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Multilingual AI-Driven Workflows on Ideation, Collaboration, and Linguistic Inclusion for Graduate Entrepreneurs in West Africa


Authors : Nsikak Thompson; Chidera Johnson; Michael Ukpeh; Okengwu U. A.

Volume/Issue : Volume 11 - 2026, Issue 3 - March


Google Scholar : https://tinyurl.com/ycvzyyfu

Scribd : https://tinyurl.com/4ucx45vb

DOI : https://doi.org/10.38124/ijisrt/26mar643

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : The lack of African languages in mainstream Large Language Models (LLMs) creates a significant gap, making it harder for graduate entrepreneurs to fully use Artificial Intelligence (AI) for their business development. This study looks at how multilingual AI-driven workflows affect Ideation, Collaboration, and Linguistic Inclusion for Graduate Entrepreneurs in West Africa. Using an Agile Research Method, we created and tested Agiliter, a multilingual AI platform (English, French, and Igbo) designed with LLM-powered entrepreneurial workflows. We ran tests for six weeks with ten early-stage founders from Nigeria's South-South region. The quantitative data showed a high active participation rate of 65% and a strong preference for multilingual features, as seen in a 28% rate of French use among non-Francophone users for ideation tasks. The qualitative findings indicated that the automated multilingual workflow generation served as a crucial support system. It reduced the cognitive load of using English-only tools in resource-limited settings and encouraged sharing ideas across different regions. We conclude that a multilingual AI focused on specific fields can turn linguistic diversity from a barrier into an advantage for inclusive innovation in Africa. This paper offers a model based on evidence for building AIdriven entrepreneurial capacity in linguistically diverse emerging economies.

Keywords : Artificial Intelligence (AI), Linguistic Inclusion, Entrepreneurship, Multilingual Platform, West Africa.

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The lack of African languages in mainstream Large Language Models (LLMs) creates a significant gap, making it harder for graduate entrepreneurs to fully use Artificial Intelligence (AI) for their business development. This study looks at how multilingual AI-driven workflows affect Ideation, Collaboration, and Linguistic Inclusion for Graduate Entrepreneurs in West Africa. Using an Agile Research Method, we created and tested Agiliter, a multilingual AI platform (English, French, and Igbo) designed with LLM-powered entrepreneurial workflows. We ran tests for six weeks with ten early-stage founders from Nigeria's South-South region. The quantitative data showed a high active participation rate of 65% and a strong preference for multilingual features, as seen in a 28% rate of French use among non-Francophone users for ideation tasks. The qualitative findings indicated that the automated multilingual workflow generation served as a crucial support system. It reduced the cognitive load of using English-only tools in resource-limited settings and encouraged sharing ideas across different regions. We conclude that a multilingual AI focused on specific fields can turn linguistic diversity from a barrier into an advantage for inclusive innovation in Africa. This paper offers a model based on evidence for building AIdriven entrepreneurial capacity in linguistically diverse emerging economies.

Keywords : Artificial Intelligence (AI), Linguistic Inclusion, Entrepreneurship, Multilingual Platform, West Africa.

Paper Submission Last Date
31 - March - 2026

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