowering Underserved SMEs Through Intelligent Systems},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {3},
pages = {334-352},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710480.pdf},
abstract = {This paper examines the transformative role of artificial intelligence (AI) in addressing systemic barriers faced by underserved small and medium-sized enterprises (SMEs), particularly those owned by women, minorities, and businesses in rural areas. Through an in-depth review of academic literature, policy frameworks, and case studies, the study highlights how AI-driven tools such as chatbots, predictive analytics, AI-enabled financial planning platforms, and Natural Language Processing (NLP) technologies are democratizing access to critical business resources and fostering equitable economic participation. The findings reveal AI?s potential to enhance SME competitiveness by improving operational efficiency, financial decision-making, and customer engagement, while also identifying persistent challenges related to AI bias, data privacy, digital literacy gaps, and onboarding costs. The paper is structured to first explore academic perspectives on economic inclusion and AI?s application in business, followed by an analysis of digital transformation trends within SME ecosystems. Subsequent sections examine the barriers impeding SME innovation, AI-driven solutions addressing these challenges, and the broader economic impacts of AI empowerment. The study concludes with policy recommendations and strategic pathways to ensure inclusive AI adoption, emphasizing the need for sustained ecosystem support and collaborative public-private initiatives. The anticipated implications for economic policy and innovation ecosystems are profound. AI has the capacity to bridge opportunity gaps, fuel SME-led economic revitalization, and align with broader goals of equity and resilience. However, achieving these outcomes requires intentional policy design, ethical AI deployment principles, and targeted capacity-building efforts to ensure no business is left behind in the digital economy.},
keywords = {Artificial Intelligence, SME Competitiveness, Economic Inclusion, AI-Driven Innovation, Digital Transformation, Predictive Analytics, NLP, Financial Access, AI Policy, Digital Equity, Minority-Owned Businesses, Rural SMEs.},
month = {September},
doi = {https://doi.org/10.64388/IREV9I3-1710480}
}